2025-07-17T06:45:43.5888090Z Current runner version: '2.326.0'
2025-07-17T06:45:43.5891220Z Runner name: 'i-06ffcdff1c2e10d08'
2025-07-17T06:45:43.5891640Z Runner group name: 'default'
2025-07-17T06:45:43.5892140Z Machine name: 'ip-10-0-1-119'
2025-07-17T06:45:43.5893590Z ##[group]GITHUB_TOKEN Permissions
2025-07-17T06:45:43.5894650Z Contents: read
2025-07-17T06:45:43.5894960Z Metadata: read
2025-07-17T06:45:43.5895240Z ##[endgroup]
2025-07-17T06:45:43.5896320Z Secret source: Actions
2025-07-17T06:45:43.5896670Z Prepare workflow directory
2025-07-17T06:45:43.7176910Z Prepare all required actions
2025-07-17T06:45:43.7202070Z Getting action download info
2025-07-17T06:45:43.9170580Z Download action repository 'pytorch/test-infra@main' (SHA:a9ec424ad5e5851e47d68139cfd953b4031778d5)
2025-07-17T06:45:44.5734080Z Download action repository 'pytorch/pytorch@main' (SHA:a38f433be2e94a64b095a44ba39879d02d0c2316)
2025-07-17T06:45:49.6150280Z Getting action download info
2025-07-17T06:45:49.7398550Z Download action repository 'actions/checkout@v4' (SHA:11bd71901bbe5b1630ceea73d27597364c9af683)
2025-07-17T06:45:50.0093580Z Getting action download info
2025-07-17T06:45:50.1648870Z Uses: pytorch/pytorch/.github/workflows/_mac-test.yml@refs/heads/main (a38f433be2e94a64b095a44ba39879d02d0c2316)
2025-07-17T06:45:50.1652360Z ##[group] Inputs
2025-07-17T06:45:50.1652650Z   build-environment: macos-py3-arm64
2025-07-17T06:45:50.1654060Z   test-matrix: {"include": [{"config": "default", "shard": 1, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "default", "shard": 2, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "default", "shard": 3, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m1-13"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m1-14"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m2-15"}]}
2025-07-17T06:45:50.1655380Z   sync-tag: 
2025-07-17T06:45:50.1655630Z   python-version: 3.12.7
2025-07-17T06:45:50.1656340Z   timeout-minutes: 270
2025-07-17T06:45:50.1656830Z   disable-monitor: false
2025-07-17T06:45:50.1657120Z   monitor-log-interval: 5
2025-07-17T06:45:50.1657430Z   monitor-data-collect-interval: 1
2025-07-17T06:45:50.1657720Z ##[endgroup]
2025-07-17T06:45:50.1658080Z Complete job name: macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)
2025-07-17T06:45:50.1940210Z ##[group]Run sysctl machdep.cpu.brand_string kern.osproductversion
2025-07-17T06:45:50.1940650Z sysctl machdep.cpu.brand_string kern.osproductversion
2025-07-17T06:45:50.1953560Z shell: /bin/bash -e -l {0}
2025-07-17T06:45:50.1953860Z env:
2025-07-17T06:45:50.1954010Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:45:50.1954220Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:45:50.1954420Z   TEST_CONFIG: default
2025-07-17T06:45:50.1954580Z   SHARD_NUMBER: 1
2025-07-17T06:45:50.1954730Z   NUM_TEST_SHARDS: 3
2025-07-17T06:45:50.1954900Z   PR_BODY: 
2025-07-17T06:45:50.1955040Z ##[endgroup]
2025-07-17T06:45:50.2332920Z machdep.cpu.brand_string: Apple M1
2025-07-17T06:45:50.2333280Z kern.osproductversion: 14.4.1
2025-07-17T06:45:50.2393580Z ##[group]Run for PROCESS in "python" "conda" "ninja" "clang"; do
2025-07-17T06:45:50.2393940Z for PROCESS in "python" "conda" "ninja" "clang"; do
2025-07-17T06:45:50.2394230Z   echo "Cleaning up all remaining ${PROCESS} process"
2025-07-17T06:45:50.2394490Z   pkill "${PROCESS}" || true
2025-07-17T06:45:50.2394680Z done
2025-07-17T06:45:50.2405930Z shell: /bin/bash -e -l {0}
2025-07-17T06:45:50.2406100Z env:
2025-07-17T06:45:50.2406250Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:45:50.2406480Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:45:50.2406670Z   TEST_CONFIG: default
2025-07-17T06:45:50.2406820Z   SHARD_NUMBER: 1
2025-07-17T06:45:50.2406980Z   NUM_TEST_SHARDS: 3
2025-07-17T06:45:50.2407130Z   PR_BODY: 
2025-07-17T06:45:50.2407260Z ##[endgroup]
2025-07-17T06:45:50.2652430Z Cleaning up all remaining python process
2025-07-17T06:45:50.2729260Z Cleaning up all remaining conda process
2025-07-17T06:45:50.2771740Z Cleaning up all remaining ninja process
2025-07-17T06:45:50.2813160Z Cleaning up all remaining clang process
2025-07-17T06:45:50.2881190Z ##[group]Run if brew list miniconda; then
2025-07-17T06:45:50.2881460Z if brew list miniconda; then
2025-07-17T06:45:50.2881680Z   brew uninstall miniconda
2025-07-17T06:45:50.2881920Z   echo "REINSTALL_BREW_MINICONDA=1" >> "${GITHUB_ENV}"
2025-07-17T06:45:50.2882170Z fi
2025-07-17T06:45:50.2893240Z shell: /bin/bash -e -l {0}
2025-07-17T06:45:50.2893420Z env:
2025-07-17T06:45:50.2893560Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:45:50.2893750Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:45:50.2893970Z   TEST_CONFIG: default
2025-07-17T06:45:50.2894120Z   SHARD_NUMBER: 1
2025-07-17T06:45:50.2894280Z   NUM_TEST_SHARDS: 3
2025-07-17T06:45:50.2894440Z   PR_BODY: 
2025-07-17T06:45:50.2894580Z ##[endgroup]
2025-07-17T06:45:51.7364120Z find: /opt/homebrew/Caskroom/miniconda: No such file or directory
2025-07-17T06:45:51.7388920Z ##[error]Failure while executing; `/usr/bin/env find /opt/homebrew/Caskroom/miniconda -not -type d -not -name .DS_Store -print` exited with 1. Here's the output:
find: /opt/homebrew/Caskroom/miniconda: No such file or directory


2025-07-17T06:45:51.7535060Z ##[group]Run for dir in  ~/.local/lib/python3.*/site-packages; do
2025-07-17T06:45:51.7535410Z for dir in  ~/.local/lib/python3.*/site-packages; do
2025-07-17T06:45:51.7535650Z   echo "Cleaning up ${dir}"
2025-07-17T06:45:51.7535840Z   rm -rf "${dir}"
2025-07-17T06:45:51.7536000Z done
2025-07-17T06:45:51.7547100Z shell: /bin/bash -e -l {0}
2025-07-17T06:45:51.7547260Z env:
2025-07-17T06:45:51.7547390Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:45:51.7547550Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:45:51.7547740Z   TEST_CONFIG: default
2025-07-17T06:45:51.7547880Z   SHARD_NUMBER: 1
2025-07-17T06:45:51.7548030Z   NUM_TEST_SHARDS: 3
2025-07-17T06:45:51.7548190Z   PR_BODY: 
2025-07-17T06:45:51.7548330Z ##[endgroup]
2025-07-17T06:45:51.7893630Z Cleaning up /Users/ec2-user/.local/lib/python3.11/site-packages
2025-07-17T06:45:51.9350960Z ##[group]Run pytorch/test-infra/.github/actions/check-disk-space@main
2025-07-17T06:45:51.9351220Z with:
2025-07-17T06:45:51.9351380Z   minimum-available-space-in-gb: 6
2025-07-17T06:45:51.9351550Z env:
2025-07-17T06:45:51.9351680Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:45:51.9351860Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:45:51.9352030Z   TEST_CONFIG: default
2025-07-17T06:45:51.9352170Z   SHARD_NUMBER: 1
2025-07-17T06:45:51.9352290Z   NUM_TEST_SHARDS: 3
2025-07-17T06:45:51.9352410Z   PR_BODY: 
2025-07-17T06:45:51.9352530Z ##[endgroup]
2025-07-17T06:45:51.9428620Z ##[group]Run echo "Print the available disk space for manual inspection"
2025-07-17T06:45:51.9429010Z echo "Print the available disk space for manual inspection"
2025-07-17T06:45:51.9429290Z df -h
2025-07-17T06:45:51.9429420Z 
2025-07-17T06:45:51.9429590Z function check_disk_space() {
2025-07-17T06:45:51.9429770Z   set +e
2025-07-17T06:45:51.9429920Z 
2025-07-17T06:45:51.9430080Z   # Set the minimum requirement space to 6GB
2025-07-17T06:45:51.9430390Z   MINIMUM_AVAILABLE_SPACE_IN_KB=$(($MINIMUM_AVAILABLE_SPACE_IN_GB * 1024 * 1024))
2025-07-17T06:45:51.9430660Z 
2025-07-17T06:45:51.9430830Z   # Use KB to avoid floating point warning like 3.1GB
2025-07-17T06:45:51.9431100Z   df -k | tr -s ' ' | cut -d' ' -f 4,9 | while read -r LINE;
2025-07-17T06:45:51.9431310Z   do
2025-07-17T06:45:51.9431460Z     AVAIL=$(echo $LINE | cut -f1 -d' ')
2025-07-17T06:45:51.9431690Z     MOUNT=$(echo $LINE | cut -f2 -d' ')
2025-07-17T06:45:51.9431870Z 
2025-07-17T06:45:51.9432000Z     if [ "${MOUNT}" = "/" ]; then
2025-07-17T06:45:51.9432310Z       if [ "${AVAIL}" -lt "${MINIMUM_AVAILABLE_SPACE_IN_KB}" ]; then
2025-07-17T06:45:51.9433040Z         echo "Failure: There is only ${AVAIL}KB free space left in ${MOUNT}, which is less than the minimum requirement of ${MINIMUM_AVAILABLE_SPACE_IN_KB}KB for ${RUNNER_OS}"
2025-07-17T06:45:51.9433470Z       else
2025-07-17T06:45:51.9433750Z         echo "Success: There is ${AVAIL}KB free space left in ${MOUNT} for ${RUNNER_OS}, continue"
2025-07-17T06:45:51.9434040Z       fi
2025-07-17T06:45:51.9434160Z     fi
2025-07-17T06:45:51.9434290Z   done
2025-07-17T06:45:51.9434420Z 
2025-07-17T06:45:51.9434530Z   set -e
2025-07-17T06:45:51.9434650Z }
2025-07-17T06:45:51.9434820Z 
2025-07-17T06:45:51.9434940Z RESULT=$(check_disk_space)
2025-07-17T06:45:51.9435120Z echo "${RESULT}"
2025-07-17T06:45:51.9435280Z 
2025-07-17T06:45:51.9435460Z if [[ "${RESULT}" == *Failure* && "${RUNNER_OS}" == "macOS" ]]; then
2025-07-17T06:45:51.9435950Z   # We can clean up /System/Library/Caches/com.apple.coresymbolicationd on MacOS to free up the space and this should free up enough space
2025-07-17T06:45:51.9436430Z   # https://github.com/pytorch/pytorch/issues/85440
2025-07-17T06:45:51.9436740Z   sudo rm "/System/Library/Caches/com.apple.coresymbolicationd/data" || true
2025-07-17T06:45:51.9437210Z   # Stop the daemon and launchctl will automatically start it again, thus accomplish a restart and free up the above file
2025-07-17T06:45:51.9437630Z   sudo launchctl stop com.apple.coresymbolicationd || true
2025-07-17T06:45:51.9437850Z 
2025-07-17T06:45:51.9437990Z   # Clean up crash reports on the runner
2025-07-17T06:45:51.9438270Z   sudo rm -rf "/System/Volumes/Data/Library/Logs/CrashReporter" || true
2025-07-17T06:45:51.9438520Z 
2025-07-17T06:45:51.9438690Z   # Also try to clean up torch.hub caching directory
2025-07-17T06:45:51.9438950Z   rm -rf "${HOME}/.cache/torch/hub" || true
2025-07-17T06:45:51.9439150Z 
2025-07-17T06:45:51.9439470Z   # Purge conda
2025-07-17T06:45:51.9439630Z   conda clean -p -t -y || true
2025-07-17T06:45:51.9439800Z   # and pip cache
2025-07-17T06:45:51.9439950Z   pip cache purge || true
2025-07-17T06:45:51.9440100Z 
2025-07-17T06:45:51.9440280Z   echo "Re-run disk space check for ${RUNNER_OS} after cleaning up"
2025-07-17T06:45:51.9440510Z   # Re-run the check
2025-07-17T06:45:51.9440670Z   RESULT=$(check_disk_space)
2025-07-17T06:45:51.9440840Z   echo "${RESULT}"
2025-07-17T06:45:51.9440980Z fi
2025-07-17T06:45:51.9441160Z 
2025-07-17T06:45:51.9441330Z if [[ "${RESULT}" == *Failure* ]]; then
2025-07-17T06:45:51.9441510Z   df -h
2025-07-17T06:45:51.9441620Z 
2025-07-17T06:45:51.9442020Z   echo "Please help create an issue to PyTorch Release Engineering via https://github.com/pytorch/test-infra/issues and provide the link to the workflow run."
2025-07-17T06:45:51.9442460Z   exit 1
2025-07-17T06:45:51.9442570Z fi
2025-07-17T06:45:51.9454320Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T06:45:51.9454520Z env:
2025-07-17T06:45:51.9454630Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:45:51.9454790Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:45:51.9454960Z   TEST_CONFIG: default
2025-07-17T06:45:51.9455110Z   SHARD_NUMBER: 1
2025-07-17T06:45:51.9455240Z   NUM_TEST_SHARDS: 3
2025-07-17T06:45:51.9455380Z   PR_BODY: 
2025-07-17T06:45:51.9455510Z   MINIMUM_AVAILABLE_SPACE_IN_GB: 6
2025-07-17T06:45:51.9455670Z ##[endgroup]
2025-07-17T06:45:51.9680160Z Print the available disk space for manual inspection
2025-07-17T06:45:51.9692650Z Filesystem        Size    Used   Avail Capacity iused ifree %iused  Mounted on
2025-07-17T06:45:51.9693100Z /dev/disk5s2s1   256Gi   9.5Gi   103Gi     9%    404k  1.1G    0%   /
2025-07-17T06:45:51.9693830Z devfs            217Ki   217Ki     0Bi   100%     752     0  100%   /dev
2025-07-17T06:45:51.9694230Z /dev/disk5s5     256Gi   2.0Gi   103Gi     2%       2  1.1G    0%   /System/Volumes/VM
2025-07-17T06:45:51.9694640Z /dev/disk5s3     256Gi   5.7Gi   103Gi     6%    1.0k  1.1G    0%   /System/Volumes/Preboot
2025-07-17T06:45:51.9695030Z /dev/disk1s2     500Mi   6.0Mi   387Mi     2%       1  4.0M    0%   /System/Volumes/xarts
2025-07-17T06:45:51.9695420Z /dev/disk1s1     500Mi    53Mi   387Mi    13%      61  4.0M    0%   /System/Volumes/iSCPreboot
2025-07-17T06:45:51.9695820Z /dev/disk1s3     500Mi   940Ki   387Mi     1%      51  4.0M    0%   /System/Volumes/Hardware
2025-07-17T06:45:51.9696190Z /dev/disk5s1     256Gi   135Gi   103Gi    57%    7.2M  1.1G    1%   /System/Volumes/Data
2025-07-17T06:45:51.9696570Z map auto_home      0Bi     0Bi     0Bi   100%       0     0     -   /System/Volumes/Data/home
2025-07-17T06:45:51.9696960Z /dev/disk3s4     228Gi   120Ki   210Gi     1%      18  2.2G    0%   /private/tmp/tmp-mount-g9r1EB
2025-07-17T06:45:52.0079520Z Success: There is 107537728KB free space left in / for macOS, continue
2025-07-17T06:45:52.0161210Z ##[group]Run pytorch/pytorch/.github/actions/checkout-pytorch@main
2025-07-17T06:45:52.0161480Z with:
2025-07-17T06:45:52.0161600Z   submodules: recursive
2025-07-17T06:45:52.0161760Z   fetch-depth: 0
2025-07-17T06:45:52.0161890Z env:
2025-07-17T06:45:52.0162020Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:45:52.0162190Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:45:52.0162370Z   TEST_CONFIG: default
2025-07-17T06:45:52.0162510Z   SHARD_NUMBER: 1
2025-07-17T06:45:52.0162660Z   NUM_TEST_SHARDS: 3
2025-07-17T06:45:52.0162800Z   PR_BODY: 
2025-07-17T06:45:52.0162920Z ##[endgroup]
2025-07-17T06:45:52.0188520Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-07-17T06:45:52.0189080Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
2025-07-17T06:45:52.0200670Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T06:45:52.0200900Z env:
2025-07-17T06:45:52.0201050Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:45:52.0201210Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:45:52.0201380Z   TEST_CONFIG: default
2025-07-17T06:45:52.0201500Z   SHARD_NUMBER: 1
2025-07-17T06:45:52.0201640Z   NUM_TEST_SHARDS: 3
2025-07-17T06:45:52.0201760Z   PR_BODY: 
2025-07-17T06:45:52.0201860Z ##[endgroup]
2025-07-17T06:45:52.0480790Z ##[group]Run # Use all available CPUs for fetching
2025-07-17T06:45:52.0481080Z # Use all available CPUs for fetching
2025-07-17T06:45:52.0481280Z cd "${GITHUB_WORKSPACE}"
2025-07-17T06:45:52.0481510Z git config --global fetch.parallel 0
2025-07-17T06:45:52.0481740Z git config --global submodule.fetchJobs 0
2025-07-17T06:45:52.0481940Z 
2025-07-17T06:45:52.0482170Z # Clean workspace. The default checkout action should also do this, but
2025-07-17T06:45:52.0482470Z # do it here as well just in case
2025-07-17T06:45:52.0482690Z if [[ -d .git ]]; then
2025-07-17T06:45:52.0482880Z   if [ -z "${NO_SUDO}" ]; then
2025-07-17T06:45:52.0483060Z     sudo git clean -ffdx
2025-07-17T06:45:52.0483230Z   else
2025-07-17T06:45:52.0483380Z     git clean -ffdx
2025-07-17T06:45:52.0483530Z   fi
2025-07-17T06:45:52.0483650Z fi
2025-07-17T06:45:52.0494680Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T06:45:52.0494900Z env:
2025-07-17T06:45:52.0495050Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:45:52.0495220Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:45:52.0495400Z   TEST_CONFIG: default
2025-07-17T06:45:52.0495540Z   SHARD_NUMBER: 1
2025-07-17T06:45:52.0495690Z   NUM_TEST_SHARDS: 3
2025-07-17T06:45:52.0495830Z   PR_BODY: 
2025-07-17T06:45:52.0495940Z   NO_SUDO: 
2025-07-17T06:45:52.0496260Z ##[endgroup]
2025-07-17T06:45:54.3249530Z Removing .additional_ci_files/
2025-07-17T06:45:54.3249910Z Removing .pytest_cache/
2025-07-17T06:45:54.3250200Z Removing benchmarks/functional_autograd_benchmark/__pycache__/
2025-07-17T06:45:54.3250470Z Removing build/
2025-07-17T06:45:54.3250630Z Removing dist/
2025-07-17T06:45:54.3250810Z Removing test/.pytorch-disabled-tests.json
2025-07-17T06:45:54.3251030Z Removing test/__pycache__/
2025-07-17T06:45:54.3251270Z Removing test/custom_backend/__pycache__/
2025-07-17T06:45:54.3251490Z Removing test/custom_backend/build/
2025-07-17T06:45:54.3251710Z Removing test/custom_backend/test-reports/
2025-07-17T06:45:54.3251920Z Removing test/dynamo/__pycache__/
2025-07-17T06:45:54.3252140Z Removing test/export/__pycache__/
2025-07-17T06:45:54.3252340Z Removing test/functorch/__pycache__/
2025-07-17T06:45:54.3252620Z Removing test/inductor/__pycache__/
2025-07-17T06:45:54.3252880Z Removing test/jit/__pycache__/
2025-07-17T06:45:54.3253070Z Removing test/jit_hooks/build/
2025-07-17T06:45:54.3253360Z Removing test/jit_hooks/model_test_forward_tuple_input.pt
2025-07-17T06:45:54.3254270Z Removing test/jit_hooks/model_test_module_forward_multiple_inputs.pt
2025-07-17T06:45:54.3254650Z Removing test/jit_hooks/model_test_module_forward_single_input.pt
2025-07-17T06:45:54.3254990Z Removing test/jit_hooks/model_test_module_hook_return_nothing.pt
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2025-07-17T06:45:54.3317260Z ##[group]Run actions/checkout@v4
2025-07-17T06:45:54.3317430Z with:
2025-07-17T06:45:54.3317580Z   ref: a38f433be2e94a64b095a44ba39879d02d0c2316
2025-07-17T06:45:54.3317760Z   fetch-depth: 0
2025-07-17T06:45:54.3317880Z   submodules: recursive
2025-07-17T06:45:54.3318030Z   show-progress: false
2025-07-17T06:45:54.3318180Z   repository: pytorch/pytorch
2025-07-17T06:45:54.3318410Z   token: ***
2025-07-17T06:45:54.3318550Z   ssh-strict: true
2025-07-17T06:45:54.3318680Z   ssh-user: git
2025-07-17T06:45:54.3318820Z   persist-credentials: true
2025-07-17T06:45:54.3318980Z   clean: true
2025-07-17T06:45:54.3319310Z   sparse-checkout-cone-mode: true
2025-07-17T06:45:54.3319480Z   fetch-tags: false
2025-07-17T06:45:54.3319610Z   lfs: false
2025-07-17T06:45:54.3319760Z   set-safe-directory: true
2025-07-17T06:45:54.3319910Z env:
2025-07-17T06:45:54.3320010Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:45:54.3320190Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:45:54.3320390Z   TEST_CONFIG: default
2025-07-17T06:45:54.3320540Z   SHARD_NUMBER: 1
2025-07-17T06:45:54.3320670Z   NUM_TEST_SHARDS: 3
2025-07-17T06:45:54.3320800Z   PR_BODY: 
2025-07-17T06:45:54.3320930Z ##[endgroup]
2025-07-17T06:45:54.4235740Z Syncing repository: pytorch/pytorch
2025-07-17T06:45:54.4236650Z ##[group]Getting Git version info
2025-07-17T06:45:54.4236920Z Working directory is '/Users/ec2-user/runner/_work/pytorch/pytorch'
2025-07-17T06:45:54.4237310Z [command]/usr/bin/git version
2025-07-17T06:45:54.4267140Z git version 2.39.3 (Apple Git-146)
2025-07-17T06:45:54.4280110Z ##[endgroup]
2025-07-17T06:45:54.4288250Z Copying '/Users/ec2-user/.gitconfig' to '/Users/ec2-user/runner/_work/_temp/e5a70eb8-a968-4547-9cc6-eafbd1449512/.gitconfig'
2025-07-17T06:45:54.4294150Z Temporarily overriding HOME='/Users/ec2-user/runner/_work/_temp/e5a70eb8-a968-4547-9cc6-eafbd1449512' before making global git config changes
2025-07-17T06:45:54.4294740Z Adding repository directory to the temporary git global config as a safe directory
2025-07-17T06:45:54.4297060Z [command]/usr/bin/git config --global --add safe.directory /Users/ec2-user/runner/_work/pytorch/pytorch
2025-07-17T06:45:54.4367420Z [command]/usr/bin/git config --local --get remote.origin.url
2025-07-17T06:45:54.4418250Z https://github.com/pytorch/pytorch
2025-07-17T06:45:54.4426950Z ##[group]Removing previously created refs, to avoid conflicts
2025-07-17T06:45:54.4429090Z [command]/usr/bin/git rev-parse --symbolic-full-name --verify --quiet HEAD
2025-07-17T06:45:54.4559100Z HEAD
2025-07-17T06:45:54.4627240Z ##[endgroup]
2025-07-17T06:45:54.4629380Z [command]/usr/bin/git submodule status
2025-07-17T06:45:54.5432290Z  7e1e1fe3858c63c251c637ae41a20de425dde96f android/libs/fbjni (v0.1.0-12-g7e1e1fe)
2025-07-17T06:45:54.5725330Z  4dfe081cf6bcd15db339cf2680b9281b8451eeb3 third_party/FP16 (4dfe081)
2025-07-17T06:45:54.5986550Z  b408327ac2a15ec3e43352421954f5b1967701d1 third_party/FXdiv (b408327)
2025-07-17T06:45:54.6326240Z  c07e3a0400713d546e0dea2d5466dd22ea389c73 third_party/NNPACK (c07e3a0)
2025-07-17T06:45:54.6760320Z  2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07 third_party/NVTX (v3.1.0-263-g2942f16)
2025-07-17T06:45:54.7260410Z  1d8f600fd424278486eade7ed3e877c99f0846b1 third_party/VulkanMemoryAllocator (v2.1.0-982-g1d8f600)
2025-07-17T06:45:54.9352160Z  51a0103656eff6fc9bfd39a4597923c4b542c883 third_party/XNNPACK (remotes/origin/ds/ndk-1243-g51a0103656)
2025-07-17T06:45:54.9738600Z  01aae101b9e5e94d6c16a9514c9fb8df99c93150 third_party/aiter (v0.1.1-92-g01aae101)
2025-07-17T06:45:54.9966940Z  299e5928955cc62af9968370293b916f5130916f third_party/benchmark (v1.9.3)
2025-07-17T06:45:55.0742130Z  434d19f696da62c12b5372b32cbc9ba968588d7e third_party/composable_kernel (rocm-6.4.1-172-g434d19f69)
2025-07-17T06:45:55.1235980Z  3af7f2c16147f3fbc6e4d717032daf505dc1652c third_party/cpp-httplib (v0.20.1)
2025-07-17T06:45:55.1733650Z  5e3d2445e6a84d9599bee2bf78edbb4d80865e1d third_party/cpuinfo (5e3d244)
2025-07-17T06:45:55.2141650Z  f937055efc6d414d11f4c6577e3977fe74f35fb6 third_party/cudnn_frontend (v0.5-52-gf937055)
2025-07-17T06:45:55.2777060Z  b995f933179c22d3fe0d871c3a53d11e4681950f third_party/cutlass (v4.0.0)
2025-07-17T06:45:55.3456800Z  157e88b750c452bef2ab4653fe9d1eeb151ce4c3 third_party/fbgemm (v1.2.0-186-g157e88b7)
2025-07-17T06:45:55.3846120Z  979702c87a8713a8e0a5e9fee122b90d2ef13be5 third_party/flash-attention (v2.7.4)
2025-07-17T06:45:55.4006690Z  a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757 third_party/flatbuffers (v24.12.23)
2025-07-17T06:45:55.5150830Z  40626af88bd7df9a5fb80be7b25ac85b122d6c21 third_party/fmt (11.2.0)
2025-07-17T06:45:55.5498970Z  3fb5c176c17c765a3492cd2f0321b0dab712f350 third_party/gemmlowp/gemmlowp (remotes/origin/revert-87-master-135-g3fb5c17)
2025-07-17T06:45:55.5971030Z  c7b7b022c124d9643957d9bd55f57ac59fce8fa2 third_party/gloo (remotes/origin/gh/c-p-i-o/1/base-33-gc7b7b02)
2025-07-17T06:45:55.6738750Z  52eb8108c5bdec04579160ae17225d66034bd723 third_party/googletest (release-1.8.0-3544-g52eb8108)
2025-07-17T06:45:55.7133730Z  719d8e6cd7f7a0e01b155657526d693acf97c2b3 third_party/ideep (pytorch-rls-v3.7.1)
2025-07-17T06:45:55.7426710Z  dec1d23ca65ab069d225dfe40dea14f455170959 third_party/ittapi (v3.25.5)
2025-07-17T06:45:55.8157990Z  5e7501833f1021ce6f618572d3baf657b6319658 third_party/kineto (remotes/origin/sraikund/test-98-g5e75018)
2025-07-17T06:45:55.8378280Z  cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7 third_party/kleidiai (v1.8.0)
2025-07-17T06:45:55.8523630Z  fbd8b99c2b828428947d70fdc046bb55609be93e third_party/mimalloc (v2.2.4)
2025-07-17T06:45:55.8708210Z  55f93686c01528224f448c19128836e7df245f72 third_party/nlohmann (v3.12.0)
2025-07-17T06:45:55.9871240Z  e709452ef2bbc1d113faf678c24e6d3467696e83 third_party/onnx (v1.18.0)
2025-07-17T06:45:56.0045470Z  a799f4aed9c94b765dcdaabaeab7d5e7e2310878 third_party/opentelemetry-cpp (v1.14.2)
2025-07-17T06:45:56.0191230Z  0fa0ef591e38c2758e3184c6c23e497b9f732ffa third_party/pocketfft (release_for_eigen-40-g0fa0ef5)
2025-07-17T06:45:56.2544120Z  d1eca4e4b421cd2997495c4b4e65cea6be4e9b8a third_party/protobuf (v3.7.0-rc.2-1279-gd1eca4e4b)
2025-07-17T06:45:56.2768700Z  072586a71b55b7f8c584153d223e95687148a900 third_party/psimd (heads/master)
2025-07-17T06:45:56.2984320Z  4fe0e1e183925bf8cfa6aae24237e724a96479b8 third_party/pthreadpool (0.1-144-g4fe0e1e)
2025-07-17T06:45:56.3624590Z  a2e59f0e7065404b44dfe92a28aca47ba1378dc4 third_party/pybind11 (v2.11.0-182-ga2e59f0e)
2025-07-17T06:45:56.3871910Z  f45429b087dd7d5bc78bb40dc7cf06425c252d67 third_party/python-peachpy (remotes/origin/pre-generated)
2025-07-17T06:45:56.4297120Z  5a1d179df9cf652951b59010a2d2075372d67f68 third_party/sleef (3.8)
2025-07-17T06:45:56.4557730Z  52791a2fd214b2a9dc5759d36725909c1daa7f2e third_party/tensorpipe (remotes/origin/master)
2025-07-17T06:45:56.4566110Z ##[group]Cleaning the repository
2025-07-17T06:45:56.4568190Z [command]/usr/bin/git clean -ffdx
2025-07-17T06:45:56.4944770Z [command]/usr/bin/git reset --hard HEAD
2025-07-17T06:45:58.2381940Z HEAD is now at 5ffebcbddfd Update
2025-07-17T06:45:58.2390640Z ##[endgroup]
2025-07-17T06:45:58.2390950Z ##[group]Disabling automatic garbage collection
2025-07-17T06:45:58.2395360Z [command]/usr/bin/git config --local gc.auto 0
2025-07-17T06:45:58.2468810Z ##[endgroup]
2025-07-17T06:45:58.2469150Z ##[group]Setting up auth
2025-07-17T06:45:58.2472230Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand
2025-07-17T06:45:58.2532660Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'core\.sshCommand' && git config --local --unset-all 'core.sshCommand' || :"
2025-07-17T06:45:58.3028320Z Entering 'android/libs/fbjni'
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2025-07-17T06:45:58.3362280Z Entering 'third_party/NNPACK'
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2025-07-17T06:45:58.3717380Z Entering 'third_party/XNNPACK'
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2025-07-17T06:45:58.4198090Z Entering 'third_party/aiter/3rdparty/composable_kernel'
2025-07-17T06:45:58.4401470Z Entering 'third_party/benchmark'
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2025-07-17T06:45:59.5065720Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader
2025-07-17T06:45:59.5127120Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'http\.https\:\/\/github\.com\/\.extraheader' && git config --local --unset-all 'http.https://github.com/.extraheader' || :"
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2025-07-17T06:46:00.3491930Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic ***
2025-07-17T06:46:00.3563080Z ##[endgroup]
2025-07-17T06:46:00.3563340Z ##[group]Fetching the repository
2025-07-17T06:46:00.3567560Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/*
2025-07-17T06:46:06.5085690Z From https://github.com/pytorch/pytorch
2025-07-17T06:46:06.5086550Z  - [deleted]                 (none)     -> ciflow/inductor/157605
2025-07-17T06:46:06.6481310Z  - [deleted]                 (none)     -> ciflow/inductor/158288
2025-07-17T06:46:06.6481620Z  - [deleted]                 (none)     -> ciflow/inductor/158291
2025-07-17T06:46:06.6481880Z  - [deleted]                 (none)     -> ciflow/inductor/158402
2025-07-17T06:46:06.6482530Z  - [deleted]                 (none)     -> ciflow/inductor/158450
2025-07-17T06:46:06.6483980Z  - [deleted]                 (none)     -> ciflow/inductor/158527
2025-07-17T06:46:06.6484370Z  - [deleted]                 (none)     -> ciflow/trunk/147501
2025-07-17T06:46:06.6485150Z  - [deleted]                 (none)     -> ciflow/trunk/157605
2025-07-17T06:46:06.6486070Z  - [deleted]                 (none)     -> ciflow/trunk/158290
2025-07-17T06:46:06.6486970Z  - [deleted]                 (none)     -> ciflow/trunk/158291
2025-07-17T06:46:06.6488240Z  - [deleted]                 (none)     -> ciflow/trunk/158402
2025-07-17T06:46:06.6488630Z  - [deleted]                 (none)     -> ciflow/trunk/158407
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2025-07-17T06:46:06.6490380Z  - [deleted]                 (none)     -> ciflow/trunk/158484
2025-07-17T06:46:06.6491230Z  - [deleted]                 (none)     -> ciflow/trunk/158527
2025-07-17T06:46:08.5900970Z  * [new branch]              angelayi/pytree          -> origin/angelayi/pytree
2025-07-17T06:46:08.5913470Z  * [new branch]              ezyang/wip-aot-descriptors -> origin/ezyang/wip-aot-descriptors
2025-07-17T06:46:08.5931030Z  * [new branch]              gh/XuehaiPan/369/base    -> origin/gh/XuehaiPan/369/base
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2025-07-17T06:46:08.5946790Z    ee0992871c9..c990ad206d8  gh/andyanwang/32/base    -> origin/gh/andyanwang/32/base
2025-07-17T06:46:08.5954580Z    d9e6d5331c5..5bc5bb4e713  gh/andyanwang/32/head    -> origin/gh/andyanwang/32/head
2025-07-17T06:46:08.5962160Z  + 2487a36a1a9...c089f70741b gh/andyanwang/32/orig    -> origin/gh/andyanwang/32/orig  (forced update)
2025-07-17T06:46:08.5970610Z  * [new branch]              gh/bobrenjc93/536/base   -> origin/gh/bobrenjc93/536/base
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2025-07-17T06:46:08.6007550Z    54d17043330..23d08a8c38a  gh/guangyey/168/head     -> origin/gh/guangyey/168/head
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2025-07-17T06:46:08.6203130Z    0d481c36592..7770f763058  gh/ydwu4/282/head        -> origin/gh/ydwu4/282/head
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2025-07-17T06:46:08.6229950Z    1839e8d04b8..a38f433be2e  main                     -> origin/main
2025-07-17T06:46:08.6268310Z  + 3c611c95e3a...228824d2cbe mlazos/nested-dc         -> origin/mlazos/nested-dc  (forced update)
2025-07-17T06:46:08.6299400Z  + 3133820e94e...67b6d88e85c update_submodule_FBGEMM  -> origin/update_submodule_FBGEMM  (forced update)
2025-07-17T06:46:08.6307830Z  + a8647ccd0db...aa6f3f622b4 update_submodule_kineto  -> origin/update_submodule_kineto  (forced update)
2025-07-17T06:46:08.6322320Z    ada44e5ba78..f6d138807f1  viable/strict            -> origin/viable/strict
2025-07-17T06:46:08.6339240Z  t [tag update]              ciflow/inductor/155958   -> ciflow/inductor/155958
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2025-07-17T06:46:08.6379120Z  t [tag update]              ciflow/rocm-mi300/158221 -> ciflow/rocm-mi300/158221
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2025-07-17T06:46:08.6405170Z  * [new tag]                 ciflow/triton_binaries/158459 -> ciflow/triton_binaries/158459
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2025-07-17T06:46:08.6443860Z  * [new tag]                 trunk/9636e2cfd3e995ef977f670ad47e8e895296d992 -> trunk/9636e2cfd3e995ef977f670ad47e8e895296d992
2025-07-17T06:46:08.6445730Z  * [new tag]                 trunk/9f37cce69334bccebf4b21503f0047d0c0bb320c -> trunk/9f37cce69334bccebf4b21503f0047d0c0bb320c
2025-07-17T06:46:08.6447610Z  * [new tag]                 trunk/a38f433be2e94a64b095a44ba39879d02d0c2316 -> trunk/a38f433be2e94a64b095a44ba39879d02d0c2316
2025-07-17T06:46:08.6453170Z  * [new tag]                 trunk/d9426a81d2ab54f809a3b32a6ab2e606073fe66f -> trunk/d9426a81d2ab54f809a3b32a6ab2e606073fe66f
2025-07-17T06:46:08.6455940Z  * [new tag]                 trunk/ebf83b8b7772632c0558db9a88281ee10ff2df38 -> trunk/ebf83b8b7772632c0558db9a88281ee10ff2df38
2025-07-17T06:46:08.7958960Z [command]/usr/bin/git rev-parse --verify --quiet a38f433be2e94a64b095a44ba39879d02d0c2316^{object}
2025-07-17T06:46:08.8030830Z a38f433be2e94a64b095a44ba39879d02d0c2316
2025-07-17T06:46:08.8035030Z ##[endgroup]
2025-07-17T06:46:08.8035280Z ##[group]Determining the checkout info
2025-07-17T06:46:08.8035710Z ##[endgroup]
2025-07-17T06:46:08.8037810Z [command]/usr/bin/git sparse-checkout disable
2025-07-17T06:46:08.8230540Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig
2025-07-17T06:46:08.8294970Z ##[group]Checking out the ref
2025-07-17T06:46:08.8296610Z [command]/usr/bin/git checkout --progress --force a38f433be2e94a64b095a44ba39879d02d0c2316
2025-07-17T06:46:09.3374540Z Previous HEAD position was 5ffebcbddfd Update
2025-07-17T06:46:09.3403300Z HEAD is now at a38f433be2e [Docker builds] Move from Miniconda to Miniforge (#158370)
2025-07-17T06:46:09.3413980Z ##[endgroup]
2025-07-17T06:46:09.3414290Z ##[group]Setting up auth for fetching submodules
2025-07-17T06:46:09.3446400Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic ***
2025-07-17T06:46:09.3534990Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf
2025-07-17T06:46:09.3596970Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com:
2025-07-17T06:46:09.3656650Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com:
2025-07-17T06:46:09.3715290Z ##[endgroup]
2025-07-17T06:46:09.3715520Z ##[group]Fetching submodules
2025-07-17T06:46:09.3717680Z [command]/usr/bin/git submodule sync --recursive
2025-07-17T06:46:09.4257850Z Synchronizing submodule url for 'android/libs/fbjni'
2025-07-17T06:46:09.4298570Z Synchronizing submodule url for 'third_party/FP16'
2025-07-17T06:46:09.4336290Z Synchronizing submodule url for 'third_party/FXdiv'
2025-07-17T06:46:09.4372830Z Synchronizing submodule url for 'third_party/NNPACK'
2025-07-17T06:46:09.4409400Z Synchronizing submodule url for 'third_party/NVTX'
2025-07-17T06:46:09.4447590Z Synchronizing submodule url for 'third_party/VulkanMemoryAllocator'
2025-07-17T06:46:09.4484510Z Synchronizing submodule url for 'third_party/XNNPACK'
2025-07-17T06:46:09.4527530Z Synchronizing submodule url for 'third_party/aiter'
2025-07-17T06:46:09.4563290Z Synchronizing submodule url for 'third_party/aiter/3rdparty/composable_kernel'
2025-07-17T06:46:09.4604070Z Synchronizing submodule url for 'third_party/benchmark'
2025-07-17T06:46:09.4642190Z Synchronizing submodule url for 'third_party/composable_kernel'
2025-07-17T06:46:09.4681370Z Synchronizing submodule url for 'third_party/cpp-httplib'
2025-07-17T06:46:09.4718420Z Synchronizing submodule url for 'third_party/cpuinfo'
2025-07-17T06:46:09.4756790Z Synchronizing submodule url for 'third_party/cudnn_frontend'
2025-07-17T06:46:09.4795490Z Synchronizing submodule url for 'third_party/cutlass'
2025-07-17T06:46:09.4836410Z Synchronizing submodule url for 'third_party/fbgemm'
2025-07-17T06:46:09.4871650Z Synchronizing submodule url for 'third_party/fbgemm/external/asmjit'
2025-07-17T06:46:09.4907870Z Synchronizing submodule url for 'third_party/fbgemm/external/composable_kernel'
2025-07-17T06:46:09.4945950Z Synchronizing submodule url for 'third_party/fbgemm/external/cpuinfo'
2025-07-17T06:46:09.4988200Z Synchronizing submodule url for 'third_party/fbgemm/external/cutlass'
2025-07-17T06:46:09.5027400Z Synchronizing submodule url for 'third_party/fbgemm/external/googletest'
2025-07-17T06:46:09.5063430Z Synchronizing submodule url for 'third_party/fbgemm/external/hipify_torch'
2025-07-17T06:46:09.5099850Z Synchronizing submodule url for 'third_party/fbgemm/external/json'
2025-07-17T06:46:09.5138700Z Synchronizing submodule url for 'third_party/flash-attention'
2025-07-17T06:46:09.5174860Z Synchronizing submodule url for 'third_party/flash-attention/csrc/composable_kernel'
2025-07-17T06:46:09.5212340Z Synchronizing submodule url for 'third_party/flash-attention/csrc/cutlass'
2025-07-17T06:46:09.5253840Z Synchronizing submodule url for 'third_party/flatbuffers'
2025-07-17T06:46:09.5292770Z Synchronizing submodule url for 'third_party/fmt'
2025-07-17T06:46:09.5329380Z Synchronizing submodule url for 'third_party/gemmlowp/gemmlowp'
2025-07-17T06:46:09.5365340Z Synchronizing submodule url for 'third_party/gloo'
2025-07-17T06:46:09.5402480Z Synchronizing submodule url for 'third_party/googletest'
2025-07-17T06:46:09.5439510Z Synchronizing submodule url for 'third_party/ideep'
2025-07-17T06:46:09.5472780Z Synchronizing submodule url for 'third_party/ideep/mkl-dnn'
2025-07-17T06:46:09.5512370Z Synchronizing submodule url for 'third_party/ittapi'
2025-07-17T06:46:09.5550700Z Synchronizing submodule url for 'third_party/kineto'
2025-07-17T06:46:09.5586540Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog'
2025-07-17T06:46:09.5621070Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'
2025-07-17T06:46:09.5657890Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'
2025-07-17T06:46:09.5694240Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'
2025-07-17T06:46:09.5730550Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'
2025-07-17T06:46:09.5764980Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
2025-07-17T06:46:09.5803070Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-07-17T06:46:09.5840100Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-07-17T06:46:09.5876630Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-07-17T06:46:09.5913570Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-07-17T06:46:09.5951330Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/fmt'
2025-07-17T06:46:09.5987510Z Synchronizing submodule url for 'third_party/kineto/libkineto/third_party/googletest'
2025-07-17T06:46:09.6025310Z Synchronizing submodule url for 'third_party/kleidiai'
2025-07-17T06:46:09.6062270Z Synchronizing submodule url for 'third_party/mimalloc'
2025-07-17T06:46:09.6098790Z Synchronizing submodule url for 'third_party/nlohmann'
2025-07-17T06:46:09.6135260Z Synchronizing submodule url for 'third_party/onnx'
2025-07-17T06:46:09.6175830Z Synchronizing submodule url for 'third_party/onnx/third_party/pybind11'
2025-07-17T06:46:09.6215540Z Synchronizing submodule url for 'third_party/opentelemetry-cpp'
2025-07-17T06:46:09.6251560Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-07-17T06:46:09.6287270Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/googletest'
2025-07-17T06:46:09.6322900Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-07-17T06:46:09.6358830Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-07-17T06:46:09.6394930Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-07-17T06:46:09.6430050Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-07-17T06:46:09.6474190Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-07-17T06:46:09.6500610Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-07-17T06:46:09.6537960Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-07-17T06:46:09.6575450Z Synchronizing submodule url for 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-07-17T06:46:09.6621740Z Synchronizing submodule url for 'third_party/pocketfft'
2025-07-17T06:46:09.6659580Z Synchronizing submodule url for 'third_party/protobuf'
2025-07-17T06:46:09.6694450Z Synchronizing submodule url for 'third_party/protobuf/third_party/benchmark'
2025-07-17T06:46:09.6730620Z Synchronizing submodule url for 'third_party/protobuf/third_party/googletest'
2025-07-17T06:46:09.6770350Z Synchronizing submodule url for 'third_party/psimd'
2025-07-17T06:46:09.6808460Z Synchronizing submodule url for 'third_party/pthreadpool'
2025-07-17T06:46:09.6846610Z Synchronizing submodule url for 'third_party/pybind11'
2025-07-17T06:46:09.6884950Z Synchronizing submodule url for 'third_party/python-peachpy'
2025-07-17T06:46:09.6923050Z Synchronizing submodule url for 'third_party/sleef'
2025-07-17T06:46:09.6959910Z Synchronizing submodule url for 'third_party/tensorpipe'
2025-07-17T06:46:09.6993240Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/googletest'
2025-07-17T06:46:09.7028620Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/libnop'
2025-07-17T06:46:09.7064500Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/libuv'
2025-07-17T06:46:09.7101460Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/pybind11'
2025-07-17T06:46:09.7136990Z Synchronizing submodule url for 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-07-17T06:46:09.7181250Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive
2025-07-17T06:46:09.7982400Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f'
2025-07-17T06:46:09.8161540Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3'
2025-07-17T06:46:09.8341030Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1'
2025-07-17T06:46:09.8653800Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73'
2025-07-17T06:46:09.9218620Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07'
2025-07-17T06:46:09.9564190Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1'
2025-07-17T06:46:10.0610830Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883'
2025-07-17T06:46:10.1424790Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150'
2025-07-17T06:46:10.3142330Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf'
2025-07-17T06:46:10.3563430Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f'
2025-07-17T06:46:10.4268390Z Submodule path 'third_party/composable_kernel': checked out '434d19f696da62c12b5372b32cbc9ba968588d7e'
2025-07-17T06:46:10.4472600Z Submodule path 'third_party/cpp-httplib': checked out '3af7f2c16147f3fbc6e4d717032daf505dc1652c'
2025-07-17T06:46:10.4665520Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d'
2025-07-17T06:46:10.4901720Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6'
2025-07-17T06:46:10.5479540Z Submodule path 'third_party/cutlass': checked out 'b995f933179c22d3fe0d871c3a53d11e4681950f'
2025-07-17T06:46:10.5978970Z Submodule path 'third_party/fbgemm': checked out '157e88b750c452bef2ab4653fe9d1eeb151ce4c3'
2025-07-17T06:46:10.6336250Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'e5d7c0bd5d9aec44d68830187138149e6a8c4e32'
2025-07-17T06:46:10.6994640Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out '4a61bdd4bd4ed730e078aebc7c0fcf046ff29406'
2025-07-17T06:46:10.7497890Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349'
2025-07-17T06:46:10.8296780Z Submodule path 'third_party/fbgemm/external/cutlass': checked out '3ed8d2ec4ba35ef5d9d8353826209b6f868f63d3'
2025-07-17T06:46:10.8894060Z Submodule path 'third_party/fbgemm/external/googletest': checked out 'f8d7d77c06936315286eb55f8de22cd23c188571'
2025-07-17T06:46:10.9132140Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out 'a4337c69fe0e2552a7b7b0669178926beeed828c'
2025-07-17T06:46:11.0068480Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03'
2025-07-17T06:46:11.0389660Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5'
2025-07-17T06:46:11.1740600Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33'
2025-07-17T06:46:11.2634260Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420'
2025-07-17T06:46:11.3323520Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757'
2025-07-17T06:46:11.3510560Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21'
2025-07-17T06:46:11.3693380Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350'
2025-07-17T06:46:11.3898550Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2'
2025-07-17T06:46:11.4113830Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723'
2025-07-17T06:46:11.4305660Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3'
2025-07-17T06:46:11.7170280Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d'
2025-07-17T06:46:11.7359050Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959'
2025-07-17T06:46:11.7557020Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658'
2025-07-17T06:46:11.7979620Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e'
2025-07-17T06:46:11.8468160Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9'
2025-07-17T06:46:11.9008110Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400'
2025-07-17T06:46:11.9760510Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05'
2025-07-17T06:46:12.0078080Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067'
2025-07-17T06:46:12.0383150Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4'
2025-07-17T06:46:12.0794790Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446'
2025-07-17T06:46:12.1380680Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850'
2025-07-17T06:46:12.2332460Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5'
2025-07-17T06:46:12.2644780Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150'
2025-07-17T06:46:12.3403730Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164'
2025-07-17T06:46:12.3994270Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347'
2025-07-17T06:46:12.4258440Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7'
2025-07-17T06:46:12.4906460Z Submodule path 'third_party/mimalloc': checked out 'fbd8b99c2b828428947d70fdc046bb55609be93e'
2025-07-17T06:46:12.5787830Z Submodule path 'third_party/nlohmann': checked out '55f93686c01528224f448c19128836e7df245f72'
2025-07-17T06:46:12.7025380Z Submodule path 'third_party/onnx': checked out 'e709452ef2bbc1d113faf678c24e6d3467696e83'
2025-07-17T06:46:12.7855760Z Submodule path 'third_party/onnx/third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4'
2025-07-17T06:46:12.8615410Z Submodule path 'third_party/opentelemetry-cpp': checked out 'a799f4aed9c94b765dcdaabaeab7d5e7e2310878'
2025-07-17T06:46:12.9252410Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2'
2025-07-17T06:46:12.9826470Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1'
2025-07-17T06:46:13.0217180Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out '6f4529395c5b7c2d661812257cd6780c67e54afa'
2025-07-17T06:46:13.1083400Z Submodule path 'third_party/opentelemetry-cpp/third_party/nlohmann-json': checked out 'bc889afb4c5bf1c0d8ee29ef35eaaf4c8bef8a5d'
2025-07-17T06:46:13.1485670Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto': checked out '4ca4f0335c63cda7ab31ea7ed70d6553aee14dce'
2025-07-17T06:46:13.1719970Z Submodule path 'third_party/opentelemetry-cpp/third_party/opentracing-cpp': checked out '06b57f48ded1fa3bdd3d4346f6ef29e40e08eaf5'
2025-07-17T06:46:13.2169000Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp': checked out 'c9ffcdda9086ffd9e1283ea7a0276d831f3c8a8d'
2025-07-17T06:46:13.2826270Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb': checked out 'eefb26f82b233268fc98577d265352720d477ba4'
2025-07-17T06:46:13.3382410Z Submodule path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest': checked out 'e2239ee6043f73722e7aa812a459f54a28552929'
2025-07-17T06:46:13.6284290Z Submodule path 'third_party/opentelemetry-cpp/tools/vcpkg': checked out '8eb57355a4ffb410a2e94c07b4dca2dffbee8e50'
2025-07-17T06:46:13.6471490Z Submodule path 'third_party/pocketfft': checked out '0fa0ef591e38c2758e3184c6c23e497b9f732ffa'
2025-07-17T06:46:13.6983820Z Submodule path 'third_party/protobuf': checked out 'd1eca4e4b421cd2997495c4b4e65cea6be4e9b8a'
2025-07-17T06:46:13.7463780Z Submodule path 'third_party/protobuf/third_party/benchmark': checked out '5b7683f49e1e9223cf9927b24f6fd3d6bd82e3f8'
2025-07-17T06:46:13.8044580Z Submodule path 'third_party/protobuf/third_party/googletest': checked out '5ec7f0c4a113e2f18ac2c6cc7df51ad6afc24081'
2025-07-17T06:46:13.8217790Z Submodule path 'third_party/psimd': checked out '072586a71b55b7f8c584153d223e95687148a900'
2025-07-17T06:46:13.8388130Z Submodule path 'third_party/pthreadpool': checked out '4fe0e1e183925bf8cfa6aae24237e724a96479b8'
2025-07-17T06:46:13.8641550Z Submodule path 'third_party/pybind11': checked out 'a2e59f0e7065404b44dfe92a28aca47ba1378dc4'
2025-07-17T06:46:13.8811310Z Submodule path 'third_party/python-peachpy': checked out 'f45429b087dd7d5bc78bb40dc7cf06425c252d67'
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2025-07-17T06:46:14.1178280Z Submodule path 'third_party/tensorpipe/third_party/libuv': checked out '1dff88e5161cba5c59276d2070d2e304e4dcb242'
2025-07-17T06:46:14.1966840Z Submodule path 'third_party/tensorpipe/third_party/pybind11': checked out 'a23996fce38ff6ccfbcdc09f1e63f2c4be5ea2ef'
2025-07-17T06:46:14.2189010Z Submodule path 'third_party/tensorpipe/third_party/pybind11/tools/clang': checked out '6a00cbc4a9b8e68b71caf7f774b3f9c753ae84d5'
2025-07-17T06:46:14.2237180Z [command]/usr/bin/git submodule foreach --recursive git config --local gc.auto 0
2025-07-17T06:46:14.2745410Z Entering 'android/libs/fbjni'
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2025-07-17T06:46:14.6833310Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-07-17T06:46:14.6914920Z Entering 'third_party/kineto/libkineto/third_party/fmt'
2025-07-17T06:46:14.6997740Z Entering 'third_party/kineto/libkineto/third_party/googletest'
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2025-07-17T06:46:14.7410910Z Entering 'third_party/onnx/third_party/pybind11'
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2025-07-17T06:46:14.7584430Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-07-17T06:46:14.7663940Z Entering 'third_party/opentelemetry-cpp/third_party/googletest'
2025-07-17T06:46:14.7744110Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-07-17T06:46:14.7830660Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-07-17T06:46:14.7909980Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-07-17T06:46:14.7992120Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-07-17T06:46:14.8071970Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-07-17T06:46:14.8159520Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-07-17T06:46:14.8240310Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-07-17T06:46:14.8325810Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
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2025-07-17T06:46:14.8587080Z Entering 'third_party/protobuf/third_party/benchmark'
2025-07-17T06:46:14.8671520Z Entering 'third_party/protobuf/third_party/googletest'
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2025-07-17T06:46:14.8928730Z Entering 'third_party/pybind11'
2025-07-17T06:46:14.9010890Z Entering 'third_party/python-peachpy'
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2025-07-17T06:46:14.9256160Z Entering 'third_party/tensorpipe/third_party/googletest'
2025-07-17T06:46:14.9337530Z Entering 'third_party/tensorpipe/third_party/libnop'
2025-07-17T06:46:14.9416460Z Entering 'third_party/tensorpipe/third_party/libuv'
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2025-07-17T06:46:14.9669650Z ##[endgroup]
2025-07-17T06:46:14.9669930Z ##[group]Persisting credentials for submodules
2025-07-17T06:46:14.9673130Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'url\.https\:\/\/github\.com\/\.insteadOf' && git config --local --unset-all 'url.https://github.com/.insteadOf' || :"
2025-07-17T06:46:15.0173780Z Entering 'android/libs/fbjni'
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2025-07-17T06:46:15.4754560Z Entering 'third_party/kineto'
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2025-07-17T06:46:15.5495130Z url.https://github.com/.insteadof
2025-07-17T06:46:15.5558760Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
2025-07-17T06:46:15.5624870Z url.https://github.com/.insteadof
2025-07-17T06:46:15.5625090Z url.https://github.com/.insteadof
2025-07-17T06:46:15.5692910Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-07-17T06:46:15.5757410Z url.https://github.com/.insteadof
2025-07-17T06:46:15.5757630Z url.https://github.com/.insteadof
2025-07-17T06:46:15.5824510Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-07-17T06:46:15.5892800Z url.https://github.com/.insteadof
2025-07-17T06:46:15.5893100Z url.https://github.com/.insteadof
2025-07-17T06:46:15.5962940Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-07-17T06:46:15.6029620Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6029840Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6095860Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-07-17T06:46:15.6162940Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6230010Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6230280Z Entering 'third_party/kineto/libkineto/third_party/fmt'
2025-07-17T06:46:15.6296730Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6296960Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6362630Z Entering 'third_party/kineto/libkineto/third_party/googletest'
2025-07-17T06:46:15.6427980Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6428210Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6496970Z Entering 'third_party/kleidiai'
2025-07-17T06:46:15.6562210Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6563110Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6629030Z Entering 'third_party/mimalloc'
2025-07-17T06:46:15.6695290Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6696170Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6760990Z Entering 'third_party/nlohmann'
2025-07-17T06:46:15.6828100Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6893510Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6893750Z Entering 'third_party/onnx'
2025-07-17T06:46:15.6959100Z url.https://github.com/.insteadof
2025-07-17T06:46:15.6959330Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7029330Z Entering 'third_party/onnx/third_party/pybind11'
2025-07-17T06:46:15.7096420Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7096650Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7165700Z Entering 'third_party/opentelemetry-cpp'
2025-07-17T06:46:15.7230990Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7231210Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7297240Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-07-17T06:46:15.7363470Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7363710Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7429700Z Entering 'third_party/opentelemetry-cpp/third_party/googletest'
2025-07-17T06:46:15.7496470Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7496690Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7560840Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-07-17T06:46:15.7625880Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7626110Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7691500Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-07-17T06:46:15.7755590Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7756470Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7821150Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-07-17T06:46:15.7886050Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7886300Z url.https://github.com/.insteadof
2025-07-17T06:46:15.7950170Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-07-17T06:46:15.8016530Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8017410Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8082400Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-07-17T06:46:15.8148450Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8148660Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8215650Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-07-17T06:46:15.8285250Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8285480Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8354660Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-07-17T06:46:15.8424040Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8424260Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8494020Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-07-17T06:46:15.8558480Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8558720Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8634660Z Entering 'third_party/pocketfft'
2025-07-17T06:46:15.8703180Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8703420Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8768310Z Entering 'third_party/protobuf'
2025-07-17T06:46:15.8835710Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8835930Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8899820Z Entering 'third_party/protobuf/third_party/benchmark'
2025-07-17T06:46:15.8965380Z url.https://github.com/.insteadof
2025-07-17T06:46:15.8965600Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9030460Z Entering 'third_party/protobuf/third_party/googletest'
2025-07-17T06:46:15.9094720Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9094950Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9163660Z Entering 'third_party/psimd'
2025-07-17T06:46:15.9229440Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9229650Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9296730Z Entering 'third_party/pthreadpool'
2025-07-17T06:46:15.9362310Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9362540Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9427030Z Entering 'third_party/pybind11'
2025-07-17T06:46:15.9493680Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9493900Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9558700Z Entering 'third_party/python-peachpy'
2025-07-17T06:46:15.9625770Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9626010Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9691370Z Entering 'third_party/sleef'
2025-07-17T06:46:15.9756320Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9756540Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9823330Z Entering 'third_party/tensorpipe'
2025-07-17T06:46:15.9887800Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9888260Z url.https://github.com/.insteadof
2025-07-17T06:46:15.9952990Z Entering 'third_party/tensorpipe/third_party/googletest'
2025-07-17T06:46:16.0018310Z url.https://github.com/.insteadof
2025-07-17T06:46:16.0018530Z url.https://github.com/.insteadof
2025-07-17T06:46:16.0084430Z Entering 'third_party/tensorpipe/third_party/libnop'
2025-07-17T06:46:16.0150790Z url.https://github.com/.insteadof
2025-07-17T06:46:16.0151010Z url.https://github.com/.insteadof
2025-07-17T06:46:16.0216860Z Entering 'third_party/tensorpipe/third_party/libuv'
2025-07-17T06:46:16.0283670Z url.https://github.com/.insteadof
2025-07-17T06:46:16.0283900Z url.https://github.com/.insteadof
2025-07-17T06:46:16.0349620Z Entering 'third_party/tensorpipe/third_party/pybind11'
2025-07-17T06:46:16.0415840Z url.https://github.com/.insteadof
2025-07-17T06:46:16.0416060Z url.https://github.com/.insteadof
2025-07-17T06:46:16.0481040Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-07-17T06:46:16.0547530Z url.https://github.com/.insteadof
2025-07-17T06:46:16.0547780Z url.https://github.com/.insteadof
2025-07-17T06:46:16.0628720Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local 'http.https://github.com/.extraheader' 'AUTHORIZATION: basic ***' && git config --local --show-origin --name-only --get-regexp remote.origin.url"
2025-07-17T06:46:16.1126870Z Entering 'android/libs/fbjni'
2025-07-17T06:46:16.1234050Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config	remote.origin.url
2025-07-17T06:46:16.1268630Z Entering 'third_party/FP16'
2025-07-17T06:46:16.1365960Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config	remote.origin.url
2025-07-17T06:46:16.1400390Z Entering 'third_party/FXdiv'
2025-07-17T06:46:16.1498470Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config	remote.origin.url
2025-07-17T06:46:16.1531840Z Entering 'third_party/NNPACK'
2025-07-17T06:46:16.1628980Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK/config	remote.origin.url
2025-07-17T06:46:16.1664180Z Entering 'third_party/NVTX'
2025-07-17T06:46:16.1759570Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/NVTX/config	remote.origin.url
2025-07-17T06:46:16.1794700Z Entering 'third_party/VulkanMemoryAllocator'
2025-07-17T06:46:16.1891620Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/VulkanMemoryAllocator/config	remote.origin.url
2025-07-17T06:46:16.1925300Z Entering 'third_party/XNNPACK'
2025-07-17T06:46:16.2027370Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/XNNPACK/config	remote.origin.url
2025-07-17T06:46:16.2068370Z Entering 'third_party/aiter'
2025-07-17T06:46:16.2168800Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/aiter/config	remote.origin.url
2025-07-17T06:46:16.2202870Z Entering 'third_party/aiter/3rdparty/composable_kernel'
2025-07-17T06:46:16.2301700Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/aiter/modules/3rdparty/composable_kernel/config	remote.origin.url
2025-07-17T06:46:16.2341530Z Entering 'third_party/benchmark'
2025-07-17T06:46:16.2442110Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/benchmark/config	remote.origin.url
2025-07-17T06:46:16.2476630Z Entering 'third_party/composable_kernel'
2025-07-17T06:46:16.2587770Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/composable_kernel/config	remote.origin.url
2025-07-17T06:46:16.2625010Z Entering 'third_party/cpp-httplib'
2025-07-17T06:46:16.2724870Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/cpp-httplib/config	remote.origin.url
2025-07-17T06:46:16.2759920Z Entering 'third_party/cpuinfo'
2025-07-17T06:46:16.2859230Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/cpuinfo/config	remote.origin.url
2025-07-17T06:46:16.2894170Z Entering 'third_party/cudnn_frontend'
2025-07-17T06:46:16.3006460Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/cudnn_frontend/config	remote.origin.url
2025-07-17T06:46:16.3040480Z Entering 'third_party/cutlass'
2025-07-17T06:46:16.3137970Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/cutlass/config	remote.origin.url
2025-07-17T06:46:16.3175820Z Entering 'third_party/fbgemm'
2025-07-17T06:46:16.3276360Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/config	remote.origin.url
2025-07-17T06:46:16.3310760Z Entering 'third_party/fbgemm/external/asmjit'
2025-07-17T06:46:16.3407030Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/asmjit/config	remote.origin.url
2025-07-17T06:46:16.3442460Z Entering 'third_party/fbgemm/external/composable_kernel'
2025-07-17T06:46:16.3552130Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/composable_kernel/config	remote.origin.url
2025-07-17T06:46:16.3587790Z Entering 'third_party/fbgemm/external/cpuinfo'
2025-07-17T06:46:16.3686650Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cpuinfo/config	remote.origin.url
2025-07-17T06:46:16.3719560Z Entering 'third_party/fbgemm/external/cutlass'
2025-07-17T06:46:16.3817250Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/cutlass/config	remote.origin.url
2025-07-17T06:46:16.3854370Z Entering 'third_party/fbgemm/external/googletest'
2025-07-17T06:46:16.3952340Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/googletest/config	remote.origin.url
2025-07-17T06:46:16.3986530Z Entering 'third_party/fbgemm/external/hipify_torch'
2025-07-17T06:46:16.4082430Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/hipify_torch/config	remote.origin.url
2025-07-17T06:46:16.4116980Z Entering 'third_party/fbgemm/external/json'
2025-07-17T06:46:16.4213780Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/fbgemm/modules/external/json/config	remote.origin.url
2025-07-17T06:46:16.4250550Z Entering 'third_party/flash-attention'
2025-07-17T06:46:16.4349790Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/config	remote.origin.url
2025-07-17T06:46:16.4382190Z Entering 'third_party/flash-attention/csrc/composable_kernel'
2025-07-17T06:46:16.4479610Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/composable_kernel/config	remote.origin.url
2025-07-17T06:46:16.4515430Z Entering 'third_party/flash-attention/csrc/cutlass'
2025-07-17T06:46:16.4619740Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/flash-attention/modules/csrc/cutlass/config	remote.origin.url
2025-07-17T06:46:16.4659070Z Entering 'third_party/flatbuffers'
2025-07-17T06:46:16.4756740Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/flatbuffers/config	remote.origin.url
2025-07-17T06:46:16.4792940Z Entering 'third_party/fmt'
2025-07-17T06:46:16.4889630Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/fmt/config	remote.origin.url
2025-07-17T06:46:16.4924330Z Entering 'third_party/gemmlowp/gemmlowp'
2025-07-17T06:46:16.5022520Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/gemmlowp/gemmlowp/config	remote.origin.url
2025-07-17T06:46:16.5057540Z Entering 'third_party/gloo'
2025-07-17T06:46:16.5157880Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/gloo/config	remote.origin.url
2025-07-17T06:46:16.5193060Z Entering 'third_party/googletest'
2025-07-17T06:46:16.5291610Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/googletest/config	remote.origin.url
2025-07-17T06:46:16.5326320Z Entering 'third_party/ideep'
2025-07-17T06:46:16.5424650Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/ideep/config	remote.origin.url
2025-07-17T06:46:16.5457880Z Entering 'third_party/ideep/mkl-dnn'
2025-07-17T06:46:16.5556040Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/ideep/modules/mkl-dnn/config	remote.origin.url
2025-07-17T06:46:16.5594510Z Entering 'third_party/ittapi'
2025-07-17T06:46:16.5693750Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/ittapi/config	remote.origin.url
2025-07-17T06:46:16.5728800Z Entering 'third_party/kineto'
2025-07-17T06:46:16.5827970Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/config	remote.origin.url
2025-07-17T06:46:16.5861740Z Entering 'third_party/kineto/libkineto/third_party/dynolog'
2025-07-17T06:46:16.5961630Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/config	remote.origin.url
2025-07-17T06:46:16.5995430Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'
2025-07-17T06:46:16.6094710Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/DCGM/config	remote.origin.url
2025-07-17T06:46:16.6130060Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'
2025-07-17T06:46:16.6227130Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/cpr/config	remote.origin.url
2025-07-17T06:46:16.6261980Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'
2025-07-17T06:46:16.6364700Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/fmt/config	remote.origin.url
2025-07-17T06:46:16.6398910Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'
2025-07-17T06:46:16.6498180Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/config	remote.origin.url
2025-07-17T06:46:16.6529610Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
2025-07-17T06:46:16.6629150Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/gflags/modules/doc/config	remote.origin.url
2025-07-17T06:46:16.6665560Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-07-17T06:46:16.6761810Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/glog/config	remote.origin.url
2025-07-17T06:46:16.6796750Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-07-17T06:46:16.6893560Z file:/Users/ec2-user/runner/_work/pytorch/pytorch/.git/modules/third_party/kineto/modules/libkineto/third_party/dynolog/modules/third_party/googletest/config	remote.origin.url
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2025-07-17T06:46:18.2681580Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-07-17T06:46:18.2762360Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-07-17T06:46:18.2844730Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-07-17T06:46:18.2925060Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-07-17T06:46:18.3009490Z Entering 'third_party/kineto/libkineto/third_party/fmt'
2025-07-17T06:46:18.3089720Z Entering 'third_party/kineto/libkineto/third_party/googletest'
2025-07-17T06:46:18.3173470Z Entering 'third_party/kleidiai'
2025-07-17T06:46:18.3254690Z Entering 'third_party/mimalloc'
2025-07-17T06:46:18.3339140Z Entering 'third_party/nlohmann'
2025-07-17T06:46:18.3418350Z Entering 'third_party/onnx'
2025-07-17T06:46:18.3505420Z Entering 'third_party/onnx/third_party/pybind11'
2025-07-17T06:46:18.3589700Z Entering 'third_party/opentelemetry-cpp'
2025-07-17T06:46:18.3672920Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-07-17T06:46:18.3753050Z Entering 'third_party/opentelemetry-cpp/third_party/googletest'
2025-07-17T06:46:18.3834350Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-07-17T06:46:18.3913880Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-07-17T06:46:18.3995780Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-07-17T06:46:18.4076330Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-07-17T06:46:18.4157740Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-07-17T06:46:18.4236900Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-07-17T06:46:18.4318300Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-07-17T06:46:18.4401280Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-07-17T06:46:18.4491940Z Entering 'third_party/pocketfft'
2025-07-17T06:46:18.4573490Z Entering 'third_party/protobuf'
2025-07-17T06:46:18.4656260Z Entering 'third_party/protobuf/third_party/benchmark'
2025-07-17T06:46:18.4736060Z Entering 'third_party/protobuf/third_party/googletest'
2025-07-17T06:46:18.4819610Z Entering 'third_party/psimd'
2025-07-17T06:46:18.4900780Z Entering 'third_party/pthreadpool'
2025-07-17T06:46:18.4982430Z Entering 'third_party/pybind11'
2025-07-17T06:46:18.5063220Z Entering 'third_party/python-peachpy'
2025-07-17T06:46:18.5144090Z Entering 'third_party/sleef'
2025-07-17T06:46:18.5226470Z Entering 'third_party/tensorpipe'
2025-07-17T06:46:18.5307660Z Entering 'third_party/tensorpipe/third_party/googletest'
2025-07-17T06:46:18.5390310Z Entering 'third_party/tensorpipe/third_party/libnop'
2025-07-17T06:46:18.5474500Z Entering 'third_party/tensorpipe/third_party/libuv'
2025-07-17T06:46:18.5566830Z Entering 'third_party/tensorpipe/third_party/pybind11'
2025-07-17T06:46:18.5647420Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-07-17T06:46:18.5741290Z ##[endgroup]
2025-07-17T06:46:18.5857490Z [command]/usr/bin/git log -1 --format=%H
2025-07-17T06:46:18.5924060Z a38f433be2e94a64b095a44ba39879d02d0c2316
2025-07-17T06:46:18.6013270Z Prepare all required actions
2025-07-17T06:46:18.6032670Z ##[group]Run ./.github/actions/get-workflow-job-id
2025-07-17T06:46:18.6032860Z with:
2025-07-17T06:46:18.6033170Z   github-token: ***
2025-07-17T06:46:18.6033290Z env:
2025-07-17T06:46:18.6033400Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:18.6033650Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:18.6033820Z   TEST_CONFIG: default
2025-07-17T06:46:18.6033940Z   SHARD_NUMBER: 1
2025-07-17T06:46:18.6034050Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:18.6034170Z   PR_BODY: 
2025-07-17T06:46:18.6034280Z ##[endgroup]
2025-07-17T06:46:18.6043550Z ##[group]Run set -eux
2025-07-17T06:46:18.6043700Z set -eux
2025-07-17T06:46:18.6043940Z python3 .github/scripts/get_workflow_job_id.py "${GITHUB_RUN_ID}" "${RUNNER_NAME}"
2025-07-17T06:46:18.6422860Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T06:46:18.6423050Z env:
2025-07-17T06:46:18.6423170Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:18.6423370Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:18.6423540Z   TEST_CONFIG: default
2025-07-17T06:46:18.6423660Z   SHARD_NUMBER: 1
2025-07-17T06:46:18.6423770Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:18.6423890Z   PR_BODY: 
2025-07-17T06:46:18.6424090Z   GITHUB_TOKEN: ***
2025-07-17T06:46:18.6424210Z ##[endgroup]
2025-07-17T06:46:18.6655430Z + python3 .github/scripts/get_workflow_job_id.py 16337959945 i-06ffcdff1c2e10d08
2025-07-17T06:46:19.5283190Z Setting output job-id=46154244367
2025-07-17T06:46:19.5283710Z Setting output job-name=macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)
2025-07-17T06:46:19.5382820Z ##[group]Run pytorch/test-infra/.github/actions/setup-python@main
2025-07-17T06:46:19.5383150Z with:
2025-07-17T06:46:19.5383320Z   python-version: 3.12.7
2025-07-17T06:46:19.5383660Z   pip-requirements-file: .github/requirements/pip-requirements-macOS.txt
2025-07-17T06:46:19.5383990Z env:
2025-07-17T06:46:19.5384150Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:19.5384370Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:19.5384610Z   TEST_CONFIG: default
2025-07-17T06:46:19.5384790Z   SHARD_NUMBER: 1
2025-07-17T06:46:19.5384960Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:19.5398990Z   PR_BODY: 
2025-07-17T06:46:19.5399180Z ##[endgroup]
2025-07-17T06:46:19.5865220Z Warning: HomeBrew only supports version specified by major and minor, but got 3.12.7
2025-07-17T06:46:20.3509210Z ==> Updating Homebrew...
2025-07-17T06:46:21.2742940Z Already up-to-date.
2025-07-17T06:46:22.2942990Z ##[warning]python@3.12 3.12.11 is already installed and up-to-date.
To reinstall 3.12.11, run:
  brew reinstall python@3.12

2025-07-17T06:46:22.3261350Z Using python at /opt/homebrew/bin/python3.12 to create venv /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:24.4536520Z Installing requirements from .github/requirements/pip-requirements-macOS.txt
2025-07-17T06:46:24.7906100Z Collecting boto3==1.35.42 (from -r .github/requirements/pip-requirements-macOS.txt (line 1))
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2025-07-17T06:46:24.8547270Z Collecting cmake==3.27.* (from -r .github/requirements/pip-requirements-macOS.txt (line 2))
2025-07-17T06:46:24.8594440Z   Using cached cmake-3.27.9-py2.py3-none-macosx_10_10_universal2.macosx_10_10_x86_64.macosx_11_0_arm64.macosx_11_0_universal2.whl.metadata (6.3 kB)
2025-07-17T06:46:24.8783810Z Collecting expecttest==0.3.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 3))
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2025-07-17T06:46:24.9227680Z Collecting filelock==3.6.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 5))
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2025-07-17T06:46:25.0297250Z Collecting hypothesis==6.56.4 (from -r .github/requirements/pip-requirements-macOS.txt (line 6))
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2025-07-17T06:46:25.0728090Z Collecting mpmath==1.3.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 8))
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2025-07-17T06:46:25.0988560Z Collecting networkx==2.8.7 (from -r .github/requirements/pip-requirements-macOS.txt (line 9))
2025-07-17T06:46:25.1032180Z   Using cached networkx-2.8.7-py3-none-any.whl.metadata (5.1 kB)
2025-07-17T06:46:25.1250670Z Collecting ninja==1.10.2.4 (from -r .github/requirements/pip-requirements-macOS.txt (line 10))
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2025-07-17T06:46:25.1910450Z Collecting numba==0.59.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 11))
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2025-07-17T06:46:25.2777330Z Collecting numpy==1.26.4 (from -r .github/requirements/pip-requirements-macOS.txt (line 12))
2025-07-17T06:46:25.2825100Z   Using cached numpy-1.26.4-cp312-cp312-macosx_11_0_arm64.whl.metadata (61 kB)
2025-07-17T06:46:25.3032790Z Collecting opt-einsum>=3.3 (from -r .github/requirements/pip-requirements-macOS.txt (line 13))
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2025-07-17T06:46:25.3497040Z Collecting optree==0.13.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 14))
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2025-07-17T06:46:25.3730310Z Collecting packaging==23.1 (from -r .github/requirements/pip-requirements-macOS.txt (line 15))
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2025-07-17T06:46:25.3895550Z Collecting parameterized==0.8.1 (from -r .github/requirements/pip-requirements-macOS.txt (line 16))
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2025-07-17T06:46:25.4760000Z Collecting pillow==10.3.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 17))
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2025-07-17T06:46:25.5536340Z Collecting protobuf==5.29.4 (from -r .github/requirements/pip-requirements-macOS.txt (line 18))
2025-07-17T06:46:25.5575030Z   Using cached protobuf-5.29.4-cp38-abi3-macosx_10_9_universal2.whl.metadata (592 bytes)
2025-07-17T06:46:25.6187670Z Collecting psutil==5.9.1 (from -r .github/requirements/pip-requirements-macOS.txt (line 19))
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2025-07-17T06:46:25.6339800Z Collecting pygments==2.15.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 20))
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2025-07-17T06:46:25.6524420Z Collecting pytest-cpp==2.3.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 21))
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2025-07-17T06:46:25.6676530Z Collecting pytest-flakefinder==1.1.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 22))
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2025-07-17T06:46:25.6844610Z Collecting pytest-rerunfailures==10.3 (from -r .github/requirements/pip-requirements-macOS.txt (line 23))
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2025-07-17T06:46:25.7035830Z Collecting pytest-subtests==0.13.1 (from -r .github/requirements/pip-requirements-macOS.txt (line 24))
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2025-07-17T06:46:25.7226690Z Collecting pytest-xdist==3.3.1 (from -r .github/requirements/pip-requirements-macOS.txt (line 25))
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2025-07-17T06:46:25.7460110Z Collecting pytest==7.3.2 (from -r .github/requirements/pip-requirements-macOS.txt (line 26))
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2025-07-17T06:46:25.7748560Z Collecting pyyaml==6.0.2 (from -r .github/requirements/pip-requirements-macOS.txt (line 27))
2025-07-17T06:46:25.7770100Z   Using cached PyYAML-6.0.2-cp312-cp312-macosx_11_0_arm64.whl.metadata (2.1 kB)
2025-07-17T06:46:25.8352780Z Collecting scipy==1.12.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 28))
2025-07-17T06:46:25.8406590Z   Using cached scipy-1.12.0-cp312-cp312-macosx_12_0_arm64.whl.metadata (217 kB)
2025-07-17T06:46:25.9278670Z Collecting setuptools==72.1.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 29))
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2025-07-17T06:46:25.9494530Z Collecting sympy==1.13.3 (from -r .github/requirements/pip-requirements-macOS.txt (line 30))
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2025-07-17T06:46:25.9778850Z Collecting tlparse==0.3.30 (from -r .github/requirements/pip-requirements-macOS.txt (line 31))
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2025-07-17T06:46:25.9980720Z Collecting tensorboard==2.13.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 32))
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2025-07-17T06:46:26.0155180Z Collecting typing-extensions==4.12.2 (from -r .github/requirements/pip-requirements-macOS.txt (line 33))
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2025-07-17T06:46:26.0340580Z Collecting unittest-xml-reporting<=3.2.0,>=2.0.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 34))
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2025-07-17T06:46:26.0560320Z Collecting xdoctest==1.1.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 35))
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2025-07-17T06:46:26.1082620Z Collecting z3-solver==4.12.2.0 (from -r .github/requirements/pip-requirements-macOS.txt (line 36))
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2025-07-17T06:46:26.3199940Z Collecting botocore<1.36.0,>=1.35.42 (from boto3==1.35.42->-r .github/requirements/pip-requirements-macOS.txt (line 1))
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2025-07-17T06:46:26.7541380Z Collecting colorama (from pytest-cpp==2.3.0->-r .github/requirements/pip-requirements-macOS.txt (line 21))
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2025-07-17T06:46:29.7557620Z Using cached tensorboard_data_server-0.7.2-py3-none-any.whl (2.4 kB)
2025-07-17T06:46:29.7579540Z Using cached thriftpy2-0.5.3-cp312-cp312-macosx_11_0_arm64.whl (833 kB)
2025-07-17T06:46:29.7638400Z Using cached ply-3.11-py2.py3-none-any.whl (49 kB)
2025-07-17T06:46:29.7655980Z Using cached six-1.17.0-py2.py3-none-any.whl (11 kB)
2025-07-17T06:46:29.7680370Z Using cached urllib3-2.5.0-py3-none-any.whl (129 kB)
2025-07-17T06:46:29.7691280Z Using cached yarl-1.20.1-cp312-cp312-macosx_11_0_arm64.whl (89 kB)
2025-07-17T06:46:29.7713090Z Using cached librosa-0.11.0-py3-none-any.whl (260 kB)
2025-07-17T06:46:29.7742100Z Using cached opt_einsum-3.4.0-py3-none-any.whl (71 kB)
2025-07-17T06:46:29.7763040Z Using cached absl_py-2.3.1-py3-none-any.whl (135 kB)
2025-07-17T06:46:29.7793190Z Using cached aiohappyeyeballs-2.6.1-py3-none-any.whl (15 kB)
2025-07-17T06:46:29.7803370Z Using cached aiosignal-1.4.0-py3-none-any.whl (7.5 kB)
2025-07-17T06:46:29.7821820Z Using cached attrs-25.3.0-py3-none-any.whl (63 kB)
2025-07-17T06:46:29.7838400Z Using cached audioread-3.0.1-py3-none-any.whl (23 kB)
2025-07-17T06:46:29.7850040Z Using cached certifi-2025.7.14-py3-none-any.whl (162 kB)
2025-07-17T06:46:29.7866300Z Using cached decorator-5.2.1-py3-none-any.whl (9.2 kB)
2025-07-17T06:46:29.7880430Z Using cached execnet-2.1.1-py3-none-any.whl (40 kB)
2025-07-17T06:46:29.7895120Z Using cached frozenlist-1.7.0-cp312-cp312-macosx_11_0_arm64.whl (46 kB)
2025-07-17T06:46:29.7916010Z Using cached grpcio-1.73.1-cp312-cp312-macosx_11_0_universal2.whl (10.6 MB)
2025-07-17T06:46:29.8612170Z Using cached joblib-1.5.1-py3-none-any.whl (307 kB)
2025-07-17T06:46:29.8649320Z Using cached lazy_loader-0.4-py3-none-any.whl (12 kB)
2025-07-17T06:46:29.8668150Z Using cached markdown-3.8.2-py3-none-any.whl (106 kB)
2025-07-17T06:46:29.8691020Z Using cached msgpack-1.1.1-cp312-cp312-macosx_11_0_arm64.whl (79 kB)
2025-07-17T06:46:29.8722250Z Using cached pooch-1.8.2-py3-none-any.whl (64 kB)
2025-07-17T06:46:29.8750460Z Using cached platformdirs-4.3.8-py3-none-any.whl (18 kB)
2025-07-17T06:46:29.8765720Z Using cached propcache-0.3.2-cp312-cp312-macosx_11_0_arm64.whl (43 kB)
2025-07-17T06:46:29.8782580Z Using cached pyasn1-0.6.1-py3-none-any.whl (83 kB)
2025-07-17T06:46:29.8810280Z Using cached pyasn1_modules-0.4.2-py3-none-any.whl (181 kB)
2025-07-17T06:46:29.8833170Z Using cached requests_oauthlib-2.0.0-py2.py3-none-any.whl (24 kB)
2025-07-17T06:46:29.8847970Z Using cached oauthlib-3.3.1-py3-none-any.whl (160 kB)
2025-07-17T06:46:29.8869090Z Using cached scikit_learn-1.7.0-cp312-cp312-macosx_12_0_arm64.whl (10.7 MB)
2025-07-17T06:46:29.9895000Z Using cached soundfile-0.13.1-py2.py3-none-macosx_11_0_arm64.whl (1.1 MB)
2025-07-17T06:46:30.0027650Z Using cached cffi-1.17.1-cp312-cp312-macosx_11_0_arm64.whl (178 kB)
2025-07-17T06:46:30.0053290Z Using cached soxr-0.5.0.post1-cp312-abi3-macosx_11_0_arm64.whl (156 kB)
2025-07-17T06:46:30.0081130Z Using cached threadpoolctl-3.6.0-py3-none-any.whl (18 kB)
2025-07-17T06:46:30.0100360Z Using cached werkzeug-3.1.3-py3-none-any.whl (224 kB)
2025-07-17T06:46:30.0136540Z Using cached MarkupSafe-3.0.2-cp312-cp312-macosx_11_0_arm64.whl (12 kB)
2025-07-17T06:46:30.0151540Z Using cached wheel-0.45.1-py3-none-any.whl (72 kB)
2025-07-17T06:46:30.0172570Z Using cached colorama-0.4.6-py2.py3-none-any.whl (25 kB)
2025-07-17T06:46:30.0187100Z Using cached iniconfig-2.1.0-py3-none-any.whl (6.0 kB)
2025-07-17T06:46:30.0201160Z Using cached lxml-6.0.0-cp312-cp312-macosx_10_13_universal2.whl (8.4 MB)
2025-07-17T06:46:30.1032530Z Using cached pycparser-2.22-py3-none-any.whl (117 kB)
2025-07-17T06:46:30.3920050Z Installing collected packages: z3-solver, sortedcontainers, ply, parameterized, ninja, mpmath, cmake, wheel, urllib3, typing-extensions, tlparse, threadpoolctl, tensorboard-data-server, sympy, six, setuptools, pyyaml, pygments, pycparser, pyasn1, psutil, protobuf, propcache, pluggy, platformdirs, pillow, packaging, opt-einsum, oauthlib, numpy, networkx, multidict, msgpack, MarkupSafe, markdown, lxml, llvmlite, joblib, jmespath, iniconfig, idna, grpcio, frozenlist, filelock, expecttest, execnet, decorator, colorama, charset_normalizer, certifi, cachetools, audioread, attrs, aiohappyeyeballs, absl-py, yarl, xdoctest, werkzeug, unittest-xml-reporting, thriftpy2, soxr, scipy, rsa, requests, python-dateutil, pytest, pyasn1-modules, optree, numba, lazy_loader, hypothesis, cffi, aiosignal, soundfile, scikit-learn, requests-oauthlib, pytest-xdist, pytest-subtests, pytest-rerunfailures, pytest-flakefinder, pytest-cpp, pooch, google-auth, botocore, aiohttp, s3transfer, librosa, google-auth-oauthlib, fbscribelogger, tensorboard, boto3
2025-07-17T06:46:46.5318080Z 
2025-07-17T06:46:46.5357900Z Successfully installed MarkupSafe-3.0.2 absl-py-2.3.1 aiohappyeyeballs-2.6.1 aiohttp-3.12.14 aiosignal-1.4.0 attrs-25.3.0 audioread-3.0.1 boto3-1.35.42 botocore-1.35.99 cachetools-5.5.2 certifi-2025.7.14 cffi-1.17.1 charset_normalizer-3.4.2 cmake-3.27.9 colorama-0.4.6 decorator-5.2.1 execnet-2.1.1 expecttest-0.3.0 fbscribelogger-0.1.7 filelock-3.6.0 frozenlist-1.7.0 google-auth-2.40.3 google-auth-oauthlib-1.0.0 grpcio-1.73.1 hypothesis-6.56.4 idna-3.10 iniconfig-2.1.0 jmespath-1.0.1 joblib-1.5.1 lazy_loader-0.4 librosa-0.11.0 llvmlite-0.42.0 lxml-6.0.0 markdown-3.8.2 mpmath-1.3.0 msgpack-1.1.1 multidict-6.6.3 networkx-2.8.7 ninja-1.10.2.4 numba-0.59.0 numpy-1.26.4 oauthlib-3.3.1 opt-einsum-3.4.0 optree-0.13.0 packaging-23.1 parameterized-0.8.1 pillow-10.3.0 platformdirs-4.3.8 pluggy-1.6.0 ply-3.11 pooch-1.8.2 propcache-0.3.2 protobuf-5.29.4 psutil-5.9.1 pyasn1-0.6.1 pyasn1-modules-0.4.2 pycparser-2.22 pygments-2.15.0 pytest-7.3.2 pytest-cpp-2.3.0 pytest-flakefinder-1.1.0 pytest-rerunfailures-10.3 pytest-subtests-0.13.1 pytest-xdist-3.3.1 python-dateutil-2.9.0.post0 pyyaml-6.0.2 requests-2.32.4 requests-oauthlib-2.0.0 rsa-4.9.1 s3transfer-0.10.4 scikit-learn-1.7.0 scipy-1.12.0 setuptools-72.1.0 six-1.17.0 sortedcontainers-2.4.0 soundfile-0.13.1 soxr-0.5.0.post1 sympy-1.13.3 tensorboard-2.13.0 tensorboard-data-server-0.7.2 threadpoolctl-3.6.0 thriftpy2-0.5.3 tlparse-0.3.30 typing-extensions-4.12.2 unittest-xml-reporting-3.2.0 urllib3-2.5.0 werkzeug-3.1.3 wheel-0.45.1 xdoctest-1.1.0 yarl-1.20.1 z3-solver-4.12.2.0
2025-07-17T06:46:47.2768190Z ##[group]Run "$VENV_PATH/bin/python3" -m pip install psutil==5.9.1 dataclasses_json==0.6.7
2025-07-17T06:46:47.2768590Z "$VENV_PATH/bin/python3" -m pip install psutil==5.9.1 dataclasses_json==0.6.7
2025-07-17T06:46:47.2769160Z "$VENV_PATH/bin/python3" -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 &
2025-07-17T06:46:47.2769670Z echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}"
2025-07-17T06:46:47.2800070Z shell: /bin/bash -e -l {0}
2025-07-17T06:46:47.2800210Z env:
2025-07-17T06:46:47.2800320Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:47.2800470Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:47.2800640Z   TEST_CONFIG: default
2025-07-17T06:46:47.2800760Z   SHARD_NUMBER: 1
2025-07-17T06:46:47.2801000Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:47.2801120Z   PR_BODY: 
2025-07-17T06:46:47.2801310Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:47.2801530Z   JOB_ID: 46154244367
2025-07-17T06:46:47.2801730Z   JOB_NAME: macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)
2025-07-17T06:46:47.2801950Z   WORKFLOW_NAME: trunk
2025-07-17T06:46:47.2802080Z   WORKFLOW_RUN_ID: 16337959945
2025-07-17T06:46:47.2802230Z   MONITOR_LOG_INTERVAL: 5
2025-07-17T06:46:47.2802380Z   MONITOR_DATA_COLLECT_INTERVAL: 1
2025-07-17T06:46:47.2802530Z ##[endgroup]
2025-07-17T06:46:47.4834340Z Requirement already satisfied: psutil==5.9.1 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (5.9.1)
2025-07-17T06:46:47.5126780Z Collecting dataclasses_json==0.6.7
2025-07-17T06:46:47.5152320Z   Using cached dataclasses_json-0.6.7-py3-none-any.whl.metadata (25 kB)
2025-07-17T06:46:47.5439270Z Collecting marshmallow<4.0.0,>=3.18.0 (from dataclasses_json==0.6.7)
2025-07-17T06:46:47.5459480Z   Using cached marshmallow-3.26.1-py3-none-any.whl.metadata (7.3 kB)
2025-07-17T06:46:47.5594690Z Collecting typing-inspect<1,>=0.4.0 (from dataclasses_json==0.6.7)
2025-07-17T06:46:47.5635570Z   Using cached typing_inspect-0.9.0-py3-none-any.whl.metadata (1.5 kB)
2025-07-17T06:46:47.5672900Z Requirement already satisfied: packaging>=17.0 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses_json==0.6.7) (23.1)
2025-07-17T06:46:47.5736640Z Collecting mypy-extensions>=0.3.0 (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7)
2025-07-17T06:46:47.5750320Z   Using cached mypy_extensions-1.1.0-py3-none-any.whl.metadata (1.1 kB)
2025-07-17T06:46:47.5805840Z Requirement already satisfied: typing-extensions>=3.7.4 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (4.12.2)
2025-07-17T06:46:47.5826000Z Using cached dataclasses_json-0.6.7-py3-none-any.whl (28 kB)
2025-07-17T06:46:47.5850920Z Using cached marshmallow-3.26.1-py3-none-any.whl (50 kB)
2025-07-17T06:46:47.5870910Z Using cached typing_inspect-0.9.0-py3-none-any.whl (8.8 kB)
2025-07-17T06:46:47.5896530Z Using cached mypy_extensions-1.1.0-py3-none-any.whl (5.0 kB)
2025-07-17T06:46:47.6656360Z Installing collected packages: mypy-extensions, marshmallow, typing-inspect, dataclasses_json
2025-07-17T06:46:47.7111700Z 
2025-07-17T06:46:47.7148780Z Successfully installed dataclasses_json-0.6.7 marshmallow-3.26.1 mypy-extensions-1.1.0 typing-inspect-0.9.0
2025-07-17T06:46:47.7505030Z Prepare all required actions
2025-07-17T06:46:47.7505280Z Getting action download info
2025-07-17T06:46:47.8856170Z Download action repository 'seemethere/download-artifact-s3@v4' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6)
2025-07-17T06:46:48.1795760Z Download action repository 'actions/download-artifact@v4' (SHA:d3f86a106a0bac45b974a628896c90dbdf5c8093)
2025-07-17T06:46:48.4048460Z ##[group]Run ./.github/actions/download-build-artifacts
2025-07-17T06:46:48.4048700Z with:
2025-07-17T06:46:48.4048830Z   name: macos-py3-arm64
2025-07-17T06:46:48.4049000Z   use-gha: true
2025-07-17T06:46:48.4049150Z   s3-bucket: gha-artifacts
2025-07-17T06:46:48.4049320Z env:
2025-07-17T06:46:48.4049450Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:48.4049620Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:48.4049820Z   TEST_CONFIG: default
2025-07-17T06:46:48.4049960Z   SHARD_NUMBER: 1
2025-07-17T06:46:48.4050110Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:48.4050250Z   PR_BODY: 
2025-07-17T06:46:48.4050470Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:48.4050710Z ##[endgroup]
2025-07-17T06:46:48.4074210Z ##[group]Run actions/download-artifact@v4
2025-07-17T06:46:48.4074390Z with:
2025-07-17T06:46:48.4074530Z   name: macos-py3-arm64
2025-07-17T06:46:48.4074670Z   merge-multiple: false
2025-07-17T06:46:48.4074830Z   repository: pytorch/pytorch
2025-07-17T06:46:48.4075200Z   run-id: 16337959945
2025-07-17T06:46:48.4075330Z env:
2025-07-17T06:46:48.4075460Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:48.4075630Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:48.4075800Z   TEST_CONFIG: default
2025-07-17T06:46:48.4075950Z   SHARD_NUMBER: 1
2025-07-17T06:46:48.4076070Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:48.4076200Z   PR_BODY: 
2025-07-17T06:46:48.4076400Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:48.4076630Z ##[endgroup]
2025-07-17T06:46:48.5464820Z Downloading single artifact
2025-07-17T06:46:48.6187280Z Preparing to download the following artifacts:
2025-07-17T06:46:48.6205980Z - macos-py3-arm64 (ID: 3551917746, Size: 70653767, Expected Digest: sha256:6d45381d423937eca6bd3f9b244b81431c18532b7b40fb78315abce56be71843)
2025-07-17T06:46:48.6733340Z Redirecting to blob download url: https://productionresultssa18.blob.core.windows.net/actions-results/f6c081a3-8a6f-44b6-a437-366cdb9b3828/workflow-job-run-83f3e020-83ba-56ac-b2cf-3faec8b15234/artifacts/e6751562b1f6f20bcd6ad8a8dad1f3c02045e3fad46dd739dee73dcfde9461bb.zip
2025-07-17T06:46:48.6734770Z Starting download of artifact to: /Users/ec2-user/runner/_work/pytorch/pytorch
2025-07-17T06:46:48.7892450Z (node:32810) [DEP0005] DeprecationWarning: Buffer() is deprecated due to security and usability issues. Please use the Buffer.alloc(), Buffer.allocUnsafe(), or Buffer.from() methods instead.
2025-07-17T06:46:48.7894810Z (Use `node --trace-deprecation ...` to show where the warning was created)
2025-07-17T06:46:49.5170830Z SHA256 digest of downloaded artifact is 6d45381d423937eca6bd3f9b244b81431c18532b7b40fb78315abce56be71843
2025-07-17T06:46:49.5171240Z Artifact download completed successfully.
2025-07-17T06:46:49.5171550Z Total of 1 artifact(s) downloaded
2025-07-17T06:46:49.5175030Z Download artifact has finished successfully
2025-07-17T06:46:49.5220390Z ##[group]Run unzip -o artifacts.zip
2025-07-17T06:46:49.5220610Z unzip -o artifacts.zip
2025-07-17T06:46:49.5232700Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T06:46:49.5232920Z env:
2025-07-17T06:46:49.5233070Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:49.5233250Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:49.5233430Z   TEST_CONFIG: default
2025-07-17T06:46:49.5233580Z   SHARD_NUMBER: 1
2025-07-17T06:46:49.5233710Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:49.5233850Z   PR_BODY: 
2025-07-17T06:46:49.5234040Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:49.5234280Z ##[endgroup]
2025-07-17T06:46:49.5550250Z Archive:  artifacts.zip
2025-07-17T06:46:49.5551000Z    creating: dist/
2025-07-17T06:46:50.0173420Z   inflating: dist/torch-2.9.0a0+gita38f433-cp312-cp312-macosx_11_0_arm64.whl  
2025-07-17T06:46:50.0329420Z   inflating: build/.ninja_log        
2025-07-17T06:46:50.0890370Z   inflating: build/compile_commands.json  
2025-07-17T06:46:50.0890780Z    creating: .additional_ci_files/
2025-07-17T06:46:50.1028200Z   inflating: .additional_ci_files/test-times.json  
2025-07-17T06:46:50.1694680Z   inflating: .additional_ci_files/test-class-times.json  
2025-07-17T06:46:50.1714730Z ##[group]Run rm artifacts.zip
2025-07-17T06:46:50.1715000Z rm artifacts.zip
2025-07-17T06:46:50.1727550Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T06:46:50.1727790Z env:
2025-07-17T06:46:50.1727920Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:50.1728110Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:50.1728300Z   TEST_CONFIG: default
2025-07-17T06:46:50.1728450Z   SHARD_NUMBER: 1
2025-07-17T06:46:50.1728590Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:50.1728760Z   PR_BODY: 
2025-07-17T06:46:50.1728960Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:50.1729220Z ##[endgroup]
2025-07-17T06:46:50.2009040Z ##[group]Run df -H
2025-07-17T06:46:50.2009230Z df -H
2025-07-17T06:46:50.2021250Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T06:46:50.2021460Z env:
2025-07-17T06:46:50.2021770Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:50.2021950Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:50.2022160Z   TEST_CONFIG: default
2025-07-17T06:46:50.2022300Z   SHARD_NUMBER: 1
2025-07-17T06:46:50.2022430Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:50.2022580Z   PR_BODY: 
2025-07-17T06:46:50.2022780Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:50.2023020Z ##[endgroup]
2025-07-17T06:46:50.2285600Z Filesystem        Size    Used   Avail Capacity iused ifree %iused  Mounted on
2025-07-17T06:46:50.2286070Z /dev/disk5s2s1    275G     10G    109G     9%    404k  1.1G    0%   /
2025-07-17T06:46:50.2286810Z devfs             222k    222k      0B   100%     752     0  100%   /dev
2025-07-17T06:46:50.2287170Z /dev/disk5s5      275G   2148M    109G     2%       2  1.1G    0%   /System/Volumes/VM
2025-07-17T06:46:50.2287660Z /dev/disk5s3      275G   6122M    109G     6%    1.0k  1.1G    0%   /System/Volumes/Preboot
2025-07-17T06:46:50.2288070Z /dev/disk1s2      524M   6312k    406M     2%       1  4.0M    0%   /System/Volumes/xarts
2025-07-17T06:46:50.2288450Z /dev/disk1s1      524M     56M    406M    13%      61  4.0M    0%   /System/Volumes/iSCPreboot
2025-07-17T06:46:50.2288820Z /dev/disk1s3      524M    963k    406M     1%      51  4.0M    0%   /System/Volumes/Hardware
2025-07-17T06:46:50.2289180Z /dev/disk5s1      275G    146G    109G    58%    7.2M  1.1G    1%   /System/Volumes/Data
2025-07-17T06:46:50.2289530Z map auto_home       0B      0B      0B   100%       0     0     -   /System/Volumes/Data/home
2025-07-17T06:46:50.2289910Z /dev/disk3s4      245G    123k    226G     1%      18  2.2G    0%   /private/tmp/tmp-mount-g9r1EB
2025-07-17T06:46:50.2319380Z Prepare all required actions
2025-07-17T06:46:50.2319800Z Getting action download info
2025-07-17T06:46:50.3761210Z ##[group]Run ./.github/actions/download-td-artifacts
2025-07-17T06:46:50.3761630Z with:
2025-07-17T06:46:50.3761860Z   use-gha: true
2025-07-17T06:46:50.3762100Z env:
2025-07-17T06:46:50.3762380Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:50.3762740Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:50.3763100Z   TEST_CONFIG: default
2025-07-17T06:46:50.3763370Z   SHARD_NUMBER: 1
2025-07-17T06:46:50.3763650Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:50.3763940Z   PR_BODY: 
2025-07-17T06:46:50.3764340Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:50.3764860Z ##[endgroup]
2025-07-17T06:46:50.3809440Z ##[group]Run actions/download-artifact@v4
2025-07-17T06:46:50.3809840Z with:
2025-07-17T06:46:50.3810110Z   name: td_results.json
2025-07-17T06:46:50.3810420Z   merge-multiple: false
2025-07-17T06:46:50.3810820Z   repository: pytorch/pytorch
2025-07-17T06:46:50.3811160Z   run-id: 16337959945
2025-07-17T06:46:50.3811470Z env:
2025-07-17T06:46:50.3811750Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:50.3812100Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:50.3812510Z   TEST_CONFIG: default
2025-07-17T06:46:50.3812800Z   SHARD_NUMBER: 1
2025-07-17T06:46:50.3813070Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:50.3813360Z   PR_BODY: 
2025-07-17T06:46:50.3813740Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:50.3814250Z ##[endgroup]
2025-07-17T06:46:50.5196020Z Downloading single artifact
2025-07-17T06:46:50.5932340Z Preparing to download the following artifacts:
2025-07-17T06:46:50.5933600Z - td_results.json (ID: 3551944785, Size: 18391, Expected Digest: sha256:22dd351c0595b23d55c85e1bca969a037c03e6c3bd9cd1e736869175c5e00781)
2025-07-17T06:46:50.6924460Z Redirecting to blob download url: https://productionresultssa18.blob.core.windows.net/actions-results/f6c081a3-8a6f-44b6-a437-366cdb9b3828/workflow-job-run-285f2f3b-d0ff-5ec3-a61d-e3fe67ef96d6/artifacts/adc6e1455d65305bef307fe59db64c62b28fcb8f1e044d47ac9f5a2f27485441.zip
2025-07-17T06:46:50.6926690Z Starting download of artifact to: /Users/ec2-user/runner/_work/pytorch/pytorch
2025-07-17T06:46:50.7442620Z (node:32817) [DEP0005] DeprecationWarning: Buffer() is deprecated due to security and usability issues. Please use the Buffer.alloc(), Buffer.allocUnsafe(), or Buffer.from() methods instead.
2025-07-17T06:46:50.7445100Z (Use `node --trace-deprecation ...` to show where the warning was created)
2025-07-17T06:46:50.7507490Z SHA256 digest of downloaded artifact is 22dd351c0595b23d55c85e1bca969a037c03e6c3bd9cd1e736869175c5e00781
2025-07-17T06:46:50.7508280Z Artifact download completed successfully.
2025-07-17T06:46:50.7508760Z Total of 1 artifact(s) downloaded
2025-07-17T06:46:50.7514680Z Download artifact has finished successfully
2025-07-17T06:46:50.7603160Z ##[group]Run mkdir -p .additional_ci_files
2025-07-17T06:46:50.7603650Z mkdir -p .additional_ci_files
2025-07-17T06:46:50.7604200Z mv td_results.json .additional_ci_files/td_results.json || true
2025-07-17T06:46:50.7626150Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T06:46:50.7626590Z env:
2025-07-17T06:46:50.7626840Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:50.7627210Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:50.7627550Z   TEST_CONFIG: default
2025-07-17T06:46:50.7627830Z   SHARD_NUMBER: 1
2025-07-17T06:46:50.7628110Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:50.7628370Z   PR_BODY: 
2025-07-17T06:46:50.7628800Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:50.7629310Z ##[endgroup]
2025-07-17T06:46:50.7995740Z ##[group]Run .github/scripts/parse_ref.py
2025-07-17T06:46:50.7996050Z .github/scripts/parse_ref.py
2025-07-17T06:46:50.8009070Z shell: /bin/bash -e -l {0}
2025-07-17T06:46:50.8009330Z env:
2025-07-17T06:46:50.8009510Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:50.8009710Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:50.8009940Z   TEST_CONFIG: default
2025-07-17T06:46:50.8010100Z   SHARD_NUMBER: 1
2025-07-17T06:46:50.8010270Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:50.8010440Z   PR_BODY: 
2025-07-17T06:46:50.8010670Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:50.8010960Z ##[endgroup]
2025-07-17T06:46:50.8964760Z Setting output branch=main
2025-07-17T06:46:50.9053720Z Prepare all required actions
2025-07-17T06:46:50.9053970Z Getting action download info
2025-07-17T06:46:51.0311350Z Download action repository 'nick-fields/retry@v3.0.0' (SHA:7152eba30c6575329ac0576536151aca5a72780e)
2025-07-17T06:46:51.3045030Z ##[group]Run ./.github/actions/filter-test-configs
2025-07-17T06:46:51.3045300Z with:
2025-07-17T06:46:51.3045660Z   github-token: ***
2025-07-17T06:46:51.3046800Z   test-matrix: {"include": [{"config": "default", "shard": 1, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "default", "shard": 2, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "default", "shard": 3, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m1-13"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m1-14"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m2-15"}]}
2025-07-17T06:46:51.3048160Z   job-name: macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)
2025-07-17T06:46:51.3048440Z env:
2025-07-17T06:46:51.3048600Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:51.3048830Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:51.3049050Z   TEST_CONFIG: default
2025-07-17T06:46:51.3049250Z   SHARD_NUMBER: 1
2025-07-17T06:46:51.3049420Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:51.3049600Z   PR_BODY: 
2025-07-17T06:46:51.3049850Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:51.3050150Z ##[endgroup]
2025-07-17T06:46:51.3076290Z ##[group]Run nick-fields/retry@v3.0.0
2025-07-17T06:46:51.3076520Z with:
2025-07-17T06:46:51.3076670Z   shell: bash
2025-07-17T06:46:51.3076820Z   timeout_minutes: 10
2025-07-17T06:46:51.3077040Z   max_attempts: 5
2025-07-17T06:46:51.3077210Z   retry_wait_seconds: 30
2025-07-17T06:46:51.3077900Z   command: set -eux
# PyYAML 6.0 doesn't work with MacOS x86 anymore
# This must run on Python-3.7 (AmazonLinux2) so can't use request=3.32.2
python3 -m pip install requests==2.27.1 pyyaml==6.0.1

2025-07-17T06:46:51.3078670Z   polling_interval_seconds: 1
2025-07-17T06:46:51.3078900Z   warning_on_retry: true
2025-07-17T06:46:51.3079090Z   continue_on_error: false
2025-07-17T06:46:51.3079290Z env:
2025-07-17T06:46:51.3079470Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:51.3079700Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:51.3079930Z   TEST_CONFIG: default
2025-07-17T06:46:51.3080120Z   SHARD_NUMBER: 1
2025-07-17T06:46:51.3080310Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:51.3080480Z   PR_BODY: 
2025-07-17T06:46:51.3080780Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:51.3081150Z   GITHUB_TOKEN: ***
2025-07-17T06:46:51.3081320Z ##[endgroup]
2025-07-17T06:46:51.3822530Z + python3 -m pip install requests==2.27.1 pyyaml==6.0.1
2025-07-17T06:46:51.5760340Z Collecting requests==2.27.1
2025-07-17T06:46:51.5789840Z   Using cached requests-2.27.1-py2.py3-none-any.whl.metadata (5.0 kB)
2025-07-17T06:46:51.6005980Z Collecting pyyaml==6.0.1
2025-07-17T06:46:51.6023860Z   Using cached PyYAML-6.0.1-cp312-cp312-macosx_11_0_arm64.whl.metadata (2.1 kB)
2025-07-17T06:46:51.6208480Z Collecting urllib3<1.27,>=1.21.1 (from requests==2.27.1)
2025-07-17T06:46:51.6254280Z   Using cached urllib3-1.26.20-py2.py3-none-any.whl.metadata (50 kB)
2025-07-17T06:46:51.6359950Z Requirement already satisfied: certifi>=2017.4.17 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from requests==2.27.1) (2025.7.14)
2025-07-17T06:46:51.6769440Z Collecting charset-normalizer~=2.0.0 (from requests==2.27.1)
2025-07-17T06:46:51.6786100Z   Using cached charset_normalizer-2.0.12-py3-none-any.whl.metadata (11 kB)
2025-07-17T06:46:51.6829170Z Requirement already satisfied: idna<4,>=2.5 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from requests==2.27.1) (3.10)
2025-07-17T06:46:51.6881450Z Using cached requests-2.27.1-py2.py3-none-any.whl (63 kB)
2025-07-17T06:46:51.6908430Z Using cached PyYAML-6.0.1-cp312-cp312-macosx_11_0_arm64.whl (165 kB)
2025-07-17T06:46:51.6946840Z Using cached charset_normalizer-2.0.12-py3-none-any.whl (39 kB)
2025-07-17T06:46:51.6967150Z Using cached urllib3-1.26.20-py2.py3-none-any.whl (144 kB)
2025-07-17T06:46:51.7693410Z Installing collected packages: urllib3, pyyaml, charset-normalizer, requests
2025-07-17T06:46:51.7695520Z   Attempting uninstall: urllib3
2025-07-17T06:46:51.7707600Z     Found existing installation: urllib3 2.5.0
2025-07-17T06:46:51.7731180Z     Uninstalling urllib3-2.5.0:
2025-07-17T06:46:51.7739980Z       Successfully uninstalled urllib3-2.5.0
2025-07-17T06:46:51.8214430Z   Attempting uninstall: pyyaml
2025-07-17T06:46:51.8236370Z     Found existing installation: PyYAML 6.0.2
2025-07-17T06:46:51.8251140Z     Uninstalling PyYAML-6.0.2:
2025-07-17T06:46:51.8258430Z       Successfully uninstalled PyYAML-6.0.2
2025-07-17T06:46:51.8564000Z   Attempting uninstall: charset-normalizer
2025-07-17T06:46:51.8587930Z     Found existing installation: charset-normalizer 3.4.2
2025-07-17T06:46:51.8606640Z     Uninstalling charset-normalizer-3.4.2:
2025-07-17T06:46:51.8615750Z       Successfully uninstalled charset-normalizer-3.4.2
2025-07-17T06:46:51.8810210Z   Attempting uninstall: requests
2025-07-17T06:46:51.8827690Z     Found existing installation: requests 2.32.4
2025-07-17T06:46:51.8842680Z     Uninstalling requests-2.32.4:
2025-07-17T06:46:51.8848350Z       Successfully uninstalled requests-2.32.4
2025-07-17T06:46:51.9089660Z 
2025-07-17T06:46:51.9126020Z Successfully installed charset-normalizer-2.0.12 pyyaml-6.0.1 requests-2.27.1 urllib3-1.26.20
2025-07-17T06:46:52.3839080Z Command completed after 1 attempt(s).
2025-07-17T06:46:52.4031530Z ##[group]Run set -x
2025-07-17T06:46:52.4032200Z set -x
2025-07-17T06:46:52.4032700Z 
2025-07-17T06:46:52.4033560Z # Use relative path here as this could be checked out anywhere, not necessarily
2025-07-17T06:46:52.4034580Z # in runner workspace
2025-07-17T06:46:52.4036310Z python3 "${GITHUB_ACTION_PATH}/../../scripts/parse_ref.py"
2025-07-17T06:46:52.4085290Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T06:46:52.4085970Z env:
2025-07-17T06:46:52.4086430Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:52.4086930Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:52.4087510Z   TEST_CONFIG: default
2025-07-17T06:46:52.4087950Z   SHARD_NUMBER: 1
2025-07-17T06:46:52.4088410Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:52.4088830Z   PR_BODY: 
2025-07-17T06:46:52.4089430Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:52.4090200Z ##[endgroup]
2025-07-17T06:46:52.4585290Z + python3 /Users/ec2-user/runner/_work/pytorch/pytorch/./.github/actions/filter-test-configs/../../scripts/parse_ref.py
2025-07-17T06:46:52.4774430Z Setting output branch=main
2025-07-17T06:46:52.4831410Z ##[group]Run echo "Workflow: ${GITHUB_WORKFLOW}"
2025-07-17T06:46:52.4831680Z echo "Workflow: ${GITHUB_WORKFLOW}"
2025-07-17T06:46:52.4831910Z echo "Job name: ${JOB_NAME}"
2025-07-17T06:46:52.4832140Z 
2025-07-17T06:46:52.4832400Z # Use relative path here as this could be checked out anywhere, not necessarily
2025-07-17T06:46:52.4832690Z # in runner workspace
2025-07-17T06:46:52.4832980Z python3 "${GITHUB_ACTION_PATH}/../../scripts/filter_test_configs.py" \
2025-07-17T06:46:52.4833280Z   --workflow "${GITHUB_WORKFLOW}" \
2025-07-17T06:46:52.4833510Z   --job-name "${JOB_NAME}" \
2025-07-17T06:46:52.4834500Z   --test-matrix "{"include": [{"config": "default", "shard": 1, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "default", "shard": 2, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "default", "shard": 3, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m1-13"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m1-14"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m2-15"}]}" \
2025-07-17T06:46:52.4835660Z   --selected-test-configs "" \
2025-07-17T06:46:52.4835890Z   --pr-number "${PR_NUMBER}" \
2025-07-17T06:46:52.4836090Z   --tag "${TAG}" \
2025-07-17T06:46:52.4836280Z   --event-name "${EVENT_NAME}" \
2025-07-17T06:46:52.4836490Z   --schedule "${SCHEDULE}" \
2025-07-17T06:46:52.4836700Z   --branch "${HEAD_BRANCH}"
2025-07-17T06:46:52.4849040Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T06:46:52.4849280Z env:
2025-07-17T06:46:52.4849410Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:52.4849630Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:52.4849850Z   TEST_CONFIG: default
2025-07-17T06:46:52.4850000Z   SHARD_NUMBER: 1
2025-07-17T06:46:52.4850170Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:52.4850310Z   PR_BODY: 
2025-07-17T06:46:52.4850540Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:52.4851150Z   GITHUB_TOKEN: ***
2025-07-17T06:46:52.4851380Z   JOB_NAME: macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)
2025-07-17T06:46:52.4851640Z   PR_NUMBER: 
2025-07-17T06:46:52.4851770Z   TAG: 
2025-07-17T06:46:52.4851890Z   EVENT_NAME: push
2025-07-17T06:46:52.4852050Z   SCHEDULE: 
2025-07-17T06:46:52.4852170Z   HEAD_BRANCH: main
2025-07-17T06:46:52.4852320Z ##[endgroup]
2025-07-17T06:46:52.5093290Z Workflow: trunk
2025-07-17T06:46:52.5093600Z Job name: macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)
2025-07-17T06:46:52.7586410Z Setting output keep-going=True
2025-07-17T06:46:52.7586740Z Setting output ci-verbose-test-logs=False
2025-07-17T06:46:52.7587020Z Setting output ci-test-showlocals=False
2025-07-17T06:46:52.7587300Z Setting output ci-no-test-timeout=False
2025-07-17T06:46:52.7587560Z Setting output ci-no-td=False
2025-07-17T06:46:52.7587800Z Setting output ci-td-distributed=False
2025-07-17T06:46:52.7588080Z Setting output is-unstable=False
2025-07-17T06:46:52.7588310Z Setting output reenabled-issues=
2025-07-17T06:46:52.7589830Z Setting output test-matrix={"include": [{"config": "default", "shard": 1, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "default", "shard": 2, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "default", "shard": 3, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m1-13"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m1-14"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m2-15"}]}
2025-07-17T06:46:52.7591130Z Setting output is-test-matrix-empty=False
2025-07-17T06:46:52.7691430Z ##[group]Run echo "Filtered matrix:"
2025-07-17T06:46:52.7691690Z echo "Filtered matrix:"
2025-07-17T06:46:52.7692740Z echo "{"include": [{"config": "default", "shard": 1, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "default", "shard": 2, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "default", "shard": 3, "num_shards": 3, "runner": "macos-m1-stable"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m1-13"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m1-14"}, {"config": "mps", "shard": 1, "num_shards": 1, "runner": "macos-m2-15"}]}"
2025-07-17T06:46:52.7693770Z 
2025-07-17T06:46:52.7693930Z echo
2025-07-17T06:46:52.7694130Z echo "Is the current job unstable? False"
2025-07-17T06:46:52.7694380Z 
2025-07-17T06:46:52.7694520Z echo
2025-07-17T06:46:52.7694740Z echo "Is keep-going label set? True"
2025-07-17T06:46:52.7694960Z 
2025-07-17T06:46:52.7695110Z echo
2025-07-17T06:46:52.7695270Z echo "Reenabled issues? "
2025-07-17T06:46:52.7707830Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T06:46:52.7708080Z env:
2025-07-17T06:46:52.7708220Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:52.7708420Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:52.7708620Z   TEST_CONFIG: default
2025-07-17T06:46:52.7708780Z   SHARD_NUMBER: 1
2025-07-17T06:46:52.7709160Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:52.7709320Z   PR_BODY: 
2025-07-17T06:46:52.7709550Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:52.7709810Z ##[endgroup]
2025-07-17T06:46:52.7949830Z Filtered matrix:
2025-07-17T06:46:52.7950820Z {include: [{config: default, shard: 1, num_shards: 3, runner: macos-m1-stable}, {config: default, shard: 2, num_shards: 3, runner: macos-m1-stable}, {config: default, shard: 3, num_shards: 3, runner: macos-m1-stable}, {config: mps, shard: 1, num_shards: 1, runner: macos-m1-13}, {config: mps, shard: 1, num_shards: 1, runner: macos-m1-14}, {config: mps, shard: 1, num_shards: 1, runner: macos-m2-15}]}
2025-07-17T06:46:52.7951710Z 
2025-07-17T06:46:52.7951800Z Is the current job unstable? False
2025-07-17T06:46:52.7951940Z 
2025-07-17T06:46:52.7952020Z Is keep-going label set? True
2025-07-17T06:46:52.7952160Z 
2025-07-17T06:46:52.7952230Z Reenabled issues? 
2025-07-17T06:46:52.7994850Z ##[group]Run echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}"
2025-07-17T06:46:52.7995170Z echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}"
2025-07-17T06:46:52.8006720Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T06:46:52.8006950Z env:
2025-07-17T06:46:52.8007080Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:52.8007270Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:52.8007480Z   TEST_CONFIG: default
2025-07-17T06:46:52.8007630Z   SHARD_NUMBER: 1
2025-07-17T06:46:52.8007770Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:52.8007900Z   PR_BODY: 
2025-07-17T06:46:52.8008110Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:52.8008360Z   JOB_TIMEOUT: 270
2025-07-17T06:46:52.8008500Z ##[endgroup]
2025-07-17T06:46:52.8281710Z ##[group]Run # shellcheck disable=SC1090
2025-07-17T06:46:52.8281990Z # shellcheck disable=SC1090
2025-07-17T06:46:52.8282180Z set -ex
2025-07-17T06:46:52.8282480Z 
2025-07-17T06:46:52.8282670Z # TODO: Remove me later, and properly activate venv
2025-07-17T06:46:52.8282920Z PATH="$VENV_PATH/bin:$PATH"
2025-07-17T06:46:52.8283110Z export PATH
2025-07-17T06:46:52.8283250Z 
2025-07-17T06:46:52.8283460Z # Print out some information about the test environment
2025-07-17T06:46:52.8283710Z for tool in python3 python; do
2025-07-17T06:46:52.8283920Z   which $tool
2025-07-17T06:46:52.8284080Z   $tool --version
2025-07-17T06:46:52.8284250Z done
2025-07-17T06:46:52.8284380Z 
2025-07-17T06:46:52.8284570Z python3 -mpip install --no-index --no-deps dist/*.whl
2025-07-17T06:46:52.8284810Z 
2025-07-17T06:46:52.8284960Z set +e
2025-07-17T06:46:52.8285120Z pushd "${RUNNER_TEMP}"
2025-07-17T06:46:52.8285410Z # Install pip dependencies if they are not found. This is to mitigate a peculiar
2025-07-17T06:46:52.8285740Z # flaky missing dependencies on MacOS
2025-07-17T06:46:52.8285960Z python3 -c "import torch"
2025-07-17T06:46:52.8286240Z RC=$?
2025-07-17T06:46:52.8286370Z popd
2025-07-17T06:46:52.8286520Z 
2025-07-17T06:46:52.8286660Z if [ "${RC}" -ne 0 ]; then
2025-07-17T06:46:52.8286960Z   python3 -mpip install --ignore-installed -r "${PIP_REQUIREMENTS_FILE}"
2025-07-17T06:46:52.8287230Z fi
2025-07-17T06:46:52.8287360Z set -e
2025-07-17T06:46:52.8287500Z 
2025-07-17T06:46:52.8287660Z .ci/pytorch/macos-test.sh
2025-07-17T06:46:52.8299190Z shell: /bin/bash -e -l {0}
2025-07-17T06:46:52.8299370Z env:
2025-07-17T06:46:52.8299500Z   GIT_DEFAULT_BRANCH: main
2025-07-17T06:46:52.8299690Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T06:46:52.8299880Z   TEST_CONFIG: default
2025-07-17T06:46:52.8300040Z   SHARD_NUMBER: 1
2025-07-17T06:46:52.8300180Z   NUM_TEST_SHARDS: 3
2025-07-17T06:46:52.8300340Z   PR_BODY: 
2025-07-17T06:46:52.8300550Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T06:46:52.8300820Z   PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: 0
2025-07-17T06:46:52.8301040Z   PYTORCH_TEST_RERUN_DISABLED_TESTS: 0
2025-07-17T06:46:52.8301230Z   CONTINUE_THROUGH_ERROR: True
2025-07-17T06:46:52.8301430Z   VERBOSE_TEST_LOGS: False
2025-07-17T06:46:52.8301600Z   TEST_SHOWLOCALS: False
2025-07-17T06:46:52.8301770Z   NO_TEST_TIMEOUT: False
2025-07-17T06:46:52.8301920Z   NO_TD: False
2025-07-17T06:46:52.8302150Z   PIP_REQUIREMENTS_FILE: .github/requirements/pip-requirements-macOS.txt
2025-07-17T06:46:52.8302430Z   GITHUB_REPOSITORY: pytorch/pytorch
2025-07-17T06:46:52.8302630Z   GITHUB_WORKFLOW: trunk
2025-07-17T06:46:52.8302780Z   GITHUB_JOB: test
2025-07-17T06:46:52.8302940Z   GITHUB_RUN_ID: 16337959945
2025-07-17T06:46:52.8303120Z   GITHUB_RUN_NUMBER: 136346
2025-07-17T06:46:52.8303290Z   GITHUB_RUN_ATTEMPT: 1
2025-07-17T06:46:52.8303460Z   JOB_ID: 46154244367
2025-07-17T06:46:52.8303680Z   JOB_NAME: macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)
2025-07-17T06:46:52.8303940Z   REENABLED_ISSUES: 
2025-07-17T06:46:52.8304310Z   HUGGING_FACE_HUB_TOKEN: ***
2025-07-17T06:46:52.8304490Z ##[endgroup]
2025-07-17T06:46:52.8570760Z + PATH=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin:/opt/homebrew/Caskroom/miniconda/base/bin:/usr/local/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/local/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/bin:/var/run/com.apple.security.cryptexd/codex.system/bootstrap/usr/appleinternal/bin:/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin:/opt/homebrew/Caskroom/miniconda/base/bin:/opt/homebrew/Caskroom/miniconda/base/condabin:/opt/homebrew/bin:/opt/homebrew/sbin
2025-07-17T06:46:52.8572420Z + export PATH
2025-07-17T06:46:52.8572570Z + for tool in python3 python
2025-07-17T06:46:52.8572740Z + which python3
2025-07-17T06:46:52.8599840Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python3
2025-07-17T06:46:52.8600490Z + python3 --version
2025-07-17T06:46:52.8651630Z Python 3.12.11
2025-07-17T06:46:52.8653010Z + for tool in python3 python
2025-07-17T06:46:52.8653230Z + which python
2025-07-17T06:46:52.8663570Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python
2025-07-17T06:46:52.8664330Z + python --version
2025-07-17T06:46:52.8713970Z Python 3.12.11
2025-07-17T06:46:52.8716550Z + python3 -mpip install --no-index --no-deps dist/torch-2.9.0a0+gita38f433-cp312-cp312-macosx_11_0_arm64.whl
2025-07-17T06:46:53.0398390Z Processing ./dist/torch-2.9.0a0+gita38f433-cp312-cp312-macosx_11_0_arm64.whl
2025-07-17T06:46:53.1113670Z Installing collected packages: torch
2025-07-17T06:47:00.6865100Z Successfully installed torch-2.9.0a0+gita38f433
2025-07-17T06:47:00.7129010Z + set +e
2025-07-17T06:47:00.7129230Z + pushd /Users/ec2-user/runner/_work/_temp
2025-07-17T06:47:00.7129500Z + python3 -c 'import torch'
2025-07-17T06:47:00.7129770Z ~/runner/_work/_temp ~/runner/_work/pytorch/pytorch
2025-07-17T06:47:05.1305170Z + RC=0
2025-07-17T06:47:05.1305360Z + popd
2025-07-17T06:47:05.1305530Z ~/runner/_work/pytorch/pytorch
2025-07-17T06:47:05.1305750Z + '[' 0 -ne 0 ']'
2025-07-17T06:47:05.1305900Z + set -e
2025-07-17T06:47:05.1306050Z + .ci/pytorch/macos-test.sh
2025-07-17T06:47:05.1563590Z ++ dirname .ci/pytorch/macos-test.sh
2025-07-17T06:47:05.1604850Z + source .ci/pytorch/macos-common.sh
2025-07-17T06:47:05.1616600Z +++ dirname .ci/pytorch/macos-common.sh
2025-07-17T06:47:05.1628610Z ++ source .ci/pytorch/common.sh
2025-07-17T06:47:05.1637300Z ++++ dirname .ci/pytorch/common.sh
2025-07-17T06:47:05.1648620Z +++ source .ci/pytorch/common_utils.sh
2025-07-17T06:47:05.1659170Z ++++ declare -f -t trap_add
2025-07-17T06:47:05.1662070Z +++ set -ex -o pipefail
2025-07-17T06:47:05.1662270Z +++ [[ macos-py3-arm64 == *rocm* ]]
2025-07-17T06:47:05.1662720Z +++ BUILD_TEST_LIBTORCH=0
2025-07-17T06:47:05.1665250Z ++ sysctl -a
2025-07-17T06:47:05.1666340Z ++ grep machdep.cpu
2025-07-17T06:47:05.1789590Z machdep.cpu.cores_per_package: 8
2025-07-17T06:47:05.1789850Z machdep.cpu.core_count: 8
2025-07-17T06:47:05.1790100Z machdep.cpu.logical_per_package: 8
2025-07-17T06:47:05.1790320Z machdep.cpu.thread_count: 8
2025-07-17T06:47:05.1790520Z machdep.cpu.brand_string: Apple M1
2025-07-17T06:47:05.1791040Z ++ export MACOSX_DEPLOYMENT_TARGET=11.1
2025-07-17T06:47:05.1791280Z ++ MACOSX_DEPLOYMENT_TARGET=11.1
2025-07-17T06:47:05.1799740Z ++ export CXX=clang++
2025-07-17T06:47:05.1799950Z ++ CXX=clang++
2025-07-17T06:47:05.1800100Z ++ export CC=clang
2025-07-17T06:47:05.1800250Z ++ CC=clang
2025-07-17T06:47:05.1800410Z + pushd test
2025-07-17T06:47:05.1800710Z ++ python -c 'import torch; print(int(torch.backends.openmp.is_available()))'
2025-07-17T06:47:05.1801100Z ~/runner/_work/pytorch/pytorch/test ~/runner/_work/pytorch/pytorch
2025-07-17T06:47:05.9627910Z + [[ ! 1 == \1 ]]
2025-07-17T06:47:05.9628110Z + popd
2025-07-17T06:47:05.9628280Z + export TORCH_SERIALIZATION_DEBUG=1
2025-07-17T06:47:05.9628520Z + TORCH_SERIALIZATION_DEBUG=1
2025-07-17T06:47:05.9628730Z ~/runner/_work/pytorch/pytorch
2025-07-17T06:47:05.9632980Z + [[ default == *\p\e\r\f\_\a\l\l* ]]
2025-07-17T06:47:05.9633230Z + [[ default == *\p\e\r\f\_\t\o\r\c\h\b\e\n\c\h* ]]
2025-07-17T06:47:05.9633480Z + [[ default == *\p\e\r\f\_\h\f* ]]
2025-07-17T06:47:05.9633700Z + [[ default == *\p\e\r\f\_\t\i\m\m* ]]
2025-07-17T06:47:05.9633910Z + [[ default == *\p\e\r\f\_\s\m\o\k\e\t\e\s\t* ]]
2025-07-17T06:47:05.9634150Z + [[ default == *\m\p\s* ]]
2025-07-17T06:47:05.9634330Z + [[ 3 -gt 1 ]]
2025-07-17T06:47:05.9634490Z + test_python_shard 1
2025-07-17T06:47:05.9634660Z + [[ -z 3 ]]
2025-07-17T06:47:05.9634810Z + setup_test_python
2025-07-17T06:47:05.9634980Z + export GLOO_SOCKET_IFNAME=lo0
2025-07-17T06:47:05.9635600Z + GLOO_SOCKET_IFNAME=lo0
2025-07-17T06:47:05.9637760Z ++ ninja --version
2025-07-17T06:47:06.1199470Z + echo 'Ninja version: 1.10.2.git.kitware.jobserver-1'
2025-07-17T06:47:06.1199810Z Ninja version: 1.10.2.git.kitware.jobserver-1
2025-07-17T06:47:06.1202600Z ++ which python
2025-07-17T06:47:06.1220720Z ++ python --version
2025-07-17T06:47:06.1298520Z + echo 'Python version: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python (Python 3.12.11)'
2025-07-17T06:47:06.1299250Z Python version: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python (Python 3.12.11)
2025-07-17T06:47:06.1299730Z + ulimit -n 16384
2025-07-17T06:47:06.1302490Z + python test/run_test.py --verbose --exclude-jit-executor --exclude-distributed-tests --shard 1 3
2025-07-17T06:47:09.5631840Z Found test times from artifacts
2025-07-17T06:47:09.6248140Z Found test times from artifacts
2025-07-17T06:47:09.6271280Z Running all tests
2025-07-17T06:47:09.6464240Z Running parallel tests on 3 processes
2025-07-17T06:47:09.6469350Z Name: tests to run (est. time: 61.64min)
2025-07-17T06:47:09.6469590Z   Serial tests (48):
2025-07-17T06:47:09.6470610Z     test_ci_sanity_check_fail 1/1
2025-07-17T06:47:09.6470890Z     test_openreg 1/1
2025-07-17T06:47:09.6471090Z     test_fake_tensor 1/1
2025-07-17T06:47:09.6471260Z     test_namedtuple_return_api 1/1
2025-07-17T06:47:09.6471460Z     test_nn 1/1
2025-07-17T06:47:09.6471660Z     test_spectral_ops 1/1
2025-07-17T06:47:09.6471850Z     distributions/test_distributions 1/1
2025-07-17T06:47:09.6472060Z     test_extension_utils 1/1
2025-07-17T06:47:09.6472250Z     test_cpp_api_parity 1/1
2025-07-17T06:47:09.6472450Z     inductor/test_cutlass_backend 1/1
2025-07-17T06:47:09.6472740Z     test_cpp_extensions_open_device_registration 1/1
2025-07-17T06:47:09.6472980Z     test_transformers_privateuse1 1/1
2025-07-17T06:47:09.6473180Z     inductor/test_flex_attention 1/1
2025-07-17T06:47:09.6473370Z     test_fx 1/1
2025-07-17T06:47:09.6473510Z     test_show_pickle 1/1
2025-07-17T06:47:09.6473680Z     inductor/test_benchmark_fusion 1/1
2025-07-17T06:47:09.6473880Z     inductor/test_max_autotune 1/1
2025-07-17T06:47:09.6474050Z     test_utils 1/1
2025-07-17T06:47:09.6474200Z     test_multiprocessing 1/1
2025-07-17T06:47:09.6474400Z     test_tensorexpr 1/1
2025-07-17T06:47:09.6474560Z     test_jit_disabled 1/1
2025-07-17T06:47:09.6474740Z     test_cpp_extensions_mtia_backend 1/1
2025-07-17T06:47:09.6474970Z     test_cpp_extensions_stream_and_event 1/1
2025-07-17T06:47:09.6475170Z     test_dispatch 1/1
2025-07-17T06:47:09.6475320Z     test_python_dispatch 1/1
2025-07-17T06:47:09.6475500Z     test_autograd_fallback 1/1
2025-07-17T06:47:09.6475670Z     test_cuda_nvml_based_avail 1/1
2025-07-17T06:47:09.6475870Z     test_tensor_creation_ops 1/1
2025-07-17T06:47:09.6476060Z     test_cuda_trace 1/1
2025-07-17T06:47:09.6476210Z     test_autocast 1/1
2025-07-17T06:47:09.6476380Z     inductor/test_distributed_patterns 1/1
2025-07-17T06:47:09.6476590Z     dynamo/test_fake_distributed 1/1
2025-07-17T06:47:09.6476790Z     test_cpp_extensions_jit 1/1
2025-07-17T06:47:09.6476990Z     test_cuda_primary_ctx 1/1
2025-07-17T06:47:09.6477160Z     test_torch 1/1
2025-07-17T06:47:09.6477310Z     test_native_mha 1/1
2025-07-17T06:47:09.6477470Z     test_sort_and_select 1/1
2025-07-17T06:47:09.6477690Z     test_multiprocessing_spawn 1/1
2025-07-17T06:47:09.6477870Z     nn/test_pooling 1/1
2025-07-17T06:47:09.6478030Z     test_overrides 1/1
2025-07-17T06:47:09.6478170Z     test_mobile_optimizer 1/1
2025-07-17T06:47:09.6478350Z     nn/test_convolution 1/1
2025-07-17T06:47:09.6478540Z     test_reductions 1/1
2025-07-17T06:47:09.6478690Z     doctests 1/1
2025-07-17T06:47:09.6478850Z     test_autoload_disable 1/1
2025-07-17T06:47:09.6479020Z     test_autoload_enable 1/1
2025-07-17T06:47:09.6479220Z     test_cpp_extensions_aot_ninja 1/1
2025-07-17T06:47:09.6479420Z     test_cpp_extensions_aot_no_ninja 1/1
2025-07-17T06:47:09.6479610Z   Parallel tests (101):
2025-07-17T06:47:09.6480040Z     inductor/test_torchinductor_dynamic_shapes 1/2
2025-07-17T06:47:09.6480270Z     test_decomp 2/4
2025-07-17T06:47:09.6480410Z     test_decomp 3/4
2025-07-17T06:47:09.6480540Z     test_decomp 4/4
2025-07-17T06:47:09.6480700Z     inductor/test_triton_extension_backend 1/1
2025-07-17T06:47:09.6481020Z     inductor/test_extension_backend 1/1
2025-07-17T06:47:09.6481240Z     inductor/test_kernel_benchmark 1/1
2025-07-17T06:47:09.6481440Z     inductor/test_cpu_cpp_wrapper 1/1
2025-07-17T06:47:09.6481660Z     inductor/test_torchinductor_strided_blocks 1/1
2025-07-17T06:47:09.6481890Z     inductor/test_pad_mm 1/1
2025-07-17T06:47:09.6482060Z     inductor/test_torchinductor 2/2
2025-07-17T06:47:09.6482290Z     test_file_check 1/1
2025-07-17T06:47:09.6482460Z     export/test_tree_utils 1/1
2025-07-17T06:47:09.6482630Z     inductor/test_indexing 1/1
2025-07-17T06:47:09.6482810Z     dynamo/test_buffers_override 1/1
2025-07-17T06:47:09.6483020Z     test_appending_byte_serializer 1/1
2025-07-17T06:47:09.6483210Z     dynamo/test_resume 1/1
2025-07-17T06:47:09.6483380Z     inductor/test_aot_inductor 1/1
2025-07-17T06:47:09.6483580Z     inductor/test_combo_kernels 1/1
2025-07-17T06:47:09.6483770Z     torch_np/test_dtype 1/1
2025-07-17T06:47:09.6483960Z     inductor/test_metrics 1/1
2025-07-17T06:47:09.6484140Z     test_proxy_tensor 1/1
2025-07-17T06:47:09.6484350Z     inductor/test_gpu_cpp_wrapper 1/1
2025-07-17T06:47:09.6484560Z     inductor/test_torchinductor_opinfo 2/14
2025-07-17T06:47:09.6484790Z     inductor/test_torchinductor_opinfo 6/14
2025-07-17T06:47:09.6485010Z     inductor/test_torchinductor_opinfo 7/14
2025-07-17T06:47:09.6485220Z     inductor/test_torchinductor_opinfo 11/14
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2025-07-17T06:47:09.6500340Z Name: excluded (est. time: 0.0min)
2025-07-17T06:47:09.6500520Z   Serial tests (0):
2025-07-17T06:47:09.6500670Z   Parallel tests (0):
2025-07-17T06:47:09.6500920Z Running test_ci_sanity_check_fail 1/1 ... [2025-07-17 06:47:09.648657]
2025-07-17T06:47:09.6501190Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:47:09.6501960Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_ci_sanity_check_fail.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:47:09.648894]
2025-07-17T06:47:09.6503120Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /Users/ec2-user/runner/_work/pytorch/pytorch/test/.pytorch-disabled-tests.json
2025-07-17T06:47:09.6503680Z Ignoring disabled issues:  ['']
2025-07-17T06:47:18.9357340Z Running test_openreg 1/1 ... [2025-07-17 06:47:18.935612]
2025-07-17T06:47:18.9358250Z Running test_fake_tensor 1/1 ... [2025-07-17 06:47:18.935796]
2025-07-17T06:47:18.9358540Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:47:18.9361250Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_fake_tensor.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:47:18.936021]
2025-07-17T06:47:18.9362090Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading
2025-07-17T06:47:18.9362400Z Uploading artifacts took 0.00 seconds
2025-07-17T06:47:28.7220480Z 
2025-07-17T06:47:28.7221010Z test_fake_tensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fake_tensor_1.1_9c423396cc33f55e_.log
2025-07-17T06:47:28.7295190Z Running 284 items in this shard: test/test_fake_tensor.py::FakeTensorTest::test__adaptive_avg_pool2d_backward, test/test_fake_tensor.py::FakeTensorTest::test_alias_call, test/test_fake_tensor.py::FakeTensorTest::test_allow_meta, test/test_fake_tensor.py::FakeTensorTest::test_aten_copy_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_aten_index_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_aten_slice_scatter_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_basic, test/test_fake_tensor.py::FakeTensorTest::test_batch_tensor, test/test_fake_tensor.py::FakeTensorTest::test_binary_op_type_promotion, test/test_fake_tensor.py::FakeTensorTest::test_constructor, test/test_fake_tensor.py::FakeTensorTest::test_convert_fake_to_real, test/test_fake_tensor.py::FakeTensorTest::test_cpu_fallback, test/test_fake_tensor.py::FakeTensorTest::test_cuda_initialized, test/test_fake_tensor.py::FakeTensorTest::test_cuda_lstm, test/test_fake_tensor.py::FakeTensorTest::test_cudnn_rnn_with_fallback, test/test_fake_tensor.py::FakeTensorTest::test_cudnn_rnn_without_fallback, test/test_fake_tensor.py::FakeTensorTest::test_custom_op_fallback, test/test_fake_tensor.py::FakeTensorTest::test_data_dependent_operator, test/test_fake_tensor.py::FakeTensorTest::test_deepcopy, test/test_fake_tensor.py::FakeTensorTest::test_device_inplace_copy, test/test_fake_tensor.py::FakeTensorTest::test_embedding_bag_meta, test/test_fake_tensor.py::FakeTensorTest::test_export_numpy, test/test_fake_tensor.py::FakeTensorTest::test_fake_device, test/test_fake_tensor.py::FakeTensorTest::test_fake_dispatch_keys, test/test_fake_tensor.py::FakeTensorTest::test_fake_grad_copy, test/test_fake_tensor.py::FakeTensorTest::test_fake_mode_error, test/test_fake_tensor.py::FakeTensorTest::test_fast_div, test/test_fake_tensor.py::FakeTensorTest::test_from_numpy, test/test_fake_tensor.py::FakeTensorTest::test_fsdp_flat_param, test/test_fake_tensor.py::FakeTensorTest::test_full, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_complex128, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_complex64, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float32, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float64, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fn, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fnuz, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e5m2, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e5m2fnuz, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int16, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int32, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int64, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int8, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_uint8, test/test_fake_tensor.py::FakeTensorTest::test_index_put_error, test/test_fake_tensor.py::FakeTensorTest::test_jagged_fake_to_fake_preserved, test/test_fake_tensor.py::FakeTensorTest::test_like_constructor, test/test_fake_tensor.py::FakeTensorTest::test_mixed_real_and_fake_inputs, test/test_fake_tensor.py::FakeTensorTest::test_mode, test/test_fake_tensor.py::FakeTensorTest::test_nan_to_num, test/test_fake_tensor.py::FakeTensorTest::test_nanmean_out, test/test_fake_tensor.py::FakeTensorTest::test_new, test/test_fake_tensor.py::FakeTensorTest::test_no_tag_func, test/test_fake_tensor.py::FakeTensorTest::test_non_kwarg_device, test/test_fake_tensor.py::FakeTensorTest::test_non_overlapping_stride_zero, test/test_fake_tensor.py::FakeTensorTest::test_non_parameter_grad, test/test_fake_tensor.py::FakeTensorTest::test_normalize_device, test/test_fake_tensor.py::FakeTensorTest::test_out_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_parameter_instantiation, test/test_fake_tensor.py::FakeTensorTest::test_parameter_view, test/test_fake_tensor.py::FakeTensorTest::test_print_in_fake_mode, test/test_fake_tensor.py::FakeTensorTest::test_randperm, test/test_fake_tensor.py::FakeTensorTest::test_recursive_invocation, test/test_fake_tensor.py::FakeTensorTest::test_repr, test/test_fake_tensor.py::FakeTensorTest::test_same_shape_env_preserved, test/test_fake_tensor.py::FakeTensorTest::test_scalar_inputs, test/test_fake_tensor.py::FakeTensorTest::test_scan_reverse_False, test/test_fake_tensor.py::FakeTensorTest::test_scan_reverse_True, test/test_fake_tensor.py::FakeTensorTest::test_setitem, test/test_fake_tensor.py::FakeTensorTest::test_shape_take_not_device, test/test_fake_tensor.py::FakeTensorTest::test_split_return_self, test/test_fake_tensor.py::FakeTensorTest::test_throw, test/test_fake_tensor.py::FakeTensorTest::test_tolist, test/test_fake_tensor.py::FakeTensorTest::test_type_as, test/test_fake_tensor.py::FakeTensorTest::test_unbind_copy_out, test/test_fake_tensor.py::FakeTensorTest::test_unsqueeze_copy, test/test_fake_tensor.py::FakeTensorTest::test_upsample_bilinear_small_channels, test/test_fake_tensor.py::FakeTensorTest::test_zero_dim, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test__adaptive_avg_pool2d_backward_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_alias_call_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_allow_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_aten_copy_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_aten_index_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_aten_slice_scatter_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_basic_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_batch_tensor_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_binary_op_type_promotion_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_constructor_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_convert_fake_to_real_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cpu_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cuda_initialized_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cuda_lstm_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cudnn_rnn_with_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cudnn_rnn_without_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_custom_op_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_data_dependent_operator_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_deepcopy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_device_inplace_copy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_embedding_bag_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_export_numpy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_dispatch_keys_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_grad_copy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_mode_error_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fast_div_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_from_numpy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fsdp_flat_param_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_full_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_complex128_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_complex64_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float32_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float64_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fn_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fnuz_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e5m2_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e5m2fnuz_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int16_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int32_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int64_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int8_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_uint8_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_put_error_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_jagged_fake_to_fake_preserved_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_like_constructor_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_mixed_real_and_fake_inputs_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_nan_to_num_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_nanmean_out_propagate_real_tensors, 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test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_print_in_fake_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_randperm_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_recursive_invocation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_repr_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_same_shape_env_preserved_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_scalar_inputs_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_scan_reverse_False_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_scan_reverse_True_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_setitem_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_shape_take_not_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_split_return_self_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_throw_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_tolist_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_type_as_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_unbind_copy_out_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_unsqueeze_copy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_upsample_bilinear_small_channels_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_zero_dim_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorConstHandling::test_aliased_const_write, test/test_fake_tensor.py::FakeTensorConstHandling::test_constant_invalidation, test/test_fake_tensor.py::FakeTensorConstHandling::test_constant_propagate_through_functions, test/test_fake_tensor.py::FakeTensorConstHandling::test_fake_tensor_batch_norm_cpu, test/test_fake_tensor.py::FakeTensorConstHandling::test_fake_tensor_in_intlist_repro, test/test_fake_tensor.py::FakeTensorConstHandling::test_inplace_add, test/test_fake_tensor.py::FakeTensorConstHandling::test_inplace_view_invalidation, test/test_fake_tensor.py::FakeTensorConstHandling::test_shared_storage_invalidation, test/test_fake_tensor.py::FakeTensorConstHandling::test_shared_storages, test/test_fake_tensor.py::FakeTensorConstHandling::test_simple, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_aliased_const_write_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_constant_invalidation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_constant_propagate_through_functions_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_fake_tensor_batch_norm_cpu_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_fake_tensor_in_intlist_repro_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_inplace_add_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_inplace_view_invalidation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_shared_storage_invalidation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_shared_storages_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_simple_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyCatCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyCubeCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyMulCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyMulScalarCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyNMSCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyNonzeroCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpySortCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpySplitCopyCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyTakeCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyViewCopyCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyCatCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyCubeCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyMulCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyMulScalarCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyNMSCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyNonzeroCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpySortCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpySplitCopyCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyTakeCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyViewCopyCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorConverterTest::test_dead_key, test/test_fake_tensor.py::FakeTensorConverterTest::test_dead_weak_ref, test/test_fake_tensor.py::FakeTensorConverterTest::test_memoized_conversion_from_meta, test/test_fake_tensor.py::FakeTensorConverterTest::test_memoized_conversion_to_meta, test/test_fake_tensor.py::FakeTensorConverterTest::test_multiple_modes, test/test_fake_tensor.py::FakeTensorConverterTest::test_no_active_mode, test/test_fake_tensor.py::FakeTensorConverterTest::test_no_ref_cycle, test/test_fake_tensor.py::FakeTensorConverterTest::test_separate_mode_error, test/test_fake_tensor.py::FakeTensorConverterTest::test_separate_tensor_storages_non_view, test/test_fake_tensor.py::FakeTensorConverterTest::test_separate_tensor_storages_view, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_dead_key_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_dead_weak_ref_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_memoized_conversion_from_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_memoized_conversion_to_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_multiple_modes_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_no_active_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_no_ref_cycle_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_separate_mode_error_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_separate_tensor_storages_non_view_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_separate_tensor_storages_view_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_conv_c1_backward, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_cross_entropy_loss, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_embedding_bag_private, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_fake_gpu_no_init, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_flash_attention, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_like_ops, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_no_dispatch_with_like_function, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_non_kwarg_only_device, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_sparse_new, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_str_storage, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_tensor_constructors_all_have_kwarg_device, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_tensor_new, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_conv_c1_backward_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_cross_entropy_loss_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_embedding_bag_private_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_fake_gpu_no_init_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_flash_attention_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_like_ops_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_module_to_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_no_dispatch_with_like_function_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_non_kwarg_only_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_sparse_new_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_str_storage_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_tensor_constructors_all_have_kwarg_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_tensor_new_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorPropTest::test_fake_tensor_prop_on_nn_module, test/test_fake_tensor.py::FakeTensorPropTest::test_fake_tensor_prop_on_nn_module_with_optional_args, test/test_fake_tensor.py::FakeTensorPropTest::test_nonzero_stride, test/test_fake_tensor.py::FakeTensorPropTest::test_torch_load_with_fake_mode, test/test_fake_tensor.py::FakeTensorPropTest::test_unbacked_shape_realloc, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_fake_tensor_prop_on_nn_module_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_fake_tensor_prop_on_nn_module_with_optional_args_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_nonzero_stride_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_torch_load_with_fake_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_unbacked_shape_realloc_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorSerialization::test_serialization, test/test_fake_tensor.py::FakeTensorSerialization::test_serialization_with_tracing, test/test_fake_tensor.py::FakeTensorDispatchCache::test__upsample_bilinear2d_aa_backward_dynamic_shapes, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_aten_index, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_bypass, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_default_device, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_default_dtype, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_dispatch_key_set, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_hit, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_inplace_op, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_constants, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_device, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_dtype, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_is_conj, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_is_inference, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_is_neg, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_memory_format, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_requires_grad, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_shape, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_storage_offset, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_stride, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_tuple_outputs, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_view_op, test/test_fake_tensor.py::FakeTensorDispatchCache::test_fft_hfft2_issue145522, test/test_fake_tensor.py::FakeTensorDispatchCache::test_from_buffer, test/test_fake_tensor.py::FakeTensorDispatchCache::test_inference_mode, test/test_fake_tensor.py::FakeTensorDispatchCache::test_invoke_subgraph, test/test_fake_tensor.py::FakeTensorDispatchCache::test_invoke_subgraph_cacheable_inplace, test/test_fake_tensor.py::FakeTensorDispatchCache::test_meta_tensor_to_fake_cpu, test/test_fake_tensor.py::FakeTensorDispatchCache::test_shape_env_settings, test/test_fake_tensor.py::FakeTensorDispatchCache::test_unbacked_output, test/test_fake_tensor.py::FakeTensorDispatchCache::test_wrapper_tensor_subclass_different_device
2025-07-17T06:47:28.7358660Z 
2025-07-17T06:47:28.7358820Z Running test_namedtuple_return_api 1/1 ... [2025-07-17 06:47:28.722644]
2025-07-17T06:47:28.7359090Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:47:28.7359830Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_namedtuple_return_api.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:47:28.722915]
2025-07-17T06:47:31.2513380Z 
2025-07-17T06:47:31.2514080Z test_namedtuple_return_api 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_namedtuple_return_api_1.1_a7a0add8a8ca3ffb_.log
2025-07-17T06:47:31.2515510Z Running 3 items in this shard: test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_import_return_types, test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_namedtuple_return, test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_native_functions_yaml
2025-07-17T06:47:31.2516410Z 
2025-07-17T06:47:31.2518040Z Running test_nn 1/1 ... [2025-07-17 06:47:31.251742]
2025-07-17T06:47:31.2518360Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:47:31.2521540Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_nn.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:47:31.252048]
2025-07-17T06:49:24.1992670Z 
2025-07-17T06:49:24.1993200Z test_nn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_nn_1.1_8d108c8b39758257_.log
2025-07-17T06:49:24.3207010Z Running 3422 items in this shard: test/test_nn.py::TestNN::test_AdaptiveLogSoftmax, test/test_nn.py::TestNN::test_AdaptiveLogSoftmax_cuda, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_BCELoss_no_reduce, test/test_nn.py::TestNN::test_BCELoss_no_reduce_cuda, test/test_nn.py::TestNN::test_BCELoss_no_reduce_scalar, test/test_nn.py::TestNN::test_BCELoss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce_cuda, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce_scalar, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_legacy_enum, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_legacy_enum_cuda, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce_scalar, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_CELU_no_batch_dim, test/test_nn.py::TestNN::test_CELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_CTCLoss_critical_target_len, test/test_nn.py::TestNN::test_CTCLoss_lengthchecks_cpu, test/test_nn.py::TestNN::test_CTCLoss_lengthchecks_cuda, test/test_nn.py::TestNN::test_CTCLoss_long_targets, test/test_nn.py::TestNN::test_CTCLoss_typechecks, test/test_nn.py::TestNN::test_CTCLoss_zero_infinity, test/test_nn.py::TestNN::test_CTCLoss_zero_lengths, test/test_nn.py::TestNN::test_Conv1d, test/test_nn.py::TestNN::test_Conv1d_circular_stride2_pad2, test/test_nn.py::TestNN::test_Conv1d_circular_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_cuda, test/test_nn.py::TestNN::test_Conv1d_dilated, test/test_nn.py::TestNN::test_Conv1d_dilated_cuda, test/test_nn.py::TestNN::test_Conv1d_groups, test/test_nn.py::TestNN::test_Conv1d_groups_cuda, test/test_nn.py::TestNN::test_Conv1d_pad1, test/test_nn.py::TestNN::test_Conv1d_pad1_cuda, test/test_nn.py::TestNN::test_Conv1d_pad1size1, test/test_nn.py::TestNN::test_Conv1d_pad1size1_cuda, test/test_nn.py::TestNN::test_Conv1d_pad2, test/test_nn.py::TestNN::test_Conv1d_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_pad2size1, test/test_nn.py::TestNN::test_Conv1d_pad2size1_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_same, test/test_nn.py::TestNN::test_Conv1d_pad_same2, test/test_nn.py::TestNN::test_Conv1d_pad_same2_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_same_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_same_dilated, test/test_nn.py::TestNN::test_Conv1d_pad_same_dilated_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_valid, test/test_nn.py::TestNN::test_Conv1d_pad_valid_cuda, test/test_nn.py::TestNN::test_Conv1d_reflect_stride2_pad2, test/test_nn.py::TestNN::test_Conv1d_reflect_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_replicate_stride2_pad2, test/test_nn.py::TestNN::test_Conv1d_replicate_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_stride, test/test_nn.py::TestNN::test_Conv1d_stride_cuda, test/test_nn.py::TestNN::test_Conv1d_zero_batch, test/test_nn.py::TestNN::test_Conv1d_zero_batch_cuda, test/test_nn.py::TestNN::test_Conv1d_zeros_stride2_pad2, test/test_nn.py::TestNN::test_Conv1d_zeros_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d, test/test_nn.py::TestNN::test_Conv2d_circular_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_circular_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise, test/test_nn.py::TestNN::test_Conv2d_depthwise_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_dilated, test/test_nn.py::TestNN::test_Conv2d_depthwise_dilated_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_padded, test/test_nn.py::TestNN::test_Conv2d_depthwise_padded_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_strided, test/test_nn.py::TestNN::test_Conv2d_depthwise_strided_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_with_multiplier, test/test_nn.py::TestNN::test_Conv2d_depthwise_with_multiplier_cuda, test/test_nn.py::TestNN::test_Conv2d_dilated, test/test_nn.py::TestNN::test_Conv2d_dilated_cuda, test/test_nn.py::TestNN::test_Conv2d_dilated_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_dilated_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_groups, test/test_nn.py::TestNN::test_Conv2d_groups_cuda, test/test_nn.py::TestNN::test_Conv2d_groups_thnn, test/test_nn.py::TestNN::test_Conv2d_groups_thnn_cuda, test/test_nn.py::TestNN::test_Conv2d_groups_thnn_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_groups_thnn_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_groups_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_groups_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_no_bias, test/test_nn.py::TestNN::test_Conv2d_no_bias_cuda, test/test_nn.py::TestNN::test_Conv2d_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_no_bias_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_pad_same, test/test_nn.py::TestNN::test_Conv2d_pad_same_cuda, test/test_nn.py::TestNN::test_Conv2d_pad_same_dilated, test/test_nn.py::TestNN::test_Conv2d_pad_same_dilated_cuda, test/test_nn.py::TestNN::test_Conv2d_pad_valid, test/test_nn.py::TestNN::test_Conv2d_pad_valid_cuda, test/test_nn.py::TestNN::test_Conv2d_padding, test/test_nn.py::TestNN::test_Conv2d_padding_cuda, test/test_nn.py::TestNN::test_Conv2d_padding_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_padding_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_reflect_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_reflect_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d_replicate_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_replicate_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d_strided, test/test_nn.py::TestNN::test_Conv2d_strided_cuda, test/test_nn.py::TestNN::test_Conv2d_strided_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_strided_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_zero_batch, test/test_nn.py::TestNN::test_Conv2d_zero_batch_cuda, test/test_nn.py::TestNN::test_Conv2d_zero_batch_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_zero_batch_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_zeros_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_zeros_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv3d, test/test_nn.py::TestNN::test_Conv3d_1x1x1_no_bias, test/test_nn.py::TestNN::test_Conv3d_1x1x1_no_bias_cuda, test/test_nn.py::TestNN::test_Conv3d_1x1x1_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_1x1x1_no_bias_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_circular_stride2_pad2, test/test_nn.py::TestNN::test_Conv3d_circular_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv3d_cuda, test/test_nn.py::TestNN::test_Conv3d_dilated, test/test_nn.py::TestNN::test_Conv3d_dilated_cuda, test/test_nn.py::TestNN::test_Conv3d_dilated_strided, test/test_nn.py::TestNN::test_Conv3d_dilated_strided_cuda, test/test_nn.py::TestNN::test_Conv3d_groups, test/test_nn.py::TestNN::test_Conv3d_groups_cuda, test/test_nn.py::TestNN::test_Conv3d_groups_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_groups_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_no_bias, test/test_nn.py::TestNN::test_Conv3d_no_bias_cuda, test/test_nn.py::TestNN::test_Conv3d_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_no_bias_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_pad_same, test/test_nn.py::TestNN::test_Conv3d_pad_same_cuda, test/test_nn.py::TestNN::test_Conv3d_pad_same_dilated, test/test_nn.py::TestNN::test_Conv3d_pad_same_dilated_cuda, test/test_nn.py::TestNN::test_Conv3d_pad_valid, test/test_nn.py::TestNN::test_Conv3d_pad_valid_cuda, test/test_nn.py::TestNN::test_Conv3d_replicate_stride2_pad2, test/test_nn.py::TestNN::test_Conv3d_replicate_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv3d_stride, test/test_nn.py::TestNN::test_Conv3d_stride_cuda, test/test_nn.py::TestNN::test_Conv3d_stride_padding, test/test_nn.py::TestNN::test_Conv3d_stride_padding_cuda, test/test_nn.py::TestNN::test_Conv3d_stride_padding_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_stride_padding_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_stride_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_stride_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_zero_batch, test/test_nn.py::TestNN::test_Conv3d_zero_batch_cuda, test/test_nn.py::TestNN::test_Conv3d_zero_batch_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_zero_batch_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_zeros_stride2_pad2, test/test_nn.py::TestNN::test_Conv3d_zeros_stride2_pad2_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d, test/test_nn.py::TestNN::test_ConvTranspose1d_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d_dilated, test/test_nn.py::TestNN::test_ConvTranspose1d_dilated_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d_groups, test/test_nn.py::TestNN::test_ConvTranspose1d_groups_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d_no_bias, test/test_nn.py::TestNN::test_ConvTranspose1d_no_bias_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d, test/test_nn.py::TestNN::test_ConvTranspose2d_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_dilated, test/test_nn.py::TestNN::test_ConvTranspose2d_dilated_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_dilated_with_long_tensor, test/test_nn.py::TestNN::test_ConvTranspose2d_dilated_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_groups, test/test_nn.py::TestNN::test_ConvTranspose2d_groups_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_groups_with_long_tensor, test/test_nn.py::TestNN::test_ConvTranspose2d_groups_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_with_long_tensor, test/test_nn.py::TestNN::test_ConvTranspose2d_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose3d, test/test_nn.py::TestNN::test_ConvTranspose3d_cuda, test/test_nn.py::TestNN::test_ConvTranspose3d_dilated, test/test_nn.py::TestNN::test_ConvTranspose3d_dilated_cuda, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_CrossMapLRN2d, test/test_nn.py::TestNN::test_CrossMapLRN2d_cuda, test/test_nn.py::TestNN::test_ELU_no_batch_dim, test/test_nn.py::TestNN::test_ELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Embedding, test/test_nn.py::TestNN::test_EmbeddingBag_discontiguous, test/test_nn.py::TestNN::test_EmbeddingBag_discontiguous_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_max, test/test_nn.py::TestNN::test_EmbeddingBag_max_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_max_padding_idx, test/test_nn.py::TestNN::test_EmbeddingBag_max_padding_idx_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_mean, test/test_nn.py::TestNN::test_EmbeddingBag_mean_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_mean_padding_idx, test/test_nn.py::TestNN::test_EmbeddingBag_mean_padding_idx_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_sparse, test/test_nn.py::TestNN::test_EmbeddingBag_sparse_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_sum, test/test_nn.py::TestNN::test_EmbeddingBag_sum_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_sum_padding_idx, test/test_nn.py::TestNN::test_EmbeddingBag_sum_padding_idx_cuda, test/test_nn.py::TestNN::test_Embedding_cuda, test/test_nn.py::TestNN::test_Embedding_discontiguous, test/test_nn.py::TestNN::test_Embedding_discontiguous_cuda, test/test_nn.py::TestNN::test_Embedding_sparse, test/test_nn.py::TestNN::test_Embedding_sparse_cuda, test/test_nn.py::TestNN::test_Flatten, test/test_nn.py::TestNN::test_Flatten_cuda, test/test_nn.py::TestNN::test_Flatten_no_batch_dim, test/test_nn.py::TestNN::test_Flatten_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Fold, test/test_nn.py::TestNN::test_Fold_cuda, test/test_nn.py::TestNN::test_Fold_int_input, test/test_nn.py::TestNN::test_Fold_int_input_cuda, test/test_nn.py::TestNN::test_Fold_no_batch_dim_input, test/test_nn.py::TestNN::test_Fold_no_batch_dim_input_cuda, test/test_nn.py::TestNN::test_Fold_no_batch_dim_int_input, test/test_nn.py::TestNN::test_Fold_no_batch_dim_int_input_cuda, test/test_nn.py::TestNN::test_GELU_no_batch_dim, test/test_nn.py::TestNN::test_GELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_GLU_no_batch_dim, test/test_nn.py::TestNN::test_GLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Hardshrink_no_batch_dim, test/test_nn.py::TestNN::test_Hardshrink_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Hardsigmoid_no_batch_dim, test/test_nn.py::TestNN::test_Hardsigmoid_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Hardswish_no_batch_dim, test/test_nn.py::TestNN::test_Hardswish_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Hardtanh_no_batch_dim, test/test_nn.py::TestNN::test_Hardtanh_no_batch_dim_cuda, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_margin_no_reduce, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_margin_no_reduce_cuda, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_reduce, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_HuberLoss_delta, test/test_nn.py::TestNN::test_HuberLoss_delta_cuda, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_batch_mean, test/test_nn.py::TestNN::test_KLDivLoss_batch_mean_log_target, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_log_target, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_log_target_cuda, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar_log_target, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar_log_target_cuda, test/test_nn.py::TestNN::test_KLDivLoss_with_log_target_no_reduce, test/test_nn.py::TestNN::test_KLDivLoss_with_log_target_no_reduce_cuda, test/test_nn.py::TestNN::test_KLDivLoss_with_target_no_reduce, test/test_nn.py::TestNN::test_KLDivLoss_with_target_no_reduce_cuda, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_L1Loss_no_reduce, test/test_nn.py::TestNN::test_L1Loss_no_reduce_complex, test/test_nn.py::TestNN::test_L1Loss_no_reduce_complex_cuda, test/test_nn.py::TestNN::test_L1Loss_no_reduce_cuda, test/test_nn.py::TestNN::test_L1Loss_no_reduce_scalar, test/test_nn.py::TestNN::test_L1Loss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_LSTM_cell, test/test_nn.py::TestNN::test_LSTM_cell_forward_hidden_size, test/test_nn.py::TestNN::test_LSTM_cell_forward_input_size, test/test_nn.py::TestNN::test_LayerNorm_3d_no_affine_large_feature, test/test_nn.py::TestNN::test_LayerNorm_3d_no_affine_large_feature_cuda, test/test_nn.py::TestNN::test_LayerNorm_3d_no_affine_large_feature_eval, test/test_nn.py::TestNN::test_LayerNorm_3d_no_affine_large_feature_eval_cuda, test/test_nn.py::TestNN::test_LeakyReLU_no_batch_dim, test/test_nn.py::TestNN::test_LeakyReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Linear, test/test_nn.py::TestNN::test_Linear_cuda, test/test_nn.py::TestNN::test_Linear_no_batch_dim, test/test_nn.py::TestNN::test_Linear_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Linear_no_bias, test/test_nn.py::TestNN::test_Linear_no_bias_cuda, test/test_nn.py::TestNN::test_LogSigmoid_no_batch_dim, test/test_nn.py::TestNN::test_LogSigmoid_no_batch_dim_cuda, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MSELoss_no_reduce, test/test_nn.py::TestNN::test_MSELoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MSELoss_no_reduce_scalar, test/test_nn.py::TestNN::test_MSELoss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MaxUnpool1d_net, test/test_nn.py::TestNN::test_MaxUnpool1d_net_cuda, test/test_nn.py::TestNN::test_MaxUnpool1d_net_no_batch_dim, test/test_nn.py::TestNN::test_MaxUnpool1d_net_no_batch_dim_cuda, test/test_nn.py::TestNN::test_MaxUnpool2d_net, test/test_nn.py::TestNN::test_MaxUnpool2d_net_cuda, test/test_nn.py::TestNN::test_MaxUnpool2d_net_no_batch_dim, test/test_nn.py::TestNN::test_MaxUnpool2d_net_no_batch_dim_cuda, test/test_nn.py::TestNN::test_MaxUnpool3d_net, test/test_nn.py::TestNN::test_MaxUnpool3d_net_cuda, test/test_nn.py::TestNN::test_MaxUnpool3d_net_no_batch_dim, test/test_nn.py::TestNN::test_MaxUnpool3d_net_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Mish_no_batch_dim, test/test_nn.py::TestNN::test_Mish_no_batch_dim_cuda, test/test_nn.py::TestNN::test_ModuleDict, test/test_nn.py::TestNN::test_ModuleList, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_0d_no_reduce, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_0d_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_1d_no_reduce, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_1d_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_index_neg, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_index_neg_cuda, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_reduce, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_reduce, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_weights_no_reduce, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_weights_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_1d_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_1d_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_margin_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_margin_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_p_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_p_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_weights_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_weights_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_ignore_index, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_ignore_index_cuda, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_weights, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_weights_cuda, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_ignore_index, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_ignore_index_cuda, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_weights, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_weights_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_NLLLoss_no_reduce, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_ignore_index, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_ignore_index_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index_neg, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index_neg_cuda, test/test_nn.py::TestNN::test_PReLU_backward_requires_grad_false, test/test_nn.py::TestNN::test_PReLU_no_batch_dim, test/test_nn.py::TestNN::test_PReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_PairwiseDistance, test/test_nn.py::TestNN::test_PairwiseDistance_broadcast_lhs, test/test_nn.py::TestNN::test_PairwiseDistance_broadcast_lhs_cuda, test/test_nn.py::TestNN::test_PairwiseDistance_broadcast_rhs, test/test_nn.py::TestNN::test_PairwiseDistance_broadcast_rhs_cuda, test/test_nn.py::TestNN::test_PairwiseDistance_cuda, test/test_nn.py::TestNN::test_PairwiseDistance_no_batch_dim, test/test_nn.py::TestNN::test_PairwiseDistance_no_batch_dim_cuda, test/test_nn.py::TestNN::test_PairwiseDistance_with_non_default_args, test/test_nn.py::TestNN::test_PairwiseDistance_with_non_default_args_cuda, test/test_nn.py::TestNN::test_ParameterDict, test/test_nn.py::TestNN::test_ParameterDict_replication, test/test_nn.py::TestNN::test_ParameterList, test/test_nn.py::TestNN::test_ParameterList_meta, test/test_nn.py::TestNN::test_ParameterList_replication, test/test_nn.py::TestNN::test_PixelShuffle, test/test_nn.py::TestNN::test_PixelShuffle_cuda, test/test_nn.py::TestNN::test_PixelUnshuffle, test/test_nn.py::TestNN::test_PixelUnshuffle_cuda, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_reduce, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_RNN_cell, test/test_nn.py::TestNN::test_RNN_cell_forward_zero_hidden_size, test/test_nn.py::TestNN::test_RNN_cell_no_broadcasting, test/test_nn.py::TestNN::test_RNN_change_dropout, test/test_nn.py::TestNN::test_RNN_cpu_vs_cudnn_no_dropout, test/test_nn.py::TestNN::test_RNN_cpu_vs_cudnn_with_dropout, test/test_nn.py::TestNN::test_RNN_cudnn_weight_norm, test/test_nn.py::TestNN::test_RNN_dropout, test/test_nn.py::TestNN::test_RNN_dropout_state, test/test_nn.py::TestNN::test_RNN_input_size_zero, test/test_nn.py::TestNN::test_RNN_nonlinearity, test/test_nn.py::TestNN::test_RNN_nonlinearity_passed_as_arg, test/test_nn.py::TestNN::test_RReLU, test/test_nn.py::TestNN::test_RReLU_cuda, test/test_nn.py::TestNN::test_RReLU_no_batch_dim, test/test_nn.py::TestNN::test_RReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_RReLU_with_up_down, test/test_nn.py::TestNN::test_RReLU_with_up_down_cuda, test/test_nn.py::TestNN::test_RReLU_with_up_down_scalar, test/test_nn.py::TestNN::test_RReLU_with_up_down_scalar_cuda, test/test_nn.py::TestNN::test_ReLU6_no_batch_dim, test/test_nn.py::TestNN::test_ReLU6_no_batch_dim_cuda, test/test_nn.py::TestNN::test_ReLU_no_batch_dim, test/test_nn.py::TestNN::test_ReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_ReplicationPad3d, test/test_nn.py::TestNN::test_ReplicationPad3d_complex, test/test_nn.py::TestNN::test_ReplicationPad3d_complex_cuda, test/test_nn.py::TestNN::test_ReplicationPad3d_cuda, test/test_nn.py::TestNN::test_ReplicationPad3d_no_batch_dim, test/test_nn.py::TestNN::test_ReplicationPad3d_no_batch_dim_cuda, test/test_nn.py::TestNN::test_SELU_no_batch_dim, test/test_nn.py::TestNN::test_SELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Sequential_add, test/test_nn.py::TestNN::test_Sequential_append, test/test_nn.py::TestNN::test_Sequential_delitem, test/test_nn.py::TestNN::test_Sequential_extend, test/test_nn.py::TestNN::test_Sequential_getitem, test/test_nn.py::TestNN::test_Sequential_iadd, test/test_nn.py::TestNN::test_Sequential_imul, test/test_nn.py::TestNN::test_Sequential_insert, test/test_nn.py::TestNN::test_Sequential_insert_fail_case, test/test_nn.py::TestNN::test_Sequential_mul, test/test_nn.py::TestNN::test_Sequential_pop, test/test_nn.py::TestNN::test_Sequential_rmul, test/test_nn.py::TestNN::test_Sequential_setitem, test/test_nn.py::TestNN::test_Sequential_setitem_named, test/test_nn.py::TestNN::test_SiLU_no_batch_dim, test/test_nn.py::TestNN::test_SiLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Sigmoid_no_batch_dim, test/test_nn.py::TestNN::test_Sigmoid_no_batch_dim_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_beta, test/test_nn.py::TestNN::test_SmoothL1Loss_beta_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_none, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_sum, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce_scalar, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_zero_beta, test/test_nn.py::TestNN::test_SmoothL1Loss_zero_beta_cuda, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_SoftMarginLoss_no_reduce, test/test_nn.py::TestNN::test_SoftMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_Softplus_no_batch_dim, test/test_nn.py::TestNN::test_Softplus_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Softshrink_no_batch_dim, test/test_nn.py::TestNN::test_Softshrink_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Softsign_no_batch_dim, test/test_nn.py::TestNN::test_Softsign_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Tanh_no_batch_dim, test/test_nn.py::TestNN::test_Tanh_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Tanhshrink_no_batch_dim, test/test_nn.py::TestNN::test_Tanhshrink_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Threshold_no_batch_dim, test/test_nn.py::TestNN::test_Threshold_no_batch_dim_cuda, test/test_nn.py::TestNN::test_TransformerDecoderLayer_gelu_activation, test/test_nn.py::TestNN::test_TransformerDecoderLayer_gelu_activation_cuda, test/test_nn.py::TestNN::test_TransformerDecoderLayer_relu_activation, test/test_nn.py::TestNN::test_TransformerDecoderLayer_relu_activation_cuda, test/test_nn.py::TestNN::test_TransformerEncoderLayer_gelu_activation, test/test_nn.py::TestNN::test_TransformerEncoderLayer_gelu_activation_cuda, test/test_nn.py::TestNN::test_TransformerEncoderLayer_relu_activation, test/test_nn.py::TestNN::test_TransformerEncoderLayer_relu_activation_cuda, test/test_nn.py::TestNN::test_Transformer_cell, test/test_nn.py::TestNN::test_Transformer_multilayer_coder, test/test_nn.py::TestNN::test_Transformer_multilayer_coder_cuda, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_Unflatten_no_batch_dim, test/test_nn.py::TestNN::test_Unflatten_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Unfold, test/test_nn.py::TestNN::test_Unfold_cuda, test/test_nn.py::TestNN::test_Unfold_int_input, test/test_nn.py::TestNN::test_Unfold_int_input_cuda, test/test_nn.py::TestNN::test_adaptive_log_softmax, test/test_nn.py::TestNN::test_add_module, test/test_nn.py::TestNN::test_add_module_raises_error_if_attr_exists, test/test_nn.py::TestNN::test_affine_grid, test/test_nn.py::TestNN::test_affine_grid_3d, test/test_nn.py::TestNN::test_affine_grid_backward_cl_cf_consistency_device_cpu_nd_2, test/test_nn.py::TestNN::test_affine_grid_backward_cl_cf_consistency_device_cpu_nd_3, test/test_nn.py::TestNN::test_affine_grid_error_checking, test/test_nn.py::TestNN::test_assignment, test/test_nn.py::TestNN::test_batch_norm_update_stats, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_cpu_float32, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_cpu_float32, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_cpu_float32, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_cpu_float32, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_buffer_update_when_stats_are_not_tracked, test/test_nn.py::TestNN::test_batchnorm_cudnn_half, test/test_nn.py::TestNN::test_batchnorm_cudnn_nhwc, test/test_nn.py::TestNN::test_batchnorm_half_overflow, test/test_nn.py::TestNN::test_batchnorm_load_state_dict, test/test_nn.py::TestNN::test_batchnorm_nhwc_cpu, test/test_nn.py::TestNN::test_batchnorm_nhwc_cuda, test/test_nn.py::TestNN::test_batchnorm_non_contig_cpu_BatchNorm2d, test/test_nn.py::TestNN::test_batchnorm_non_contig_cpu_SyncBatchNorm, test/test_nn.py::TestNN::test_batchnorm_nonaffine_cuda_half_input, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_bias_is_not_same_size_as_input, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_less_than_one_value_per_channel, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_running_mean_is_not_same_size_as_input, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_running_var_is_not_same_size_as_input, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_running_var_or_running_mean_have_forward_grad, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_weight_is_not_same_size_as_input, test/test_nn.py::TestNN::test_bce_loss_always_nonnegative, test/test_nn.py::TestNN::test_bce_loss_broadcasts_weights, test/test_nn.py::TestNN::test_bce_loss_input_range, test/test_nn.py::TestNN::test_bce_loss_size_mismatch, test/test_nn.py::TestNN::test_bce_with_logits_broadcasts_pos_weights, test/test_nn.py::TestNN::test_bce_with_logits_broadcasts_weights, test/test_nn.py::TestNN::test_bce_with_logits_gives_same_result_as_sigmoid_and_bce_loss, test/test_nn.py::TestNN::test_bce_with_logits_gives_same_result_as_sigmoid_and_bce_loss_large_tensors_with_grad, test/test_nn.py::TestNN::test_bce_with_logits_has_correct_forward_grad, test/test_nn.py::TestNN::test_bce_with_logits_has_correct_grad_at_zero, test/test_nn.py::TestNN::test_bce_with_logits_ones_in_pos_weights_are_the_same_as_none, test/test_nn.py::TestNN::test_bce_with_logits_raises_if_target_and_input_are_different_size, test/test_nn.py::TestNN::test_bce_with_logits_stability, test/test_nn.py::TestNN::test_bce_with_logits_with_pos_weight_has_correct_grad_at_zero, test/test_nn.py::TestNN::test_bilinear, test/test_nn.py::TestNN::test_bilinear_broadcasting, test/test_nn.py::TestNN::test_bilinear_no_bias, test/test_nn.py::TestNN::test_bilinear_non_contiguous, test/test_nn.py::TestNN::test_bilinear_value_error, test/test_nn.py::TestNN::test_broadcast_double_backwards_gpu, test/test_nn.py::TestNN::test_broadcast_no_grad, test/test_nn.py::TestNN::test_broadcast_not_requiring_grad, test/test_nn.py::TestNN::test_buffer_bad_module_subclass, test/test_nn.py::TestNN::test_buffer_not_persistent, test/test_nn.py::TestNN::test_buffer_not_persistent_assign, test/test_nn.py::TestNN::test_buffer_not_persistent_del, test/test_nn.py::TestNN::test_buffer_not_persistent_load, test/test_nn.py::TestNN::test_buffer_not_persistent_overwrite, test/test_nn.py::TestNN::test_buffers_and_named_buffers, test/test_nn.py::TestNN::test_call_supports_python_dict_output, test/test_nn.py::TestNN::test_channel_shuffle_input_checks, test/test_nn.py::TestNN::test_channel_shuffle_return_alias_of_self, test/test_nn.py::TestNN::test_children, test/test_nn.py::TestNN::test_container_copy, test/test_nn.py::TestNN::test_convert_sync_batchnorm, test/test_nn.py::TestNN::test_cosine_embedding_loss_error_on_diff_shapes, test/test_nn.py::TestNN::test_cosine_embedding_loss_error_on_nonexpandable_shapes, test/test_nn.py::TestNN::test_cosine_embedding_loss_invalid_shape, test/test_nn.py::TestNN::test_cosine_embedding_loss_margin_no_reduce, test/test_nn.py::TestNN::test_cosine_embedding_loss_no_reduce, test/test_nn.py::TestNN::test_cosine_embedding_loss_with_diff_type, test/test_nn.py::TestNN::test_cosine_similarity, test/test_nn.py::TestNN::test_cross_entropy_loss, test/test_nn.py::TestNN::test_cross_entropy_loss_precision, test/test_nn.py::TestNN::test_cross_entropy_loss_zero_div, test/test_nn.py::TestNN::test_cudnn_forward_exception, test/test_nn.py::TestNN::test_cudnn_rnn_dropout_states_device, test/test_nn.py::TestNN::test_cudnn_weight_format, test/test_nn.py::TestNN::test_cudnn_weight_tying, test/test_nn.py::TestNN::test_dir, test/test_nn.py::TestNN::test_dir_digit, test/test_nn.py::TestNN::test_elu_inplace_gradgrad, test/test_nn.py::TestNN::test_elu_inplace_on_view, test/test_nn.py::TestNN::test_error_RNN_seq_len_zero, test/test_nn.py::TestNN::test_extra_state, test/test_nn.py::TestNN::test_extra_state_missing_get_extra_state, test/test_nn.py::TestNN::test_extra_state_missing_set_extra_state, test/test_nn.py::TestNN::test_extra_state_non_dict, test/test_nn.py::TestNN::test_fb_fc_packed, test/test_nn.py::TestNN::test_flatten, test/test_nn.py::TestNN::test_fold_invalid_arg, test/test_nn.py::TestNN::test_fractional_max_pool2d_invalid_output_ratio, test/test_nn.py::TestNN::test_gaussian_nll_loss_args, test/test_nn.py::TestNN::test_gaussian_nll_loss_broadcasting, test/test_nn.py::TestNN::test_gaussian_nll_loss_scalar_var, test/test_nn.py::TestNN::test_get_buffer, test/test_nn.py::TestNN::test_get_buffer_from_submodules, test/test_nn.py::TestNN::test_getattr_with_property, test/test_nn.py::TestNN::test_grid_sample, test/test_nn.py::TestNN::test_grid_sample_3d, test/test_nn.py::TestNN::test_grid_sample_error_checking, test/test_nn.py::TestNN::test_grid_sample_nearest_neighbor_rounding_mode_consistency, test/test_nn.py::TestNN::test_hardtanh_backward, test/test_nn.py::TestNN::test_hardtanh_inplace_gradgrad, test/test_nn.py::TestNN::test_huber_loss_invalid_delta, test/test_nn.py::TestNN::test_inplace_thnn, test/test_nn.py::TestNN::test_interpolate, test/test_nn.py::TestNN::test_interpolate_bicubic_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_2d_zero_dim, test/test_nn.py::TestNN::test_interpolate_bicubic_2d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_shared_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_shared_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_2d_zero_dim, test/test_nn.py::TestNN::test_interpolate_bilinear_2d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_shared_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_shared_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_tuple_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_tuple_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bilinear_tuple_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_tuple_2d_cuda, test/test_nn.py::TestNN::test_interpolate_buffer_overflow, test/test_nn.py::TestNN::test_interpolate_illegal_memory_access, test/test_nn.py::TestNN::test_interpolate_linear_1d, test/test_nn.py::TestNN::test_interpolate_linear_1d_align_corners, test/test_nn.py::TestNN::test_interpolate_linear_1d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_linear_1d_cuda, test/test_nn.py::TestNN::test_interpolate_linear_1d_zero_dim, test/test_nn.py::TestNN::test_interpolate_linear_1d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d_align_corners, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d_cuda, test/test_nn.py::TestNN::test_interpolate_linear_tuple_1d, test/test_nn.py::TestNN::test_interpolate_linear_tuple_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_1d, test/test_nn.py::TestNN::test_interpolate_nearest_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_1d_zero_dim, test/test_nn.py::TestNN::test_interpolate_nearest_1d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_2d, test/test_nn.py::TestNN::test_interpolate_nearest_2d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_2d_launch_configs, test/test_nn.py::TestNN::test_interpolate_nearest_2d_launch_configs_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_2d_zero_dim, test/test_nn.py::TestNN::test_interpolate_nearest_2d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_3d, test/test_nn.py::TestNN::test_interpolate_nearest_3d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_3d_zero_dim, test/test_nn.py::TestNN::test_interpolate_nearest_3d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_scale_1d, test/test_nn.py::TestNN::test_interpolate_nearest_scale_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_scale_2d, test/test_nn.py::TestNN::test_interpolate_nearest_scale_2d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_scale_3d, test/test_nn.py::TestNN::test_interpolate_nearest_scale_3d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_1d, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_2d, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_2d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_3d, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_3d_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_3d, test/test_nn.py::TestNN::test_interpolate_trilinear_3d_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_3d_zero_dim, test/test_nn.py::TestNN::test_interpolate_trilinear_3d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_scale_3d, test/test_nn.py::TestNN::test_interpolate_trilinear_scale_3d_align_corners, test/test_nn.py::TestNN::test_interpolate_trilinear_scale_3d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_scale_3d_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d_align_corners, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d_cuda, test/test_nn.py::TestNN::test_interpolate_undefined_behavior_casting, test/test_nn.py::TestNN::test_kl_div_log_softmax_target, test/test_nn.py::TestNN::test_kl_div_with_diff_type, test/test_nn.py::TestNN::test_kl_div_with_diff_type_log_target, test/test_nn.py::TestNN::test_l1_loss_correct, test/test_nn.py::TestNN::test_layer_norm_backwards_eps, test/test_nn.py::TestNN::test_layer_norm_eps, test/test_nn.py::TestNN::test_layer_norm_grads_with_create_graph_flag, test/test_nn.py::TestNN::test_layer_norm_large_tensor, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_bias_weightCOO, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_bias_weightCSC, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_bias_weightCSR, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_bias_weightStrided, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightCOO, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightCSC, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightCSR, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightStrided, test/test_nn.py::TestNN::test_linear_broadcasting, test/test_nn.py::TestNN::test_linear_raise_on_scalar_input, test/test_nn.py::TestNN::test_log_softmax_dim0, test/test_nn.py::TestNN::test_log_softmax_dim0_cuda, test/test_nn.py::TestNN::test_log_softmax_dim3, test/test_nn.py::TestNN::test_log_softmax_dim3_cuda, test/test_nn.py::TestNN::test_log_softmax_lastdim, test/test_nn.py::TestNN::test_log_softmax_lastdim_cuda, test/test_nn.py::TestNN::test_log_softmax_scalar, test/test_nn.py::TestNN::test_log_softmax_scalar_cuda, test/test_nn.py::TestNN::test_log_softmax_spatial, test/test_nn.py::TestNN::test_log_softmax_spatial_cuda, test/test_nn.py::TestNN::test_log_softmax_spatial_special, test/test_nn.py::TestNN::test_log_softmax_spatial_special_cuda, test/test_nn.py::TestNN::test_loss_equal_input_target_shape, test/test_nn.py::TestNN::test_margin_ranking_loss_margin_no_reduce, test/test_nn.py::TestNN::test_margin_ranking_loss_no_reduce, test/test_nn.py::TestNN::test_max_pool1d_invalid_output_size, test/test_nn.py::TestNN::test_module_apply_inplace_op, test/test_nn.py::TestNN::test_module_backcompat, test/test_nn.py::TestNN::test_module_super_init, test/test_nn.py::TestNN::test_module_to_argparse, test/test_nn.py::TestNN::test_modules, test/test_nn.py::TestNN::test_mse_loss_size_warning, test/test_nn.py::TestNN::test_multimarginloss_1d_input_0d_target_no_reduce, test/test_nn.py::TestNN::test_multimarginloss_1d_input_0d_target_no_reduce_cuda, test/test_nn.py::TestNN::test_named_children, test/test_nn.py::TestNN::test_named_modules, test/test_nn.py::TestNN::test_named_parameters_remove_duplicate, test/test_nn.py::TestNN::test_native_channel_shuffle_return_alias_of_self, test/test_nn.py::TestNN::test_nested_tensor_from_mask, test/test_nn.py::TestNN::test_nested_tensor_from_mask_error, test/test_nn.py::TestNN::test_no_grad, test/test_nn.py::TestNN::test_non_leaf_parameters, test/test_nn.py::TestNN::test_normalize, test/test_nn.py::TestNN::test_overwrite_module_params_on_conversion, test/test_nn.py::TestNN::test_pack_sequence_batch_sizes_throw, test/test_nn.py::TestNN::test_pad_scalar_error, test/test_nn.py::TestNN::test_padding_list, test/test_nn.py::TestNN::test_pairwise_distance, test/test_nn.py::TestNN::test_parameter_assignment, test/test_nn.py::TestNN::test_parameterlistdict_pickle, test/test_nn.py::TestNN::test_parameterlistdict_setting_attributes, test/test_nn.py::TestNN::test_parameters_and_named_parameters, test/test_nn.py::TestNN::test_parameters_to_vector, test/test_nn.py::TestNN::test_parse_to, test/test_nn.py::TestNN::test_partial_flat_weights, test/test_nn.py::TestNN::test_pdist, test/test_nn.py::TestNN::test_pdist_cpu_gradgrad_unimplemented, test/test_nn.py::TestNN::test_pdist_cuda_gradgrad_unimplemented, test/test_nn.py::TestNN::test_pdist_empty_col, test/test_nn.py::TestNN::test_pdist_empty_row, test/test_nn.py::TestNN::test_pdist_large, test/test_nn.py::TestNN::test_pdist_zeros, test/test_nn.py::TestNN::test_pickle_module_no_weights_only_warning, test/test_nn.py::TestNN::test_pixel_shuffle_nhwc_cpu, test/test_nn.py::TestNN::test_pixel_shuffle_unshuffle, test/test_nn.py::TestNN::test_pointwise_loss_broadcast, test/test_nn.py::TestNN::test_pointwise_loss_target_grad_none_reduction, test/test_nn.py::TestNN::test_projections_errors_on_gru_and_rnn, test/test_nn.py::TestNN::test_projections_lstm_args_check, test/test_nn.py::TestNN::test_projections_lstm_check_device, test/test_nn.py::TestNN::test_projections_lstm_initial_hidden_state, test/test_nn.py::TestNN::test_register_buffer_allows_overwriting_with_same_name, test/test_nn.py::TestNN::test_register_buffer_raises_error_if_attr_exists, test/test_nn.py::TestNN::test_register_buffer_raises_error_if_name_is_not_string, test/test_nn.py::TestNN::test_register_buffer_raises_error_if_not_tensor, test/test_nn.py::TestNN::test_register_parameter_allows_overwriting_with_same_name, test/test_nn.py::TestNN::test_register_parameter_raises_error_if_attr_exists, test/test_nn.py::TestNN::test_register_parameter_raises_error_if_name_is_not_string, test/test_nn.py::TestNN::test_relu_inplace_on_view, test/test_nn.py::TestNN::test_repr, test/test_nn.py::TestNN::test_requires_grad_, test/test_nn.py::TestNN::test_rnn_args_check, test/test_nn.py::TestNN::test_rnn_check_device, test/test_nn.py::TestNN::test_rnn_initial_hidden_state, test/test_nn.py::TestNN::test_rnn_weight_norm, test/test_nn.py::TestNN::test_set_submodule, test/test_nn.py::TestNN::test_share_memory, test/test_nn.py::TestNN::test_smoothl1loss_intergral_target, test/test_nn.py::TestNN::test_smoothl1loss_negative_beta_not_supported, test/test_nn.py::TestNN::test_softmax_functional_dim0, test/test_nn.py::TestNN::test_softmax_functional_dim0_cuda, test/test_nn.py::TestNN::test_softmax_functional_dim3, test/test_nn.py::TestNN::test_softmax_functional_dim3_cuda, test/test_nn.py::TestNN::test_softmax_functional_scalar, test/test_nn.py::TestNN::test_softmax_functional_scalar_cuda, test/test_nn.py::TestNN::test_softmax_lastdim, test/test_nn.py::TestNN::test_softmax_lastdim_cuda, test/test_nn.py::TestNN::test_softmax_lastdim_dtype, test/test_nn.py::TestNN::test_softmax_lastdim_dtype_cuda, test/test_nn.py::TestNN::test_softmax_spatial, test/test_nn.py::TestNN::test_softmax_spatial_cuda, test/test_nn.py::TestNN::test_softmax_spatial_dtype, test/test_nn.py::TestNN::test_softmax_spatial_dtype_cuda, test/test_nn.py::TestNN::test_softmax_spatial_special, test/test_nn.py::TestNN::test_softmax_spatial_special_cuda, test/test_nn.py::TestNN::test_softmin, test/test_nn.py::TestNN::test_spectral_norm, test/test_nn.py::TestNN::test_spectral_norm_dim, test/test_nn.py::TestNN::test_spectral_norm_forward, test/test_nn.py::TestNN::test_spectral_norm_load_state_dict, test/test_nn.py::TestNN::test_spectral_norm_pickle, test/test_nn.py::TestNN::test_state_dict, test/test_nn.py::TestNN::test_swap_module_params_poisons_acc_grad, test/test_nn.py::TestNN::test_sync_batchnorm_accuracy_cuda, test/test_nn.py::TestNN::test_sync_batchnorm_backward_elemt, test/test_nn.py::TestNN::test_threshold_bfloat16_half, test/test_nn.py::TestNN::test_threshold_int, test/test_nn.py::TestNN::test_to, test/test_nn.py::TestNN::test_train_errors_for_invalid_mode, test/test_nn.py::TestNN::test_transformer_args_check, test/test_nn.py::TestNN::test_transformer_layer_args_check, test/test_nn.py::TestNN::test_transformerdecoder, test/test_nn.py::TestNN::test_transformerdecoderlayer, test/test_nn.py::TestNN::test_transformerdecoderlayer_gelu, test/test_nn.py::TestNN::test_triplet_margin_loss, test/test_nn.py::TestNN::test_triplet_margin_loss_no_reduce, test/test_nn.py::TestNN::test_triplet_margin_loss_swap, test/test_nn.py::TestNN::test_triplet_margin_loss_swap_no_reduce, test/test_nn.py::TestNN::test_type, test/test_nn.py::TestNN::test_unflatten, test/test_nn.py::TestNN::test_unflatten_invalid_arg, test/test_nn.py::TestNN::test_unfold_invalid_arg, test/test_nn.py::TestNN::test_upsamplingBilinear2d_spatial_invariance, test/test_nn.py::TestNN::test_upsamplingLinear1d, test/test_nn.py::TestNN::test_upsamplingLinear1d_spatial_invariance, test/test_nn.py::TestNN::test_upsamplingTrilinear3d_spatial_invariance, test/test_nn.py::TestNN::test_upsampling_bfloat16, test/test_nn.py::TestNN::test_upsampling_not_recompute_scale_factor, test/test_nn.py::TestNN::test_upsampling_small_scale, test/test_nn.py::TestNN::test_vector_to_parameters, test/test_nn.py::TestNN::test_weight_norm, test/test_nn.py::TestNN::test_weight_norm_pickle, test/test_nn.py::TestNN::test_weighted_huber_loss, test/test_nn.py::TestNN::test_weighted_l1_loss_with_weights, test/test_nn.py::TestNN::test_weighted_mse_loss, test/test_nn.py::TestNN::test_zero_grad, test/test_nn.py::TestFusionEval::test_fuse_module_eval_numerics, test/test_nn.py::TestConstantPadNd::test_constant_pad_nd, test/test_nn.py::TestConstantPadNd::test_preserves_memory_format, test/test_nn.py::TestAddRelu::test_add_relu, test/test_nn.py::TestAddRelu::test_add_relu_broadcasting, test/test_nn.py::TestFunctionalPickle::test_pickle_softsign, test/test_nn.py::TestFusionUtils::test_fuse_conv_bn_requires_grad, test/test_nn.py::TestFusionUtils::test_fuse_linear_bn_requires_grad, test/test_nn.py::TestUtils::test_consume_prefix_in_state_dict_if_present, test/test_nn.py::TestNNDeviceTypeCPU::test_BatchNorm_empty_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_Bilinear_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_cudnn_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_empty_target_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_mean_use_module_form_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_mean_use_module_form_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_none_use_module_form_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_none_use_module_form_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_sum_use_module_form_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_sum_use_module_form_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GRU_grad_and_gradgrad_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_memory_format_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_numeric_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_raises_error_if_one_value_per_group_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_InstanceNorm1d_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_InstanceNorm2d_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_InstanceNorm3d_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_LSTM_differentiable_backward_using_oneDNN_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_LSTM_differentiable_backward_using_oneDNN_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_LSTM_grad_and_gradgrad_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_LayerNorm_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_LayerNorm_numeric_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_LocalResponseNorm_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_empty_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_empty_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_warnings_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad2d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad2d_large_deterministic_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad3d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad_empty_cpu_complex64, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad_empty_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad_fails_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad1d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad2d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad3d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad_empty_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad_empty_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_TransformerDecoderLayer_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_TransformerDecoder_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_TransformerEncoderLayer_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_TransformerEncoder_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_Transformer_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_Unfold_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_activations_bfloat16_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_activations_bfloat16_half_cpu_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_activations_bfloat16_half_cpu_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_adaptiveavg_pool1d_shmem_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_2d_rotate0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_2d_rotate45_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_2d_rotate90_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_2d_rotateRandom_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_3d_rotateRandom_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_avg_pool_large_tensor2_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_avg_pool_large_tensor_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_affine_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_affine_mixed_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_affine_mixed_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_eval_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_eval_mixed_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_eval_mixed_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_grad_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_large_batch_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_large_batch_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_simple_average_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_simple_average_mixed_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_simple_average_mixed_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_update_stats_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_channel_shuffle_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_error_if_nonfinite_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_0_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_1_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_2_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_4_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_inf_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_0_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_1_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_2_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_4_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_inf_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_multi_device_foreach_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_multi_device_foreach_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_value_foreach_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_value_foreach_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_64bit_reduction_mean_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_64bit_reduction_none_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_64bit_reduction_sum_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_consistent_index_target_and_probs_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_errors_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_weight_ignore_indices_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_with_probs_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_large_tensor_reduction_mean_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_large_tensor_reduction_none_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_large_tensor_reduction_sum_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_2d_out_of_bounds_class_index_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_2d_out_of_bounds_class_index_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_index_target_unit_weights_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_one_hot_target_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_all_reductions_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_mean_weighted_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_mean_weighted_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_none_weighted_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_none_weighted_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_sum_weighted_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_sum_weighted_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_unit_weights_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cudnn_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cudnn_tensor_cpu_length_cuda_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cudnn_tensor_cuda_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_error_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_device_mask_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_elu_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_elu_inplace_with_neg_alpha_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_fold_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_glu_bfloat16_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_bfloat16_precision_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_half_precision_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_index_2d_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_index_2d_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_index_3d_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_index_3d_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_nan_inf_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_nan_inf_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_gumbel_softmax_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_gumbel_softmax_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_hardsigmoid_grad_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_grad_corner_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_grad_corner_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_grad_corner_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_grad_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_for_single_spatial_element_during_training_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_False_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_False_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_True_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_True_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_False_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_False_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_True_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_True_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_False_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_False_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_True_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_True_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_less_than_one_value_per_channel_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_invalid_reduction_strings_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_layernorm_half_precision_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_layernorm_weight_bias_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_leaky_relu_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_leaky_relu_inplace_with_neg_slope_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_leaky_relu_inplace_with_zero_slope_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_linear_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_log_softmax_big_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_log_softmax_cpu_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_log_softmax_cpu_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_logsigmoid_out_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_lstmcell_backward_only_one_output_grad_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_TxT_layout_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_devices_parity_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_forward_with_nans_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_grad_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_lowp_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_lowp_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_mask_types_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_transformer_layout_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_mish_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_module_to_empty_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_module_to_empty_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_module_to_empty_non_recursive_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_mse_loss_error_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_all_ignored_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_byte_target_matches_long_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_empty_tensor_reduction_mean_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_empty_tensor_reduction_none_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_empty_tensor_reduction_sum_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_invalid_target_dim_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_invalid_weights_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_large_tensor_reduction_mean_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_large_tensor_reduction_none_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_large_tensor_reduction_sum_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_mismatched_batch_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_out_of_bounds_ignore_index_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_total_weight_is_zero_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nn_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nn_scalars_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nn_scalars_reductions_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nonlinearity_propagate_nan_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_one_hot_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_overwrite_module_params_on_conversion_cpu_device_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_pad_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_pad_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_prelu_backward_32bit_indexing_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_replicatepad_64bit_indexing_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_numeric_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_numeric_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_rnn_fused_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_rnn_fused_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_rnn_retain_variables_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_save_lstm_compatibility_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_silu_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_skip_init_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_smooth_l1_loss_bfloat16_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_smooth_l1_loss_vs_huber_loss_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_smoothl1loss_backward_zero_beta_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_64bit_indexing_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_64bit_indexing_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_smem_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_unaligned_grad_output_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_unaligned_output_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_without_fully_vectorized_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_bfloat16_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_double_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_forward_64bit_indexing_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_results_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_softplus_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softplus_low_threshold_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softshrink_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softshrink_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softshrink_negative_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_threshold_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_to_complex_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_to_complex_cpu_complex64, test/test_nn.py::TestNNDeviceTypeCPU::test_to_complex_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_transformerencoderlayer_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_transformerencoderlayer_fast_path_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_transformerencoderlayer_gelu_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_triplet_margin_with_distance_loss_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_triplet_margin_with_distance_loss_default_parity_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_False_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_False_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_True_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_True_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_False_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_False_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_True_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_True_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bicubic_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bilinear_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bicubic_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bilinear_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bicubic_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bilinear_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bicubic_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bilinear_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBicubic2d_aa_correctness_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBicubic2d_aa_correctness_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBicubic2d_correctness_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBilinear2d_aa_correctness_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBilinear2d_aa_correctness_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_correctness_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_correctness_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_launch_config_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_correctness_memory_format1_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_launch_config_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_launch_fail_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_launch_rocm_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_memory_format0_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_memory_format0_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_memory_format1_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_memory_format1_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format1_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_launch_config_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_memory_format0_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_memory_format0_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_memory_format1_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_memory_format1_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact1d_correctness_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact1d_correctness_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact1d_rescale_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format1_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format1_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingTrilinear3d_align_corners_False_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingTrilinear3d_align_corners_False_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingTrilinear3d_align_corners_True_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingTrilinear3d_align_corners_True_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsampling_64bit_indexing_channels_last_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsampling_64bit_indexing_channels_last_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingnearest2d_backward_64bit_indexing_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_variable_sequence_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_warp_softmax_64bit_indexing_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_warp_softmax_64bit_indexing_cpu_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_BatchNorm_empty_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_Bilinear_empty_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_CTCLoss_cudnn_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_CTCLoss_empty_target_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_CTCLoss_no_batch_dim_reduction_mean_use_module_form_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_CTCLoss_no_batch_dim_reduction_mean_use_module_form_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_CTCLoss_no_batch_dim_reduction_none_use_module_form_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_CTCLoss_no_batch_dim_reduction_none_use_module_form_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_CTCLoss_no_batch_dim_reduction_sum_use_module_form_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_CTCLoss_no_batch_dim_reduction_sum_use_module_form_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_GRU_grad_and_gradgrad_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_GroupNorm_empty_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_GroupNorm_general_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_GroupNorm_memory_format_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_GroupNorm_numeric_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_GroupNorm_raises_error_if_one_value_per_group_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_InstanceNorm1d_general_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_InstanceNorm2d_general_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_InstanceNorm3d_general_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_LSTM_differentiable_backward_using_oneDNN_mps_bfloat16, test/test_nn.py::TestNNDeviceTypeMPS::test_LSTM_differentiable_backward_using_oneDNN_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_LSTM_grad_and_gradgrad_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_LayerNorm_general_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_LayerNorm_numeric_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_LocalResponseNorm_empty_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_MarginLoss_empty_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_MarginLoss_empty_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_MarginLoss_warnings_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_ReflectionPad2d_large_deterministic_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_ReflectionPad2d_large_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_ReflectionPad3d_large_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_ReflectionPad_empty_mps_complex64, test/test_nn.py::TestNNDeviceTypeMPS::test_ReflectionPad_empty_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_ReflectionPad_fails_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_ReplicationPad1d_large_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_ReplicationPad2d_large_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_ReplicationPad3d_large_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_ReplicationPad_empty_mps_complex128, test/test_nn.py::TestNNDeviceTypeMPS::test_ReplicationPad_empty_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_TransformerDecoderLayer_empty_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_TransformerDecoder_empty_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_TransformerEncoderLayer_empty_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_TransformerEncoder_empty_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_Transformer_empty_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_Unfold_empty_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_activations_bfloat16_half_cpu_mps_bfloat16, test/test_nn.py::TestNNDeviceTypeMPS::test_activations_bfloat16_half_cpu_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_activations_bfloat16_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_adaptiveavg_pool1d_shmem_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_affine_2d_rotate0_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_affine_2d_rotate45_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_affine_2d_rotate90_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_affine_2d_rotateRandom_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_affine_3d_rotateRandom_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_avg_pool_large_tensor2_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_avg_pool_large_tensor_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_batchnorm_affine_mixed_mps_bfloat16, test/test_nn.py::TestNNDeviceTypeMPS::test_batchnorm_affine_mixed_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_batchnorm_affine_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_batchnorm_eval_mixed_mps_bfloat16, test/test_nn.py::TestNNDeviceTypeMPS::test_batchnorm_eval_mixed_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_batchnorm_eval_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_batchnorm_grad_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_batchnorm_large_batch_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_batchnorm_large_batch_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_batchnorm_simple_average_mixed_mps_bfloat16, test/test_nn.py::TestNNDeviceTypeMPS::test_batchnorm_simple_average_mixed_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_batchnorm_simple_average_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_batchnorm_update_stats_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_channel_shuffle_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_norm_error_if_nonfinite_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_norm_foreach_False_norm_type_0_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_norm_foreach_False_norm_type_1_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_norm_foreach_False_norm_type_2_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_norm_foreach_False_norm_type_4_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_norm_foreach_False_norm_type_inf_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_norm_foreach_True_norm_type_0_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_norm_foreach_True_norm_type_1_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_norm_foreach_True_norm_type_2_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_norm_foreach_True_norm_type_4_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_norm_foreach_True_norm_type_inf_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_norm_multi_device_foreach_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_norm_multi_device_foreach_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_value_foreach_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_clip_grad_value_foreach_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_conv_empty_input_mps_complex64, test/test_nn.py::TestNNDeviceTypeMPS::test_conv_empty_input_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_conv_empty_input_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_64bit_reduction_mean_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_64bit_reduction_none_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_64bit_reduction_sum_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_label_smoothing_consistent_index_target_and_probs_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_label_smoothing_errors_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_label_smoothing_weight_ignore_indices_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_label_smoothing_with_probs_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_large_tensor_reduction_mean_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_large_tensor_reduction_none_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_large_tensor_reduction_sum_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_loss_2d_out_of_bounds_class_index_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_loss_2d_out_of_bounds_class_index_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_loss_index_target_unit_weights_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_loss_one_hot_target_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_loss_prob_target_all_reductions_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_mean_weighted_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_mean_weighted_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_none_weighted_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_none_weighted_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_sum_weighted_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_sum_weighted_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_cross_entropy_loss_prob_target_unit_weights_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_ctc_loss_cudnn_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_ctc_loss_cudnn_tensor_cpu_length_cuda_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_ctc_loss_cudnn_tensor_cuda_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_ctc_loss_error_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_ctc_loss_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_device_mask_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_elu_inplace_overlap_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_elu_inplace_with_neg_alpha_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_fold_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_glu_bfloat16_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_grid_sample_bfloat16_precision_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_grid_sample_half_precision_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_grid_sample_large_index_2d_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_grid_sample_large_index_2d_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_grid_sample_large_index_3d_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_grid_sample_large_index_3d_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_grid_sample_large_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_grid_sample_nan_inf_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_grid_sample_nan_inf_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_groupnorm_nhwc_mps_bfloat16, test/test_nn.py::TestNNDeviceTypeMPS::test_groupnorm_nhwc_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_groupnorm_nhwc_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_groupnorm_nhwc_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_gumbel_softmax_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_hardsigmoid_grad_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_hardswish_grad_corner_mps_bfloat16, test/test_nn.py::TestNNDeviceTypeMPS::test_hardswish_grad_corner_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_hardswish_grad_corner_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_hardswish_grad_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_hardswish_inplace_overlap_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_for_single_spatial_element_during_training_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_False_affine_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_False_affine_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_True_affine_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_True_affine_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_False_affine_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_False_affine_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_True_affine_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_True_affine_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_False_affine_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_False_affine_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_True_affine_False_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_True_affine_True_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_instancenorm_raises_error_if_less_than_one_value_per_channel_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_invalid_reduction_strings_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_layernorm_half_precision_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_layernorm_weight_bias_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_leaky_relu_inplace_overlap_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_leaky_relu_inplace_with_neg_slope_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_leaky_relu_inplace_with_zero_slope_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_linear_empty_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_log_softmax_big_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_log_softmax_cpu_mps_bfloat16, test/test_nn.py::TestNNDeviceTypeMPS::test_log_softmax_cpu_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_logsigmoid_out_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_lstmcell_backward_only_one_output_grad_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_masked_softmax_TxT_layout_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_masked_softmax_devices_parity_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_masked_softmax_forward_with_nans_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_masked_softmax_grad_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_masked_softmax_lowp_mps_bfloat16, test/test_nn.py::TestNNDeviceTypeMPS::test_masked_softmax_lowp_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_masked_softmax_mask_types_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_masked_softmax_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_masked_softmax_transformer_layout_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_mish_inplace_overlap_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_module_to_empty_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_module_to_empty_non_recursive_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_mse_loss_error_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_all_ignored_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_byte_target_matches_long_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_empty_tensor_reduction_mean_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_empty_tensor_reduction_mean_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_empty_tensor_reduction_none_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_empty_tensor_reduction_none_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_empty_tensor_reduction_sum_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_empty_tensor_reduction_sum_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_invalid_target_dim_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_invalid_weights_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_large_tensor_reduction_mean_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_large_tensor_reduction_none_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_large_tensor_reduction_sum_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_mismatched_batch_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_out_of_bounds_ignore_index_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nll_loss_total_weight_is_zero_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nn_empty_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nn_scalars_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nn_scalars_reductions_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_nonlinearity_propagate_nan_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_one_hot_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_overwrite_module_params_on_conversion_cpu_device_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_pad_mps_complex128, test/test_nn.py::TestNNDeviceTypeMPS::test_pad_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_prelu_backward_32bit_indexing_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_replicatepad_64bit_indexing_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_rmsnorm_numeric_mps_bfloat16, test/test_nn.py::TestNNDeviceTypeMPS::test_rmsnorm_numeric_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_rnn_fused_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_rnn_fused_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_rnn_retain_variables_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_rnn_retain_variables_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_save_lstm_compatibility_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_silu_inplace_overlap_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_skip_init_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_smooth_l1_loss_bfloat16_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_smooth_l1_loss_vs_huber_loss_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_smoothl1loss_backward_zero_beta_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_64bit_indexing_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_backward_64bit_indexing_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_backward_smem_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_backward_unaligned_grad_output_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_backward_unaligned_output_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_backward_without_fully_vectorized_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_bfloat16_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_cpu_mps_bfloat16, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_cpu_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_double_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_forward_64bit_indexing_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_mps_float16, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_softmax_results_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_softplus_inplace_overlap_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_softplus_low_threshold_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_softshrink_inplace_overlap_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_softshrink_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_softshrink_negative_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_threshold_inplace_overlap_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_to_complex_mps_complex64, test/test_nn.py::TestNNDeviceTypeMPS::test_to_complex_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_transformerencoderlayer_fast_path_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_transformerencoderlayer_gelu_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_transformerencoderlayer_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_triplet_margin_with_distance_loss_default_parity_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_triplet_margin_with_distance_loss_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_False_input_size_399_output_size_437_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_False_input_size_403_output_size_377_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_True_input_size_399_output_size_437_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_True_input_size_403_output_size_377_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_False_input_size_399_output_size_437_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_False_input_size_403_output_size_377_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_True_input_size_399_output_size_437_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_True_input_size_403_output_size_377_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bicubic_memory_format0_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bicubic_memory_format1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bilinear_memory_format0_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bilinear_memory_format1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bicubic_memory_format0_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bicubic_memory_format1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bilinear_memory_format0_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bilinear_memory_format1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bicubic_memory_format0_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bicubic_memory_format1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bilinear_memory_format0_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bilinear_memory_format1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bicubic_memory_format0_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bicubic_memory_format1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bilinear_memory_format0_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bilinear_memory_format1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_float32_mps_float32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_float64_mps_float64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int16_mps_int16, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int32_mps_int32, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int64_mps_int64, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int8_mps_int8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_uint8_mps_uint8, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBicubic2d_aa_correctness_memory_format0_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBicubic2d_aa_correctness_memory_format1_mps, test/test_nn.py::TestNNDeviceTypeMPS::test_upsamplingBicubic2d_correctness_mps, 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2025-07-17T06:49:24.4373450Z 
2025-07-17T06:49:24.4373590Z Running test_spectral_ops 1/1 ... [2025-07-17 06:49:24.203273]
2025-07-17T06:49:24.4373850Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:49:24.4374560Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_spectral_ops.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:49:24.203602]
2025-07-17T06:49:31.1643070Z 
2025-07-17T06:49:31.1643600Z test_spectral_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_spectral_ops_1.1_2cc0ce6f70f19fec_.log
2025-07-17T06:49:31.1702360Z Running 281 items in this shard: test/test_spectral_ops.py::TestFFTCPU::test_batch_istft_cpu, test/test_spectral_ops.py::TestFFTCPU::test_complex_istft_real_equiv_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_definition_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_onesided_cpu, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_real_equiv_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_roundtrip_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_roundtrip_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_cufft_context_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_cufft_context_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_cufft_plan_cache_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fft2_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fft2_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfft2_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfft2_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_ifft2_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_ifft2_cpu_float32, 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2025-07-17T06:49:31.1754800Z 
2025-07-17T06:49:31.1754970Z Running distributions/test_distributions 1/1 ... [2025-07-17 06:49:31.164867]
2025-07-17T06:49:31.1755260Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:49:31.1756010Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'distributions/test_distributions.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:49:31.165136]
2025-07-17T06:49:52.9200240Z 
2025-07-17T06:49:52.9200920Z distributions/test_distributions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/distributions.test_distributions_1.1_855e47dc8d1caaf3_.log
2025-07-17T06:49:52.9259660Z Running 230 items in this shard: test/distributions/test_distributions.py::TestDistributions::test_argmax_relaxed_categorical, test/distributions/test_distributions.py::TestDistributions::test_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_bernoulli_3d, test/distributions/test_distributions.py::TestDistributions::test_bernoulli_enumerate_support, test/distributions/test_distributions.py::TestDistributions::test_beta_log_prob, test/distributions/test_distributions.py::TestDistributions::test_beta_sample, test/distributions/test_distributions.py::TestDistributions::test_beta_shape, test/distributions/test_distributions.py::TestDistributions::test_beta_underflow, test/distributions/test_distributions.py::TestDistributions::test_beta_underflow_gpu, test/distributions/test_distributions.py::TestDistributions::test_binomial, test/distributions/test_distributions.py::TestDistributions::test_binomial_bfloat16, test/distributions/test_distributions.py::TestDistributions::test_binomial_enumerate_support, test/distributions/test_distributions.py::TestDistributions::test_binomial_extreme_vals, test/distributions/test_distributions.py::TestDistributions::test_binomial_half, test/distributions/test_distributions.py::TestDistributions::test_binomial_log_prob_and_entropy, test/distributions/test_distributions.py::TestDistributions::test_binomial_log_prob_vectorized_count, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_stable, test/distributions/test_distributions.py::TestDistributions::test_binomial_vectorized_count, test/distributions/test_distributions.py::TestDistributions::test_categorical_1d, test/distributions/test_distributions.py::TestDistributions::test_categorical_2d, test/distributions/test_distributions.py::TestDistributions::test_categorical_enumerate_support, test/distributions/test_distributions.py::TestDistributions::test_cauchy, test/distributions/test_distributions.py::TestDistributions::test_cdf_icdf_inverse, test/distributions/test_distributions.py::TestDistributions::test_cdf_log_prob, test/distributions/test_distributions.py::TestDistributions::test_chi2_sample, test/distributions/test_distributions.py::TestDistributions::test_chi2_shape, test/distributions/test_distributions.py::TestDistributions::test_continuous_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_continuous_bernoulli_3d, test/distributions/test_distributions.py::TestDistributions::test_dirichlet_log_prob, test/distributions/test_distributions.py::TestDistributions::test_dirichlet_log_prob_zero, test/distributions/test_distributions.py::TestDistributions::test_dirichlet_mode, test/distributions/test_distributions.py::TestDistributions::test_dirichlet_sample, test/distributions/test_distributions.py::TestDistributions::test_dirichlet_shape, test/distributions/test_distributions.py::TestDistributions::test_distribution_expand, test/distributions/test_distributions.py::TestDistributions::test_distribution_subclass_expand, test/distributions/test_distributions.py::TestDistributions::test_enumerate_support_type, test/distributions/test_distributions.py::TestDistributions::test_exponential, test/distributions/test_distributions.py::TestDistributions::test_exponential_sample, test/distributions/test_distributions.py::TestDistributions::test_fishersnedecor, test/distributions/test_distributions.py::TestDistributions::test_fishersnedecor_sample, test/distributions/test_distributions.py::TestDistributions::test_gamma_gpu_sample, test/distributions/test_distributions.py::TestDistributions::test_gamma_gpu_shape, test/distributions/test_distributions.py::TestDistributions::test_gamma_log_prob_at_boundary, test/distributions/test_distributions.py::TestDistributions::test_gamma_sample, 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test/distributions/test_distributions.py::TestDistributions::test_lkj_cholesky_log_prob, test/distributions/test_distributions.py::TestDistributions::test_logisticnormal, test/distributions/test_distributions.py::TestDistributions::test_logisticnormal_logprob, test/distributions/test_distributions.py::TestDistributions::test_logisticnormal_sample, test/distributions/test_distributions.py::TestDistributions::test_lognormal, test/distributions/test_distributions.py::TestDistributions::test_lognormal_logprob, test/distributions/test_distributions.py::TestDistributions::test_lognormal_sample, test/distributions/test_distributions.py::TestDistributions::test_lowrank_multivariate_normal_log_prob, test/distributions/test_distributions.py::TestDistributions::test_lowrank_multivariate_normal_moments, test/distributions/test_distributions.py::TestDistributions::test_lowrank_multivariate_normal_properties, test/distributions/test_distributions.py::TestDistributions::test_lowrank_multivariate_normal_sample, test/distributions/test_distributions.py::TestDistributions::test_lowrank_multivariate_normal_shape, test/distributions/test_distributions.py::TestDistributions::test_mixture_same_family_binomial_log_prob, test/distributions/test_distributions.py::TestDistributions::test_mixture_same_family_normal_log_prob, test/distributions/test_distributions.py::TestDistributions::test_mixture_same_family_sample, test/distributions/test_distributions.py::TestDistributions::test_mixture_same_family_shape, test/distributions/test_distributions.py::TestDistributions::test_mode, test/distributions/test_distributions.py::TestDistributions::test_multinomial_1d, test/distributions/test_distributions.py::TestDistributions::test_multinomial_1d_log_prob_and_entropy, test/distributions/test_distributions.py::TestDistributions::test_multinomial_2d, test/distributions/test_distributions.py::TestDistributions::test_multinomial_sequential_draw, test/distributions/test_distributions.py::TestDistributions::test_multivariate_normal_log_prob, test/distributions/test_distributions.py::TestDistributions::test_multivariate_normal_moments, test/distributions/test_distributions.py::TestDistributions::test_multivariate_normal_properties, test/distributions/test_distributions.py::TestDistributions::test_multivariate_normal_sample, test/distributions/test_distributions.py::TestDistributions::test_multivariate_normal_shape, test/distributions/test_distributions.py::TestDistributions::test_multivariate_normal_stable_with_precision_matrix, test/distributions/test_distributions.py::TestDistributions::test_negative_binomial, test/distributions/test_distributions.py::TestDistributions::test_negative_binomial_log_prob, test/distributions/test_distributions.py::TestDistributions::test_negative_binomial_log_prob_vectorized_count, test/distributions/test_distributions.py::TestDistributions::test_normal, test/distributions/test_distributions.py::TestDistributions::test_normal_sample, test/distributions/test_distributions.py::TestDistributions::test_one_hot_categorical_1d, test/distributions/test_distributions.py::TestDistributions::test_one_hot_categorical_2d, test/distributions/test_distributions.py::TestDistributions::test_one_hot_categorical_enumerate_support, test/distributions/test_distributions.py::TestDistributions::test_pareto, test/distributions/test_distributions.py::TestDistributions::test_pareto_sample, test/distributions/test_distributions.py::TestDistributions::test_poisson_forward_ad, test/distributions/test_distributions.py::TestDistributions::test_poisson_gpu_sample, test/distributions/test_distributions.py::TestDistributions::test_poisson_log_prob, test/distributions/test_distributions.py::TestDistributions::test_poisson_sample, test/distributions/test_distributions.py::TestDistributions::test_poisson_shape, test/distributions/test_distributions.py::TestDistributions::test_relaxed_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_relaxed_one_hot_categorical_1d, test/distributions/test_distributions.py::TestDistributions::test_relaxed_one_hot_categorical_2d, test/distributions/test_distributions.py::TestDistributions::test_repr, test/distributions/test_distributions.py::TestDistributions::test_rounded_relaxed_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_rsample_requires_grad, test/distributions/test_distributions.py::TestDistributions::test_sample_detached, test/distributions/test_distributions.py::TestDistributions::test_studentT, test/distributions/test_distributions.py::TestDistributions::test_studentT_log_prob, test/distributions/test_distributions.py::TestDistributions::test_studentT_sample, test/distributions/test_distributions.py::TestDistributions::test_support_attributes, test/distributions/test_distributions.py::TestDistributions::test_torch_binomial_dtype_errors, test/distributions/test_distributions.py::TestDistributions::test_uniform, test/distributions/test_distributions.py::TestDistributions::test_valid_parameter_broadcasting, test/distributions/test_distributions.py::TestDistributions::test_vonmises_logprob, test/distributions/test_distributions.py::TestDistributions::test_vonmises_sample, test/distributions/test_distributions.py::TestDistributions::test_wishart_log_prob, test/distributions/test_distributions.py::TestDistributions::test_wishart_moments, test/distributions/test_distributions.py::TestDistributions::test_wishart_properties, test/distributions/test_distributions.py::TestDistributions::test_wishart_sample, test/distributions/test_distributions.py::TestDistributions::test_wishart_shape, test/distributions/test_distributions.py::TestDistributions::test_wishart_stable_with_precision_matrix, test/distributions/test_distributions.py::TestDistributions::test_zero_excluded_binomial, test/distributions/test_distributions.py::TestRsample::test_beta_wrt_alpha, test/distributions/test_distributions.py::TestRsample::test_beta_wrt_beta, test/distributions/test_distributions.py::TestRsample::test_chi2, test/distributions/test_distributions.py::TestRsample::test_dirichlet_multivariate, test/distributions/test_distributions.py::TestRsample::test_dirichlet_on_diagonal, test/distributions/test_distributions.py::TestRsample::test_dirichlet_tangent_field, test/distributions/test_distributions.py::TestRsample::test_gamma, test/distributions/test_distributions.py::TestDistributionShapes::test_bernoulli_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_bernoulli_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_beta_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_beta_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_binomial_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_binomial_shape_vectorized_n, test/distributions/test_distributions.py::TestDistributionShapes::test_categorical_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_cauchy_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_cauchy_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_chi2_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_chi2_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_continuous_bernoulli_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_continuous_bernoulli_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_dirichlet_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_entropy_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_exponential_shape_scalar_param, test/distributions/test_distributions.py::TestDistributionShapes::test_exponential_shape_tensor_param, test/distributions/test_distributions.py::TestDistributionShapes::test_gamma_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_gamma_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_geometric_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_geometric_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_gumbel_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_halfcauchy_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_halfcauchy_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_kumaraswamy_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_laplace_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_laplace_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_mixture_same_family_mean_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_mixture_same_family_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_multinomial_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_normal_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_normal_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_one_hot_categorical_shape, test/distributions/test_distributions.py::TestDistributionShapes::test_pareto_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_studentT_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_studentT_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_uniform_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_uniform_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_vonmises_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_vonmises_shape_tensor_params, test/distributions/test_distributions.py::TestDistributionShapes::test_weibull_scale_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_wishart_shape_scalar_params, test/distributions/test_distributions.py::TestDistributionShapes::test_wishart_shape_tensor_params, test/distributions/test_distributions.py::TestKL::test_entropy_exponential_family, test/distributions/test_distributions.py::TestKL::test_entropy_monte_carlo, test/distributions/test_distributions.py::TestKL::test_kl_edgecases, test/distributions/test_distributions.py::TestKL::test_kl_exponential_family, test/distributions/test_distributions.py::TestKL::test_kl_infinite, test/distributions/test_distributions.py::TestKL::test_kl_lowrank_multivariate_normal, test/distributions/test_distributions.py::TestKL::test_kl_lowrank_multivariate_normal_batched, test/distributions/test_distributions.py::TestKL::test_kl_monte_carlo, test/distributions/test_distributions.py::TestKL::test_kl_multivariate_normal, test/distributions/test_distributions.py::TestKL::test_kl_multivariate_normal_batched, test/distributions/test_distributions.py::TestKL::test_kl_multivariate_normal_batched_broadcasted, test/distributions/test_distributions.py::TestKL::test_kl_shape, test/distributions/test_distributions.py::TestKL::test_kl_transformed, test/distributions/test_distributions.py::TestConstraints::test_params_constraints, test/distributions/test_distributions.py::TestConstraints::test_support_constraints, test/distributions/test_distributions.py::TestNumericalStability::test_bernoulli_gradient, test/distributions/test_distributions.py::TestNumericalStability::test_bernoulli_with_logits_overflow, test/distributions/test_distributions.py::TestNumericalStability::test_bernoulli_with_logits_underflow, test/distributions/test_distributions.py::TestNumericalStability::test_categorical_log_prob, test/distributions/test_distributions.py::TestNumericalStability::test_categorical_log_prob_with_logits, test/distributions/test_distributions.py::TestNumericalStability::test_continuous_bernoulli_gradient, test/distributions/test_distributions.py::TestNumericalStability::test_continuous_bernoulli_with_logits_overflow, test/distributions/test_distributions.py::TestNumericalStability::test_continuous_bernoulli_with_logits_underflow, test/distributions/test_distributions.py::TestNumericalStability::test_multinomial_log_prob, test/distributions/test_distributions.py::TestNumericalStability::test_multinomial_log_prob_with_logits, test/distributions/test_distributions.py::TestLazyLogitsInitialization::test_lazy_logits_initialization, test/distributions/test_distributions.py::TestLazyLogitsInitialization::test_lazy_probs_initialization, test/distributions/test_distributions.py::TestAgainstScipy::test_cdf, test/distributions/test_distributions.py::TestAgainstScipy::test_icdf, test/distributions/test_distributions.py::TestAgainstScipy::test_mean, test/distributions/test_distributions.py::TestAgainstScipy::test_variance_stddev, test/distributions/test_distributions.py::TestFunctors::test_cat_event_dim, test/distributions/test_distributions.py::TestFunctors::test_cat_transform, test/distributions/test_distributions.py::TestFunctors::test_cat_transform_non_uniform, test/distributions/test_distributions.py::TestFunctors::test_stack_transform, test/distributions/test_distributions.py::TestValidation::test_invalid, test/distributions/test_distributions.py::TestValidation::test_invalid_log_probs_arg, test/distributions/test_distributions.py::TestValidation::test_valid, test/distributions/test_distributions.py::TestValidation::test_warning_unimplemented_constraints, test/distributions/test_distributions.py::TestJit::test_cdf, test/distributions/test_distributions.py::TestJit::test_entropy, test/distributions/test_distributions.py::TestJit::test_enumerate_support, test/distributions/test_distributions.py::TestJit::test_log_prob, test/distributions/test_distributions.py::TestJit::test_mean, test/distributions/test_distributions.py::TestJit::test_rsample, test/distributions/test_distributions.py::TestJit::test_sample, test/distributions/test_distributions.py::TestJit::test_variance
2025-07-17T06:49:52.9312340Z 
2025-07-17T06:49:52.9312480Z Running test_extension_utils 1/1 ... [2025-07-17 06:49:52.920500]
2025-07-17T06:49:52.9312750Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:49:52.9313480Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_extension_utils.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:49:52.920780]
2025-07-17T06:49:54.7931020Z 
2025-07-17T06:49:54.7931560Z test_extension_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_extension_utils_1.1_2a2d7704bb1bc1cd_.log
2025-07-17T06:49:54.7932880Z Running 2 items in this shard: test/test_extension_utils.py::TestExtensionUtils::test_external_module_register, test/test_extension_utils.py::TestExtensionUtils::test_external_module_register_with_renamed_backend
2025-07-17T06:49:54.7933440Z 
2025-07-17T06:49:54.7934650Z Running test_cpp_api_parity 1/1 ... [2025-07-17 06:49:54.793408]
2025-07-17T06:49:54.7934920Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:49:54.7937310Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_cpp_api_parity.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:49:54.793660]
2025-07-17T06:50:17.7650930Z 
2025-07-17T06:50:17.7651510Z test_cpp_api_parity 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_api_parity_1.1_618a139f41d75b39_.log
2025-07-17T06:50:17.7760460Z Running 488 items in this shard: test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_mean, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_mean_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_none, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_none_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_sum, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_sum_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_mean, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_mean_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_none, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_none_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_sum, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_sum_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_circular_stride2_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_circular_stride2_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_dilated, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_dilated_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_groups, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_groups_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad1, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad1_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad1size1, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad1size1_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad2size1, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad2size1_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same_dilated, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same_dilated_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_valid, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_valid_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_reflect_stride2_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_reflect_stride2_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_replicate_stride2_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_replicate_stride2_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_stride, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_stride_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_zero_batch, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_zero_batch_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_zeros_stride2_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_zeros_stride2_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_circular_stride2_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_circular_stride2_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise_dilated, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise_dilated_cuda, 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test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_dim3, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_dim3_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_lastdim, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_lastdim_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_scalar, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_scalar_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_spatial, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_spatial_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_spatial_special, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_spatial_special_cuda, 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test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_spatial_dtype_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_spatial_special, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_spatial_special_cuda
2025-07-17T06:50:17.7865650Z 
2025-07-17T06:50:17.7865800Z Running inductor/test_cutlass_backend 1/1 ... [2025-07-17 06:50:17.765684]
2025-07-17T06:50:17.7866080Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:50:17.7866790Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_cutlass_backend.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:50:17.765946]
2025-07-17T06:50:20.4978310Z 
2025-07-17T06:50:20.4978970Z inductor/test_cutlass_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cutlass_backend_1.1_93c3066c5226cdca_.log
2025-07-17T06:50:20.4979450Z 
2025-07-17T06:50:20.4981780Z Running test_cpp_extensions_open_device_registration 1/1 ... [2025-07-17 06:50:20.498100]
2025-07-17T06:50:20.4983260Z Running test_transformers_privateuse1 1/1 ... [2025-07-17 06:50:20.498295]
2025-07-17T06:50:20.4984740Z Running inductor/test_flex_attention 1/1 ... [2025-07-17 06:50:20.498449]
2025-07-17T06:50:20.4985020Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:50:20.4987860Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_flex_attention.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:50:20.498682]
2025-07-17T06:50:23.1019760Z 
2025-07-17T06:50:23.1020430Z inductor/test_flex_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_flex_attention_1.1_c92b1b95a2bb861b_.log
2025-07-17T06:50:23.1189440Z Running 496 items in this shard: test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_causal_mask_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod0_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod1_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod2_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod3_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod4_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod5_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod6_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod7_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_aot_eager_gradcheck_score_mod0_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_aot_eager_gradcheck_score_mod1_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_aot_eager_gradcheck_score_mod2_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_aot_eager_gradcheck_score_mod3_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_aot_eager_gradcheck_score_mod4_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_aot_eager_gradcheck_score_mod5_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_autograd_function_in_score_mod_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_block_mask_non_divisible_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_builtin_score_mods_automatic_dynamic_score_mod0_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_builtin_score_mods_automatic_dynamic_score_mod1_cpu_float32, 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2025-07-17T06:50:23.1333900Z 
2025-07-17T06:50:23.1334010Z Running test_fx 1/1 ... [2025-07-17 06:50:23.102766]
2025-07-17T06:50:23.1334240Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:50:23.1334920Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_fx.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:50:23.103064]
2025-07-17T06:50:40.5524440Z 
2025-07-17T06:50:40.5524890Z test_fx 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_1.1_ec576b6330d059cc_.log
2025-07-17T06:50:40.5778650Z Running 1152 items in this shard: test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationInput_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationMetadata_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationTorchTensorCall_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_Mutation_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_ReturnList_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_TakeList_cpu, test/test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_FactoryFunctionCall_cpu, test/test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_MutationFactory_cpu, test/test_fx.py::TestCSEPass::test_banned_list, test/test_fx.py::TestCSEPass::test_empty, test/test_fx.py::TestCSEPass::test_immutable_list_multiple_entries, test/test_fx.py::TestCSEPass::test_immutable_list_type, test/test_fx.py::TestCSEPass::test_kwarg, test/test_fx.py::TestCSEPass::test_nested_immutable_list_type, test/test_fx.py::TestCSEPass::test_nochange, test/test_fx.py::TestCSEPass::test_rand_like, test/test_fx.py::TestCSEPass::test_rand_n, test/test_fx.py::TestCSEPass::test_random, test/test_fx.py::TestCSEPass::test_simple, test/test_fx.py::TestCSEPass::test_simple_2, test/test_fx.py::TestCSEPass::test_simple_multiple_same_ops, test/test_fx.py::TestCSEPass::test_two_args, test/test_fx.py::TestCSEPass::test_two_args_default, test/test_fx.py::TestDCE::test_dead_chain, test/test_fx.py::TestDCE::test_dead_getattr, test/test_fx.py::TestDCE::test_dead_placeholder, test/test_fx.py::TestDCE::test_dead_placeholder_with_user, test/test_fx.py::TestDCE::test_impure_custom, test/test_fx.py::TestDCE::test_impure_kwargs, test/test_fx.py::TestDCE::test_impure_nodes_args, test/test_fx.py::TestDCE::test_impure_random, test/test_fx.py::TestDCE::test_keep_collectives, test/test_fx.py::TestDCE::test_keep_collectives_no_overload, test/test_fx.py::TestDCE::test_keep_module_with_side_effects, test/test_fx.py::TestDCE::test_keep_setitem, test/test_fx.py::TestDCE::test_keep_torch_assert, test/test_fx.py::TestDCE::test_simple, test/test_fx.py::TestConstFold::test_check_inline_non_const, test/test_fx.py::TestConstFold::test_check_inline_non_const_mult_return, test/test_fx.py::TestConstFold::test_check_skip_folding_quant_dequant_pattern, test/test_fx.py::TestConstFold::test_const_fold_basic_one_attr_name_collision, test/test_fx.py::TestConstFold::test_const_fold_basic_one_attr_no_name_collision, test/test_fx.py::TestConstFold::test_const_fold_basic_placeholder_reordered, test/test_fx.py::TestConstFold::test_const_fold_basic_two_attr, test/test_fx.py::TestConstFold::test_const_fold_basic_two_attr_three_input, test/test_fx.py::TestConstFold::test_const_fold_has_inlined_call_module_node, test/test_fx.py::TestConstFold::test_const_fold_module_attr, test/test_fx.py::TestConstFold::test_const_fold_multi_const_folded_attrs, test/test_fx.py::TestConstFold::test_const_fold_noop, test/test_fx.py::TestConstFold::test_const_fold_submod_hierarchy, test/test_fx.py::TestConstFold::test_const_fold_tensor_meta, test/test_fx.py::TestConstFold::test_const_fold_unused_placeholder, test/test_fx.py::TestConstFold::test_dict_output, test/test_fx.py::TestConstFold::test_fold_module, test/test_fx.py::TestConstFold::test_retain_node_meta, test/test_fx.py::TestConstFold::test_three_outputs, test/test_fx.py::TestConstFold::test_two_outputs, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_dim_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_ndim_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_nelement_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_numel_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_shape_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_size_const, test/test_fx.py::AnnotationsTest::test_annotate, test/test_fx.py::AnnotationsTest::test_annotations, test/test_fx.py::AnnotationsTest::test_broadcasting1, test/test_fx.py::AnnotationsTest::test_broadcasting2, test/test_fx.py::AnnotationsTest::test_broadcasting3, test/test_fx.py::AnnotationsTest::test_consistency, test/test_fx.py::AnnotationsTest::test_precision, test/test_fx.py::TypeCheckerTest::test_flatten_fully_static, test/test_fx.py::TypeCheckerTest::test_resnet50, test/test_fx.py::TypeCheckerTest::test_symbolic_add_with_broadcast, test/test_fx.py::TypeCheckerTest::test_symbolic_add_with_broadcast_2, test/test_fx.py::TypeCheckerTest::test_type_check_add_false, test/test_fx.py::TypeCheckerTest::test_type_check_add_true, test/test_fx.py::TypeCheckerTest::test_type_check_add_with_broadcast, test/test_fx.py::TypeCheckerTest::test_type_check_add_with_scalar, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D_broadcast, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D_false, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_symbolic, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_2, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_2_fully_static, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_maxpool2d_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_types, test/test_fx.py::TypeCheckerTest::test_type_check_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_flatten3, test/test_fx.py::TypeCheckerTest::test_type_check_flatten_2, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_true, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_true_param_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_true, test/test_fx.py::TypeCheckerTest::test_type_check_symbolic_inferenceconv2D_maxpool2d_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_transpose_False, test/test_fx.py::TypeCheckerTest::test_type_check_transpose_true, test/test_fx.py::TypeCheckerTest::test_type_maxpool2d_fully_static, test/test_fx.py::TypeCheckerTest::test_type_typechecl_maxpool2d_3dinput, test/test_fx.py::TypeCheckerTest::test_typecheck_basicblock, test/test_fx.py::TestMatcher::test_matcher_with_name_node_map_function, test/test_fx.py::TestMatcher::test_matcher_with_name_node_map_module, test/test_fx.py::TestMatcher::test_split_to_graph_and_name_node_map, test/test_fx.py::TestMatcher::test_subgraph_matcher_ignore_literals, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_attributes, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_list, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_list_bad, test/test_fx.py::TestMatcher::test_variatic_arg_matching, test/test_fx.py::TestPassManager::test_pass_manager, test/test_fx.py::TestPassManager::test_pass_manager_bad_checks, test/test_fx.py::TestPassManager::test_pass_manager_checks, test/test_fx.py::TestPassManager::test_pass_manager_error, test/test_fx.py::TestPassManager::test_this_before_that_pass_constraint, test/test_fx.py::TestPassManager::test_topological_sort, test/test_fx.py::TestSourceMatcher::test_legalize_slice, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_weight_tied_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_weight_tied_strict_True, test/test_fx.py::TestSubgraphRewriter::test_matching_pattern_with_list_type_arg, test/test_fx.py::TestSubgraphRewriter::test_matching_variable_arguments, test/test_fx.py::TestSubgraphRewriter::test_replace_pattern_with_callback, test/test_fx.py::TestSubgraphRewriter::test_replace_pattern_with_filters, test/test_fx.py::TestSubgraphRewriter::test_replaced_nodes, test/test_fx.py::TestSubgraphRewriter::test_replacement_with_attrs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_annotations_int, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_call_method, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_correct_output_replacement, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_graph_argument_order, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_internal_pattern_nodes_cannot_have_users_that_are_not_matched, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_local_revert, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_multiple_pattern_match, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_nodes_with_kwargs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_is_entire_graph, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_output_pattern_node_can_have_users_that_are_not_matched, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_placeholder_matching, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_preserves_logic, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_consecutive_submodules, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_with_duplicated_outputs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_with_multiple_outputs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replaces_referenced_submodules, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_single_pattern_match, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_traced_as_callable, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_oneliner_pattern, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_overlapping_matches, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_trivial_replacement, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_unused_args, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_unused_results, test/test_fx.py::TestFX::test_all_input_nodes, test/test_fx.py::TestFX::test_annotation_with_future, test/test_fx.py::TestFX::test_annotations_empty_tuple, test/test_fx.py::TestFX::test_annotations_with_forward_references, test/test_fx.py::TestFX::test_annotations_with_no_forward_references, test/test_fx.py::TestFX::test_annotations_with_non_torch_reference_and_internal_forward_references, test/test_fx.py::TestFX::test_annotations_with_non_torch_reference_and_no_internal_forward_references, test/test_fx.py::TestFX::test_args_kwargs, test/test_fx.py::TestFX::test_args_kwargs_no_self, test/test_fx.py::TestFX::test_assert, test/test_fx.py::TestFX::test_ast_rewriter_reassigns_submodules, test/test_fx.py::TestFX::test_ast_rewriter_rewrites_assert, test/test_fx.py::TestFX::test_ast_rewriter_rewrites_assert_with_message, test/test_fx.py::TestFX::test_ast_rewriter_wrap, test/test_fx.py::TestFX::test_ast_rewriter_wrap_fn_directly, test/test_fx.py::TestFX::test_ast_rewriter_wrap_with_submodule, test/test_fx.py::TestFX::test_ast_rewriter_wrapped_via_decorator, test/test_fx.py::TestFX::test_ast_rewriter_wrapped_via_decorator_and_transformed, test/test_fx.py::TestFX::test_autowrap_functions, test/test_fx.py::TestFX::test_concrete_arg_none_assert, test/test_fx.py::TestFX::test_construct_root_dict, test/test_fx.py::TestFX::test_control_flow_tracing, test/test_fx.py::TestFX::test_copy_it, test/test_fx.py::TestFX::test_copy_no_remap, test/test_fx.py::TestFX::test_ctx_mgr, test/test_fx.py::TestFX::test_custom_codegen, test/test_fx.py::TestFX::test_custom_codegen_with_transformer, test/test_fx.py::TestFX::test_custom_import, test/test_fx.py::TestFX::test_custom_proxy_dynamic_value, test/test_fx.py::TestFX::test_custom_proxy_input_dependent_control_flow, test/test_fx.py::TestFX::test_custom_proxy_type, test/test_fx.py::TestFX::test_custom_proxy_type_literal, test/test_fx.py::TestFX::test_custom_traceback_not_raised_when_exception_source_is_submodule, test/test_fx.py::TestFX::test_custom_traceback_raised_when_exception_source_is_graphmodule, test/test_fx.py::TestFX::test_deepcopy_graph_with_tracer_cls, test/test_fx.py::TestFX::test_deepcopy_graphmodule, test/test_fx.py::TestFX::test_deepcopy_graphmodule_with_transform, test/test_fx.py::TestFX::test_deepcopy_no_recursion, test/test_fx.py::TestFX::test_deepcopy_recursion_depth, test/test_fx.py::TestFX::test_deepcopy_tracer, test/test_fx.py::TestFX::test_deepcopy_with_submods_params, test/test_fx.py::TestFX::test_delete_unused_submodules_leaf, test/test_fx.py::TestFX::test_delete_unused_values, test/test_fx.py::TestFX::test_dict, test/test_fx.py::TestFX::test_direct_param_use, test/test_fx.py::TestFX::test_disallow_override, test/test_fx.py::TestFX::test_ellipsis, test/test_fx.py::TestFX::test_empty_graph_codegen, test/test_fx.py::TestFX::test_enum, test/test_fx.py::TestFX::test_erase_node_error, test/test_fx.py::TestFX::test_example_shape_prop, test/test_fx.py::TestFX::test_find_uses, test/test_fx.py::TestFX::test_fn_type_annotation_empty, test/test_fx.py::TestFX::test_fn_type_annotations, test/test_fx.py::TestFX::test_fx_and_or, test/test_fx.py::TestFX::test_fx_create_arg, test/test_fx.py::TestFX::test_fx_shifts, test/test_fx.py::TestFX::test_fx_stateless, test/test_fx.py::TestFX::test_get_torch_func_signature, test/test_fx.py::TestFX::test_getitem, test/test_fx.py::TestFX::test_getitem_subproc, test/test_fx.py::TestFX::test_graph_edit_with_proxy, test/test_fx.py::TestFX::test_graph_fns, test/test_fx.py::TestFX::test_graph_module, test/test_fx.py::TestFX::test_graph_module_init_buffer_param_copied_dict_init, test/test_fx.py::TestFX::test_graph_module_init_buffer_param_copied_mod_init, test/test_fx.py::TestFX::test_graph_module_replicate_for_dp, test/test_fx.py::TestFX::test_graph_unique_names, test/test_fx.py::TestFX::test_graph_unique_names_manual, test/test_fx.py::TestFX::test_immutable_dict_pytree_ops, test/test_fx.py::TestFX::test_immutable_list_pytree_ops, test/test_fx.py::TestFX::test_imul_code_print, test/test_fx.py::TestFX::test_inf_nan, test/test_fx.py::TestFX::test_inf_nan_kwds, test/test_fx.py::TestFX::test_informative_co_filename, test/test_fx.py::TestFX::test_inline_graph, test/test_fx.py::TestFX::test_insert_arg, test/test_fx.py::TestFX::test_insertion_point, test/test_fx.py::TestFX::test_interpreter, test/test_fx.py::TestFX::test_interpreter_default_args, test/test_fx.py::TestFX::test_interpreter_gc_values, test/test_fx.py::TestFX::test_interpreter_noop_resnet18, test/test_fx.py::TestFX::test_interpreter_not_enough_args, test/test_fx.py::TestFX::test_interpreter_onthefly_swap, test/test_fx.py::TestFX::test_interpreter_other_graph, test/test_fx.py::TestFX::test_interpreter_partial_eval, test/test_fx.py::TestFX::test_interpreter_run_node_override, test/test_fx.py::TestFX::test_interpreter_star_args, test/test_fx.py::TestFX::test_interpreter_with_codegen, test/test_fx.py::TestFX::test_layout, test/test_fx.py::TestFX::test_leaf_module, test/test_fx.py::TestFX::test_lineno_map, test/test_fx.py::TestFX::test_matmul_tracing, test/test_fx.py::TestFX::test_metadata_on_ph, test/test_fx.py::TestFX::test_module_deepcopy_edit_nodes, test/test_fx.py::TestFX::test_move_before, test/test_fx.py::TestFX::test_multi_insert_point, test/test_fx.py::TestFX::test_multiple_default_args, test/test_fx.py::TestFX::test_named_tuple_inlined, test/test_fx.py::TestFX::test_namedtuple_return_qualname, test/test_fx.py::TestFX::test_namedtuple_return_trace, test/test_fx.py::TestFX::test_native_callable, test/test_fx.py::TestFX::test_nn_module_stack, test/test_fx.py::TestFX::test_no_mutation, test/test_fx.py::TestFX::test_node_tagging, test/test_fx.py::TestFX::test_nonetype_annotation, test/test_fx.py::TestFX::test_partial_trace, test/test_fx.py::TestFX::test_pickle_custom_import, test/test_fx.py::TestFX::test_pickle_graphmodule, test/test_fx.py::TestFX::test_pickle_nonetype_annotation, test/test_fx.py::TestFX::test_pickle_torch_custom_ops, test/test_fx.py::TestFX::test_prepend_self, test/test_fx.py::TestFX::test_pretty_print, test/test_fx.py::TestFX::test_pretty_print_graph, test/test_fx.py::TestFX::test_pretty_print_node, test/test_fx.py::TestFX::test_pretty_print_targets, test/test_fx.py::TestFX::test_print_graph, test/test_fx.py::TestFX::test_profiler_ranges_side_effect, test/test_fx.py::TestFX::test_proxy_deepcopy_with_tracer, test/test_fx.py::TestFX::test_proxy_deepcopy_without_tracer, test/test_fx.py::TestFX::test_pytree, test/test_fx.py::TestFX::test_pytree_concrete, test/test_fx.py::TestFX::test_reassign_args_kwargs_uses, test/test_fx.py::TestFX::test_regular_and_default_args, test/test_fx.py::TestFX::test_remove_uses, test/test_fx.py::TestFX::test_remove_uses_with_custom_filter, test/test_fx.py::TestFX::test_replace_input, test/test_fx.py::TestFX::test_replace_uses, test/test_fx.py::TestFX::test_reserved_getattr, test/test_fx.py::TestFX::test_return_tuple, test/test_fx.py::TestFX::test_return_type_exists, test/test_fx.py::TestFX::test_return_type_exists_pre_pep585, test/test_fx.py::TestFX::test_script_method_trace, test/test_fx.py::TestFX::test_script_tensor_constant, test/test_fx.py::TestFX::test_sequential, test/test_fx.py::TestFX::test_shape_prop_aggregate, test/test_fx.py::TestFX::test_shape_prop_layout, test/test_fx.py::TestFX::test_shape_prop_layout_3d, test/test_fx.py::TestFX::test_shape_prop_unbacked_sym, test/test_fx.py::TestFX::test_single_default_arg, test/test_fx.py::TestFX::test_snake_case, test/test_fx.py::TestFX::test_sqrt, test/test_fx.py::TestFX::test_stack_traces, test/test_fx.py::TestFX::test_stack_traces_with_transformer, test/test_fx.py::TestFX::test_string_literal_return, test/test_fx.py::TestFX::test_submodule_manipulation_API, test/test_fx.py::TestFX::test_symbolic_trace_assert, test/test_fx.py::TestFX::test_symbolic_trace_sequential, test/test_fx.py::TestFX::test_tensor_attribute, test/test_fx.py::TestFX::test_tensor_attribute_coalseced, test/test_fx.py::TestFX::test_tensor_constant, test/test_fx.py::TestFX::test_throw_out_variant, test/test_fx.py::TestFX::test_torch_custom_ops, test/test_fx.py::TestFX::test_torch_fx_getattr, test/test_fx.py::TestFX::test_torch_fx_len, test/test_fx.py::TestFX::test_torch_op_overloads, test/test_fx.py::TestFX::test_torchbind_class_attribute_in_fx, test/test_fx.py::TestFX::test_torchbind_class_attribute_in_fx_tensor_arg, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_dict_int_keys, test/test_fx.py::TestFX::test_trace_dict_proxy_keys, test/test_fx.py::TestFX::test_trace_fn_constant, test/test_fx.py::TestFX::test_trace_function, test/test_fx.py::TestFX::test_trace_multiple_funcs, test/test_fx.py::TestFX::test_trace_return_dataclass, test/test_fx.py::TestFX::test_trace_return_dataclass_nested, test/test_fx.py::TestFX::test_trace_return_namedtuple, test/test_fx.py::TestFX::test_tracing_graphmodules_as_leaf_submodules, test/test_fx.py::TestFX::test_transformer_multi_outputs, test/test_fx.py::TestFX::test_transformer_noop, test/test_fx.py::TestFX::test_transformer_op_swap, test/test_fx.py::TestFX::test_transformer_preserves_nn_module_stack_for_get_attr, test/test_fx.py::TestFX::test_tuple_no_subscript, test/test_fx.py::TestFX::test_typename_print, test/test_fx.py::TestFX::test_typename_print_pre_pep585, test/test_fx.py::TestFX::test_unpack, test/test_fx.py::TestFX::test_unpack_dict_better_error, test/test_fx.py::TestFX::test_unpack_list_better_error, test/test_fx.py::TestFX::test_update_args_api, test/test_fx.py::TestFX::test_update_args_kwargs_yells_at_you, test/test_fx.py::TestFX::test_update_kwargs_api, test/test_fx.py::TestFX::test_user_friendly_call_provenance_with_function, test/test_fx.py::TestFX::test_user_friendly_call_provenance_with_module, test/test_fx.py::TestFX::test_varargs_concrete, test/test_fx.py::TestFX::test_wrap, test/test_fx.py::TestFX::test_wrap_decorated_function, test/test_fx.py::TestFX::test_wrap_fn_directly, test/test_fx.py::TestFX::test_wrap_with_submodule, test/test_fx.py::TestFX::test_wrapped_method, test/test_fx.py::TestFX::test_wrapped_retrace, test/test_fx.py::TestFX::test_wrapped_via_decorator, test/test_fx.py::TestFX::test_wrapped_via_decorator_and_transformed, test/test_fx.py::TestFX::test_wrong_target_type, test/test_fx.py::TestFX::test_wrong_topo, test/test_fx.py::TestFXAPIBackwardCompatibility::test_adding_side_effect_function, test/test_fx.py::TestFXAPIBackwardCompatibility::test_class_member_back_compat, test/test_fx.py::TestFXAPIBackwardCompatibility::test_function_back_compat, test/test_fx.py::TestFXAPIBackwardCompatibility::test_preserve_unused_attr_after_unpickle, test/test_fx.py::TestFXAPIBackwardCompatibility::test_public_api_surface, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool1d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_affine_grid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_alpha_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_batch_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_bilinear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_binary_cross_entropy, test/test_fx.py::TestFunctionalTracing::test_nn_functional_binary_cross_entropy_with_logits, test/test_fx.py::TestFunctionalTracing::test_nn_functional_celu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_celu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_channel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_tbc, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cosine_embedding_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cosine_similarity, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cross_entropy, test/test_fx.py::TestFunctionalTracing::test_nn_functional_ctc_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_elu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_elu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_embedding, test/test_fx.py::TestFunctionalTracing::test_nn_functional_embedding_bag, test/test_fx.py::TestFunctionalTracing::test_nn_functional_feature_alpha_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gaussian_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_glu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_grid_sample, test/test_fx.py::TestFunctionalTracing::test_nn_functional_group_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gumbel_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardshrink, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardsigmoid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardswish, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardtanh, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardtanh_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hinge_embedding_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_huber_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_instance_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_interpolate, test/test_fx.py::TestFunctionalTracing::test_nn_functional_kl_div, test/test_fx.py::TestFunctionalTracing::test_nn_functional_l1_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_layer_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_leaky_relu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_leaky_relu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_linear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_local_response_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_log_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_logsigmoid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_margin_ranking_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool1d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_mish, test/test_fx.py::TestFunctionalTracing::test_nn_functional_mse_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multi_head_attention_forward, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multi_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multilabel_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multilabel_soft_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_native_channel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_normalize, test/test_fx.py::TestFunctionalTracing::test_nn_functional_one_hot, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pad, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pairwise_distance, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pdist, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pixel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pixel_unshuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_poisson_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_prelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu6, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rms_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rrelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rrelu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_scaled_dot_product_attention, test/test_fx.py::TestFunctionalTracing::test_nn_functional_selu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_selu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_silu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_smooth_l1_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_soft_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softmin, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softplus, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softshrink, test/test_fx.py::TestFunctionalTracing::test_nn_functional_threshold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_threshold_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_triplet_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_triplet_margin_with_distance_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_unfold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample_bilinear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample_nearest, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_H_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_T_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___getitem___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___radd___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rdiv___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rmatmul___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rmod___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rmul___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rpow___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rsub___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__batch_norm_with_update_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__chunk_cat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__native_batch_norm_legit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__segment_reduce_lengths_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__segment_reduce_offsets_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__softmax_backward_data_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__unsafe_masked_index_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__unsafe_masked_index_put_accumulate_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__upsample_bilinear2d_aa_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_abs_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_acos_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_acosh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_add_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addbmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addcdiv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addcmul_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addmm_decomposed_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addmv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_alias_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_all_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_allclose_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_aminmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_angle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_any_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_arange_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argsort_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argwhere_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_partial_views_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_asin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_asinh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atan2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atan_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atanh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atleast_1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atleast_2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atleast_3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_baddbmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bernoulli_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bfloat16_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_block_diag_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bool_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_broadcast_shapes_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_broadcast_tensors_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_broadcast_to_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bucketize_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_byte_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cartesian_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cauchy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cdist_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cdouble_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ceil_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cfloat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_chalf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_char_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cholesky_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cholesky_inverse_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cholesky_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_chunk_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clamp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clamp_max_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clamp_min_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clone_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_column_stack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_combinations_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_complex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_conj_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_conj_physical_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_constant_pad_nd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_contiguous_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_copysign_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_corrcoef_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cos_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cosh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_count_nonzero_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cov_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cross_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cummax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cummin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cumprod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cumsum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cumulative_trapezoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_deg2rad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diag_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diag_embed_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagflat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagonal_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagonal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagonal_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diff_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_digamma_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dist_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_div_floor_rounding_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_div_no_rounding_mode_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_div_trunc_rounding_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_double_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dsplit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dstack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_einsum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_permuted_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_strided_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_eq_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_equal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_erf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_erfc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_erfinv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_exp2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_exp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expand_as_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expand_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expand_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expm1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_exponential_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_eye_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fftshift_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_hfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_hfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_hfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifftshift_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ihfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ihfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ihfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_irfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_irfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_irfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_rfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_rfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_rfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fill_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_flatten_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_flip_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fliplr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_flipud_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_float_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_float_power_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_floor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_floor_divide_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fmod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_frac_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_frexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_full_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_full_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_gather_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ge_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_geometric_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_geqrf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_gradient_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_grid_sampler_2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_gt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_half_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_heaviside_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_histc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_histogram_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_histogramdd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hsplit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hstack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hypot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_i0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_igamma_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_igammac_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_add_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_fill_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_put_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_select_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_inner_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_int_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isclose_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isfinite_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isinf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isnan_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isneginf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isposinf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isreal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_item_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_2inputs_2outputs_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_4inputs_with_extra_args_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_binary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_binary_return_by_ref_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_unary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_kron_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_kthvalue_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ldexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_le_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lerp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lgamma_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cholesky_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cholesky_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cond_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cross_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_det_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_diagonal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eig_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eigh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eigvals_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eigvalsh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_householder_product_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_inv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_inv_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_ldl_factor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_ldl_factor_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_ldl_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lstsq_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lstsq_grad_oriented_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_factor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_factor_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_power_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_rank_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_rank_hermitian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_multi_dot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_norm_subgradients_at_zero_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_pinv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_pinv_hermitian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_pinv_singular_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_qr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_slogdet_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_solve_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_solve_triangular_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_svd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_svdvals_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_tensorinv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_tensorsolve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_vander_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_vecdot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_vector_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linspace_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linspace_tensor_overload_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log10_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log1p_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_normal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_softmax_with_dtype_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logaddexp2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logaddexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logcumsumexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logdet_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_and_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_not_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_or_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_xor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logspace_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logspace_tensor_overload_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logsumexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_long_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lu_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lu_unpack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mH_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mT_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_argmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_argmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_cumprod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_cumsum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_fill_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_log_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_logaddexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_logsumexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_median_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_normalize_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_select_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_softmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_std_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_sum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_var_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_matmul_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_matrix_exp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_binary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_pool2d_with_indices_backward_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_reduction_no_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_reduction_with_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_maximum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_median_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_meshgrid_list_of_tensors_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_meshgrid_variadic_tensors_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_min_binary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_min_reduction_no_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_min_reduction_with_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_minimum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mode_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_movedim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_msort_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mul_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_multinomial_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nan_to_num_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nanmean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nanmedian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nanquantile_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nansum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_narrow_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_narrow_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_native_batch_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_native_dropout_backward_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_native_layer_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ne_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_neg_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_empty_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_empty_strided_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_full_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_ones_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_zeros_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nextafter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_alpha_dropout_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_batch_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_bilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_binary_cross_entropy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_celu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_channel_shuffle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_cosine_embedding_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_cosine_similarity_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_cross_entropy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_ctc_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_dropout2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_dropout3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_dropout_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_elu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_embedding_bag_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_embedding_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_fractional_max_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_fractional_max_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_gaussian_nll_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_gelu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_glu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_grid_sample_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_group_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardshrink_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardsigmoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardswish_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardtanh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hinge_embedding_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_huber_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_instance_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_area_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_bicubic_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_bilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_linear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_nearest_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_trilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_kl_div_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_l1_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_layer_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_leaky_relu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_linear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_local_response_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_logsigmoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_margin_ranking_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool1d_grad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool2d_grad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool3d_grad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_mish_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_mse_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multi_head_attention_forward_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multi_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multilabel_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_nll_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_normalize_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_circular_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_constant_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_reflect_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_replicate_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_replicate_negative_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pairwise_distance_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pdist_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pixel_shuffle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pixel_unshuffle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_poisson_nll_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_prelu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_relu6_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_relu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_rms_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_rrelu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_selu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_silu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_smooth_l1_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_soft_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softmin_with_dtype_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softplus_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softshrink_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softsign_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_tanhshrink_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_threshold_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_triplet_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_unfold_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_upsample_bilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_upsample_nearest_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nonzero_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nonzero_static_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_fro_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_inf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_nuc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_normal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_normal_in_place_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_normal_number_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ones_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ones_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ormqr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_outer_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_pca_lowrank_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_permute_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_permute_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_pinverse_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polar_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_4_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_positive_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_pow_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_put_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_qr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_quantile_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rad2deg_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rand_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randint_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randint_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randn_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ravel_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_real_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_reciprocal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_remainder_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_renorm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_repeat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_repeat_interleave_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_reshape_as_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_reshape_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resize__cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resize_as__cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resolve_conj_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resolve_neg_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_roll_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rot90_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_decimals_0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_decimals_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_decimals_neg_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rsqrt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rsub_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scalar_tensor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_add_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_sum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_searchsorted_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_select_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_select_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sgn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_short_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sigmoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sign_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_bartlett_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_blackman_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_cosine_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_exponential_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_gaussian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_general_cosine_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_general_hamming_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_hamming_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_hann_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_kaiser_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_nuttall_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signbit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sinc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sinh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_slice_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_slice_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_softmax_with_dtype_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sort_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sparse_mm_reduce_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sparse_sampled_addmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_airy_ai_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_j0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_j1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_y0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_y1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_t_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_u_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_v_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_w_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_entr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_erfcx_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_hermite_polynomial_h_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_hermite_polynomial_he_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_i0e_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_i1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_i1e_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_laguerre_polynomial_l_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_legendre_polynomial_p_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_log_ndtr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_i0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_i1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_k0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_k1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_ndtr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_ndtri_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_scaled_modified_bessel_k0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_scaled_modified_bessel_k1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_spherical_bessel_j0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_xlog1py_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_zeta_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_list_args_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_with_sizes_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_with_sizes_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sqrt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_square_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_squeeze_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_squeeze_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_squeeze_multiple_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_stack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_mean_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_stft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sub_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sum_to_size_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_svd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_svd_lowrank_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_t_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_t_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_take_along_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_take_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tan_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tanh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tensor_split_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tensordot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tile_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_to_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_to_sparse_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_topk_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trace_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_transpose_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_transpose_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trapezoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trapz_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_triangular_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tril_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_triu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_true_divide_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trunc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unbind_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unbind_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unflatten_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unfold_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unfold_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_uniform_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unique_consecutive_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unique_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsafe_chunk_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsafe_split_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsqueeze_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsqueeze_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_mean_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_vdot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_as_complex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_as_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_vsplit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_vstack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_where_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_xlogy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_zero__cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_zeros_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_zeros_like_cpu_float32
2025-07-17T06:50:40.6025370Z 
2025-07-17T06:50:40.6025500Z Running test_show_pickle 1/1 ... [2025-07-17 06:50:40.553543]
2025-07-17T06:50:40.6025750Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:50:40.6026460Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_show_pickle.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:50:40.553836]
2025-07-17T06:50:42.4402410Z 
2025-07-17T06:50:42.4402920Z test_show_pickle 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_show_pickle_1.1_5a50ca1d4e7f5eeb_.log
2025-07-17T06:50:42.4403600Z Running 1 items in this shard: test/test_show_pickle.py::TestShowPickle::test_scripted_model
2025-07-17T06:50:42.4403900Z 
2025-07-17T06:50:42.4406270Z Running inductor/test_benchmark_fusion 1/1 ... [2025-07-17 06:50:42.440565]
2025-07-17T06:50:42.4406600Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:50:42.4409380Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_benchmark_fusion.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:50:42.440843]
2025-07-17T06:50:44.9013710Z 
2025-07-17T06:50:44.9014390Z inductor/test_benchmark_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_benchmark_fusion_1.1_4e55bb989c2daf0c_.log
2025-07-17T06:50:44.9014940Z Running 0 items in this shard:
2025-07-17T06:50:44.9015070Z 
2025-07-17T06:50:44.9017030Z Running inductor/test_max_autotune 1/1 ... [2025-07-17 06:50:44.901621]
2025-07-17T06:50:44.9017340Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:50:44.9019440Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_max_autotune.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:50:44.901863]
2025-07-17T06:50:47.2070480Z 
2025-07-17T06:50:47.2071120Z inductor/test_max_autotune 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_max_autotune_1.1_a8e50779ec9b7b81_.log
2025-07-17T06:50:47.2071590Z 
2025-07-17T06:50:47.2073760Z Running test_utils 1/1 ... [2025-07-17 06:50:47.207309]
2025-07-17T06:50:47.2074030Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:50:47.2076660Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_utils.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:50:47.207565]
2025-07-17T06:52:43.8722090Z 
2025-07-17T06:52:43.8722810Z test_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_utils_1.1_f27d5d53ac3bb664_.log
2025-07-17T06:52:43.9913780Z Running 6035 items in this shard: test/test_utils.py::TestCheckpoint::test_checkpoint, test/test_utils.py::TestCheckpoint::test_checkpoint_module_list, test/test_utils.py::TestCheckpoint::test_checkpoint_no_tensors, test/test_utils.py::TestCheckpoint::test_checkpoint_non_tensor, test/test_utils.py::TestCheckpoint::test_checkpoint_non_tensor_inputs_outputs, test/test_utils.py::TestCheckpoint::test_checkpoint_not_preserve_rng_state_and_without_reentrant, test/test_utils.py::TestCheckpoint::test_checkpoint_partial_grad, test/test_utils.py::TestCheckpoint::test_checkpoint_rng_cpu, test/test_utils.py::TestCheckpoint::test_checkpoint_rng_cuda, test/test_utils.py::TestCheckpoint::test_checkpoint_sequential_deprecated_multiple_args, test/test_utils.py::TestCheckpoint::test_checkpoint_sequential_deprecated_no_args, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_valid, test/test_utils.py::TestCheckpoint::test_checkpointing_without_reentrant_early_free, test/test_utils.py::TestCheckpoint::test_get_device_states_recursive, test/test_utils.py::TestCheckpoint::test_infer_device_state_recursive_meta, test/test_utils.py::TestCheckpoint::test_infer_device_state_recursive_multi_cuda, test/test_utils.py::TestDataLoaderUtils::test_multi_drop, test/test_utils.py::TestDataLoaderUtils::test_multi_keep, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_single_drop, test/test_utils.py::TestDataLoaderUtils::test_single_keep, test/test_utils.py::TestBottleneck::test_bottleneck_cpu_only, test/test_utils.py::TestBottleneck::test_bottleneck_cuda, test/test_utils.py::TestCollectEnv::test_smoke, test/test_utils.py::TestONNXUtils::test_check_onnx_broadcast, test/test_utils.py::TestONNXUtils::test_prepare_onnx_paddings, test/test_utils.py::TestHipify::test_import_hipify, test/test_utils.py::TestHipifyTrie::test_add_and_search_trie, test/test_utils.py::TestHipifyTrie::test_add_multiple_and_search_trie, test/test_utils.py::TestHipifyTrie::test_char_export_trie_to_regex, test/test_utils.py::TestHipifyTrie::test_export_trie_to_regex, test/test_utils.py::TestHipifyTrie::test_prefix_words_export_trie_to_regex, test/test_utils.py::TestHipifyTrie::test_quote_escape, test/test_utils.py::TestHipifyTrie::test_single_export_trie_to_regex, test/test_utils.py::TestHipifyTrie::test_special_char_export_trie_to_regex, test/test_utils.py::TestAssert::test_assert_scriptable, test/test_utils.py::TestAssert::test_assert_true, test/test_utils.py::TestStandaloneCPPJIT::test_load_standalone, test/test_utils.py::TestRenderUtils::test_basic, test/test_utils.py::TestDeviceUtilsCPU::test_basic_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_decorator_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_decorator_generator_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rand___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rand___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rand___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rand___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rand___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rand___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmod___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmod___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmod___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmod___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___ror___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___ror___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___ror___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___ror___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___ror___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___ror___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rxor___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rxor___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rxor___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rxor___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rxor___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rxor___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__batch_norm_with_update_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__batch_norm_with_update_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__batch_norm_with_update_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__batch_norm_with_update_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__native_batch_norm_legit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__native_batch_norm_legit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__native_batch_norm_legit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__native_batch_norm_legit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_lengths_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_lengths_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_lengths_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_lengths_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_offsets_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_offsets_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_offsets_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_offsets_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__softmax_backward_data_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__softmax_backward_data_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__softmax_backward_data_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__softmax_backward_data_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__upsample_bilinear2d_aa_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__upsample_bilinear2d_aa_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__upsample_bilinear2d_aa_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcdiv_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcdiv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcdiv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcdiv_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcdiv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcdiv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_int16, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bfloat16_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bincount_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bincount_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bincount_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bincount_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bincount_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_and_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_and_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_and_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_and_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_and_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_and_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_left_shift_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_left_shift_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_left_shift_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_left_shift_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_left_shift_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_not_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_not_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_not_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_not_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_not_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_not_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_or_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_or_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_or_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_or_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_or_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_or_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_right_shift_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_right_shift_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_right_shift_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_right_shift_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_right_shift_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_xor_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_xor_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_xor_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_xor_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_xor_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_xor_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_block_diag_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_shapes_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cauchy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cauchy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cauchy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cauchy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdist_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdist_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_inverse_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_inverse_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_inverse_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_inverse_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_complex_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_complex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_complex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exponential_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exponential_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exponential_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exponential_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float8_e4m3fn, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float8_e4m3fnuz, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float8_e5m2, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float8_e5m2fnuz, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frac_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frac_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frac_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frac_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_uint16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_uint32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geqrf_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geqrf_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geqrf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geqrf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histc_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histc_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histogram_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histogram_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histogramdd_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histogramdd_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hypot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hypot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hypot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hypot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igamma_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igamma_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igamma_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igamma_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igammac_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igammac_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igammac_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igammac_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_imag_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_imag_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_imag_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_float16, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_istft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_istft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_float32, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cond_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cond_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cond_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cond_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_det_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_det_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_det_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_det_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eig_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eig_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eig_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eig_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvals_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvals_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvals_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvals_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvalsh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvalsh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvalsh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvalsh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_householder_product_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_householder_product_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_householder_product_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_householder_product_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_grad_oriented_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_grad_oriented_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_grad_oriented_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_grad_oriented_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_power_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_power_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_power_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_power_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_hermitian_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_hermitian_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_hermitian_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_hermitian_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_hermitian_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_hermitian_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_hermitian_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_hermitian_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_singular_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_singular_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_singular_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_singular_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_qr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_qr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_qr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_qr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_slogdet_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_slogdet_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_slogdet_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_slogdet_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_triangular_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_triangular_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_triangular_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_triangular_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svd_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svd_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svd_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svd_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svdvals_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svdvals_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svdvals_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svdvals_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorinv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorinv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorinv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorinv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorsolve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorsolve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorsolve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorsolve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_normal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_normal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_normal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_normal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp2_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp2_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logdet_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logdet_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logdet_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logdet_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_unpack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_unpack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_unpack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_unpack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_argmin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumprod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_cumsum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_fill_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_log_softmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_log_softmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_log_softmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_log_softmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logaddexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logaddexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logaddexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logaddexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_median_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_median_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_median_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_median_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_softmin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_std_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_sum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_pool2d_with_indices_backward_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_pool2d_with_indices_backward_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_pool2d_with_indices_backward_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_pool2d_with_indices_backward_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_multinomial_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_multinomial_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_multinomial_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_multinomial_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanquantile_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanquantile_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_batch_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_batch_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_batch_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_batch_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_layer_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_layer_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_layer_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_layer_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nextafter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nextafter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nextafter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nextafter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_alpha_dropout_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_alpha_dropout_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_alpha_dropout_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_alpha_dropout_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool3d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_batch_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_batch_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_batch_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_batch_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_with_logits_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_with_logits_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_with_logits_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_celu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_celu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_celu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_celu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_similarity_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_similarity_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_similarity_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_similarity_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cross_entropy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cross_entropy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cross_entropy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cross_entropy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_ctc_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_ctc_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_elu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_elu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_elu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_elu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_bag_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_bag_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_bag_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_bag_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_with_train_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_with_train_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_with_train_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gaussian_nll_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gaussian_nll_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gaussian_nll_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gaussian_nll_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gelu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gelu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gelu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gelu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_glu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_glu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_glu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_glu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_grid_sample_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_grid_sample_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_grid_sample_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_grid_sample_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_group_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_group_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_group_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_group_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardshrink_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardshrink_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardshrink_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardshrink_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardsigmoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardsigmoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardsigmoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardsigmoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardswish_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardswish_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardswish_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardswish_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hinge_embedding_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hinge_embedding_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hinge_embedding_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hinge_embedding_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_huber_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_huber_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_huber_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_huber_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_instance_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_instance_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_instance_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_instance_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_area_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_area_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_area_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_area_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_linear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_linear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_linear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_linear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_trilinear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_trilinear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_trilinear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_trilinear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_kl_div_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_kl_div_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_kl_div_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_kl_div_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_layer_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_layer_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_layer_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_layer_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_leaky_relu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_leaky_relu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_leaky_relu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_leaky_relu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_logsigmoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_logsigmoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_logsigmoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_logsigmoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_grad_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_grad_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_grad_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_grad_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_grad_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_grad_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_grad_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_grad_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_grad_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_grad_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_grad_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_grad_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mish_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mish_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mish_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mish_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mse_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mse_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mse_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mse_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_head_attention_forward_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_head_attention_forward_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_head_attention_forward_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_head_attention_forward_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_soft_margin_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_soft_margin_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_soft_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_nll_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_nll_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_nll_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_nll_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_one_hot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pdist_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pdist_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_prelu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_prelu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_prelu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_prelu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rrelu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rrelu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rrelu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_scaled_dot_product_attention_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_scaled_dot_product_attention_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_scaled_dot_product_attention_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_selu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_selu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_selu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_selu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_complex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_complex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_smooth_l1_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_smooth_l1_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_smooth_l1_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_smooth_l1_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_soft_margin_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_soft_margin_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_soft_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_soft_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softplus_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softplus_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softplus_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softplus_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softshrink_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softshrink_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softshrink_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softshrink_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_nuc_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_nuc_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_nuc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_nuc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_number_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_number_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_number_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_number_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ormqr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ormqr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ormqr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ormqr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pca_lowrank_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pca_lowrank_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pca_lowrank_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pca_lowrank_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pinverse_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pinverse_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pinverse_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pinverse_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polar_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polar_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_qr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_qr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_qr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_qr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_quantile_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_quantile_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_0_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_0_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_3_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_3_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_3_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_neg_3_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_neg_3_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_neg_3_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_bartlett_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_bartlett_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_blackman_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_blackman_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_cosine_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_cosine_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_exponential_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_exponential_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_gaussian_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_gaussian_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_general_cosine_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_general_cosine_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_general_hamming_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_general_hamming_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_hamming_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_hamming_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_hann_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_hann_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_kaiser_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_kaiser_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_nuttall_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_nuttall_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_mm_reduce_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_mm_reduce_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_mm_reduce_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_mm_reduce_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_sampled_addmm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_sampled_addmm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_sampled_addmm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_sampled_addmm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_t_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_t_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_t_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_t_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_t_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_t_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_t_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_t_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_u_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_u_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_u_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_u_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_u_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_u_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_u_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_u_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_erfcx_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_erfcx_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_erfcx_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_erfcx_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_erfcx_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_erfcx_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_erfcx_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_erfcx_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_h_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_h_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_h_cpu_float64, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_list_args_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_list_args_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_list_args_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_list_args_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_list_args_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_list_args_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_split_with_sizes_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sqrt_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sqrt_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sqrt_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sqrt_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sqrt_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sqrt_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sqrt_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sqrt_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sqrt_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sqrt_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sqrt_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sqrt_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_square_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_square_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_square_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_square_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_square_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_square_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_square_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_square_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_square_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_square_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_square_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_square_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_lowrank_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_lowrank_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_lowrank_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_lowrank_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch__scaled_mm_cpu_float8_e4m3fn, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch__scaled_mm_cpu_float8_e4m3fnuz, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch__scaled_mm_cpu_float8_e5m2, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch__scaled_mm_cpu_float8_e5m2fnuz, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triangular_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triangular_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triangular_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triangular_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_indices_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_indices_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_indices_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_indices_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_uint16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_uint32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_uint64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_complex_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_complex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_complex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_real_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_real_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_get_default_device_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_get_default_device_more_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_nn_module_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_set_default_device_cpu, test/test_utils.py::TestCppExtensionUtils::test_cc_compiler_is_ok, test/test_utils.py::TestCppExtensionUtils::test_cpp_compiler_is_ok, test/test_utils.py::TestTraceback::test_basic, test/test_utils.py::TestTraceback::test_captured_traceback, test/test_utils.py::TestTraceback::test_captured_traceback_format_all, test/test_utils.py::TestTraceback::test_captured_traceback_format_all_cached, test/test_utils.py::TestTraceback::test_format_traceback_short, test/test_utils.py::TestTryImport::test_import_existing, test/test_utils.py::TestTryImport::test_import_imported, test/test_utils.py::TestTryImport::test_import_missing, test/test_utils.py::TestDeprecate::test_deprecated
2025-07-17T06:52:44.1793830Z 
2025-07-17T06:52:44.1793990Z Running test_multiprocessing 1/1 ... [2025-07-17 06:52:43.876170]
2025-07-17T06:52:44.1794300Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:52:44.1795050Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_multiprocessing.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:52:43.876472]
2025-07-17T06:55:50.0790410Z 
2025-07-17T06:55:50.0791000Z test_multiprocessing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_multiprocessing_1.1_2a1afc99c25858f7_.log
2025-07-17T06:55:50.0801880Z Running 42 items in this shard: test/test_multiprocessing.py::TestMultiprocessing::test_autograd_errors, test/test_multiprocessing.py::TestMultiprocessing::test_autograd_fine_with_spawn, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_bad_call, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_ipc_deadlock, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_memory_allocation, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_parameter_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_send_many, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_simple, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_small_tensors, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_empty_shared, test/test_multiprocessing.py::TestMultiprocessing::test_empty_tensor_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_empty_tensor_sharing_cuda, test/test_multiprocessing.py::TestMultiprocessing::test_empty_tensor_sharing_meta, test/test_multiprocessing.py::TestMultiprocessing::test_event, test/test_multiprocessing.py::TestMultiprocessing::test_event_handle_exporter, test/test_multiprocessing.py::TestMultiprocessing::test_event_handle_importer, test/test_multiprocessing.py::TestMultiprocessing::test_event_handle_multi_gpu, test/test_multiprocessing.py::TestMultiprocessing::test_event_multiprocess, test/test_multiprocessing.py::TestMultiprocessing::test_fd_pool, test/test_multiprocessing.py::TestMultiprocessing::test_fd_preserve_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_fd_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_fs, test/test_multiprocessing.py::TestMultiprocessing::test_fs_is_shared, test/test_multiprocessing.py::TestMultiprocessing::test_fs_pool, test/test_multiprocessing.py::TestMultiprocessing::test_fs_preserve_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_fs_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_inherit_tensor, test/test_multiprocessing.py::TestMultiprocessing::test_integer_parameter_serialization_cpu, test/test_multiprocessing.py::TestMultiprocessing::test_integer_parameter_serialization_cuda, test/test_multiprocessing.py::TestMultiprocessing::test_is_shared, test/test_multiprocessing.py::TestMultiprocessing::test_is_shared_cuda, test/test_multiprocessing.py::TestMultiprocessing::test_leaf_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_mixed_types_cuda_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_non_leaf_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_parameter_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_rebuild_cuda_tensor, test/test_multiprocessing.py::TestMultiprocessing::test_set_thread_name, test/test_multiprocessing.py::TestMultiprocessing::test_tensor_sharing_meta, test/test_multiprocessing.py::TestMultiprocessing::test_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_wrong_cuda_fork
2025-07-17T06:55:50.0812170Z 
2025-07-17T06:55:50.0812320Z Running test_tensorexpr 1/1 ... [2025-07-17 06:55:50.079441]
2025-07-17T06:55:50.0812630Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:55:50.0813540Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_tensorexpr.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:55:50.079750]
2025-07-17T06:56:02.9327330Z 
2025-07-17T06:56:02.9328550Z test_tensorexpr 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorexpr_1.1_1e074bd8b88d2312_.log
2025-07-17T06:56:02.9342570Z Running 74 items in this shard: test/test_tensorexpr.py::TestTensorExprFuser::test_add_const_rhs, test/test_tensorexpr.py::TestTensorExprFuser::test_add_sub, test/test_tensorexpr.py::TestTensorExprFuser::test_alias_analysis_input_and_module, test/test_tensorexpr.py::TestTensorExprFuser::test_alias_analysis_inputs, test/test_tensorexpr.py::TestTensorExprFuser::test_alias_analysis_module, test/test_tensorexpr.py::TestTensorExprFuser::test_all_combos, test/test_tensorexpr.py::TestTensorExprFuser::test_alpha, test/test_tensorexpr.py::TestTensorExprFuser::test_binary_ops, test/test_tensorexpr.py::TestTensorExprFuser::test_bitwise_ops, test/test_tensorexpr.py::TestTensorExprFuser::test_broadcast, test/test_tensorexpr.py::TestTensorExprFuser::test_broadcast3, test/test_tensorexpr.py::TestTensorExprFuser::test_broadcast_2, test/test_tensorexpr.py::TestTensorExprFuser::test_broadcast_big2, test/test_tensorexpr.py::TestTensorExprFuser::test_cat, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_empty_tensors, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_negative_dim, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_only, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_promote_inputs, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_with_constant_dim, test/test_tensorexpr.py::TestTensorExprFuser::test_char, test/test_tensorexpr.py::TestTensorExprFuser::test_chunk, test/test_tensorexpr.py::TestTensorExprFuser::test_clamp, test/test_tensorexpr.py::TestTensorExprFuser::test_constant, test/test_tensorexpr.py::TestTensorExprFuser::test_double, test/test_tensorexpr.py::TestTensorExprFuser::test_double_intrinsics, test/test_tensorexpr.py::TestTensorExprFuser::test_dynamic_shape, test/test_tensorexpr.py::TestTensorExprFuser::test_easy, test/test_tensorexpr.py::TestTensorExprFuser::test_eq, test/test_tensorexpr.py::TestTensorExprFuser::test_exp_pow, test/test_tensorexpr.py::TestTensorExprFuser::test_four_arg, test/test_tensorexpr.py::TestTensorExprFuser::test_ge, test/test_tensorexpr.py::TestTensorExprFuser::test_gt, test/test_tensorexpr.py::TestTensorExprFuser::test_guard_fails, test/test_tensorexpr.py::TestTensorExprFuser::test_half_bn_relu, test/test_tensorexpr.py::TestTensorExprFuser::test_half_gelu, test/test_tensorexpr.py::TestTensorExprFuser::test_int64_promotion, test/test_tensorexpr.py::TestTensorExprFuser::test_int_output, test/test_tensorexpr.py::TestTensorExprFuser::test_le, test/test_tensorexpr.py::TestTensorExprFuser::test_loop, test/test_tensorexpr.py::TestTensorExprFuser::test_lt, test/test_tensorexpr.py::TestTensorExprFuser::test_mask, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max_reduction, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max_reduction2, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max_reduction_dim1, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max_reduction_dim1_2, test/test_tensorexpr.py::TestTensorExprFuser::test_multi_rand, test/test_tensorexpr.py::TestTensorExprFuser::test_multioutput, test/test_tensorexpr.py::TestTensorExprFuser::test_multiple_outputs, test/test_tensorexpr.py::TestTensorExprFuser::test_nans, test/test_tensorexpr.py::TestTensorExprFuser::test_ne, test/test_tensorexpr.py::TestTensorExprFuser::test_promotion, test/test_tensorexpr.py::TestTensorExprFuser::test_propagated_mem_layout, test/test_tensorexpr.py::TestTensorExprFuser::test_rand_like, test/test_tensorexpr.py::TestTensorExprFuser::test_rank_two, test/test_tensorexpr.py::TestTensorExprFuser::test_relu, test/test_tensorexpr.py::TestTensorExprFuser::test_remainder, test/test_tensorexpr.py::TestTensorExprFuser::test_reps, test/test_tensorexpr.py::TestTensorExprFuser::test_round_2, test/test_tensorexpr.py::TestTensorExprFuser::test_scalar, test/test_tensorexpr.py::TestTensorExprFuser::test_short, test/test_tensorexpr.py::TestTensorExprFuser::test_simple_add, test/test_tensorexpr.py::TestTensorExprFuser::test_sin_pow, test/test_tensorexpr.py::TestTensorExprFuser::test_slice, test/test_tensorexpr.py::TestTensorExprFuser::test_sliced_stride, test/test_tensorexpr.py::TestTensorExprFuser::test_softmax_cpu, test/test_tensorexpr.py::TestTensorExprFuser::test_softmax_cuda, test/test_tensorexpr.py::TestTensorExprFuser::test_strided_output_preserved, test/test_tensorexpr.py::TestTensorExprFuser::test_three_arg, test/test_tensorexpr.py::TestTensorExprFuser::test_three_arg2, test/test_tensorexpr.py::TestTensorExprFuser::test_transpose, test/test_tensorexpr.py::TestTensorExprFuser::test_unary_ops, test/test_tensorexpr.py::TestTensorExprFuser::test_unsqueeze, test/test_tensorexpr.py::TestTensorExprFuser::test_where
2025-07-17T06:56:02.9355980Z 
2025-07-17T06:56:02.9356130Z Running test_jit_disabled 1/1 ... [2025-07-17 06:56:02.933130]
2025-07-17T06:56:02.9356420Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:56:02.9357270Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_jit_disabled.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:56:02.933409]
2025-07-17T06:56:04.9273700Z 
2025-07-17T06:56:04.9274290Z test_jit_disabled 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_disabled_1.1_6a2d3682eda79545_.log
2025-07-17T06:56:04.9275270Z Running 3 items in this shard: test/test_jit_disabled.py::TestJitDisabled::test_attribute, test/test_jit_disabled.py::TestJitDisabled::test_recursive_script, test/test_jit_disabled.py::TestJitDisabled::test_script_module_construction
2025-07-17T06:56:04.9275890Z 
2025-07-17T06:56:04.9277060Z Running test_cpp_extensions_mtia_backend 1/1 ... [2025-07-17 06:56:04.927654]
2025-07-17T06:56:04.9277360Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:56:04.9280390Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_cpp_extensions_mtia_backend.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:56:04.927926]
2025-07-17T06:56:06.6701760Z 
2025-07-17T06:56:06.6702380Z test_cpp_extensions_mtia_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_mtia_backend_1.1_e6d71b41bebe5ce4_.log
2025-07-17T06:56:06.6704660Z Running 5 items in this shard: test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_device_context, test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_get_device_module, test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_stream_basic, test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_stream_context, test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_stream_context_different_device
2025-07-17T06:56:06.6706280Z 
2025-07-17T06:56:06.6706460Z Running test_cpp_extensions_stream_and_event 1/1 ... [2025-07-17 06:56:06.670533]
2025-07-17T06:56:06.6706790Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:56:06.6709170Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_cpp_extensions_stream_and_event.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:56:06.670813]
2025-07-17T06:56:08.4154240Z 
2025-07-17T06:56:08.4154950Z test_cpp_extensions_stream_and_event 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_stream_and_event_1.1_4db52eceacea0efe_.log
2025-07-17T06:56:08.4155880Z Running 1 items in this shard: test/test_cpp_extensions_stream_and_event.py::TestCppExtensionStreamAndEvent::test_stream_event
2025-07-17T06:56:08.4156290Z 
2025-07-17T06:56:08.4158410Z Running test_dispatch 1/1 ... [2025-07-17 06:56:08.415775]
2025-07-17T06:56:08.4158700Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:56:08.4161660Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_dispatch.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:56:08.416059]
2025-07-17T06:56:28.7120580Z 
2025-07-17T06:56:28.7127760Z test_dispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_dispatch_1.1_159bafba3d0917a8_.log
2025-07-17T06:56:28.7134310Z Running 32 items in this shard: test/test_dispatch.py::TestDispatch::test_all_invariants, test/test_dispatch.py::TestDispatch::test_computed_table, test/test_dispatch.py::TestDispatch::test_computed_table_with_ambiguous_autogradother, test/test_dispatch.py::TestDispatch::test_computed_table_with_autograd, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_autograd_defaultbackend, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_autograd_math, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_autograd_math_defaultbackend, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_defaultbackend, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_math, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_math_autogradcpu_fallthrough, test/test_dispatch.py::TestDispatch::test_computed_table_with_math, test/test_dispatch.py::TestDispatch::test_def, test/test_dispatch.py::TestDispatch::test_def_impl_schema_mismatch, test/test_dispatch.py::TestDispatch::test_def_only, test/test_dispatch.py::TestDispatch::test_def_with_explicit_alias, test/test_dispatch.py::TestDispatch::test_def_with_inference, test/test_dispatch.py::TestDispatch::test_dispatch_print_registrations_for_dispatch_key_invalid, test/test_dispatch.py::TestDispatch::test_find_dangling_impls, test/test_dispatch.py::TestDispatch::test_find_dangling_impls_ext, test/test_dispatch.py::TestDispatch::test_impl_only, test/test_dispatch.py::TestDispatch::test_multiple_def_alias_defaulting, test/test_dispatch.py::TestDispatch::test_multiple_def_alias_mismatch, test/test_dispatch.py::TestDispatch::test_multiple_def_error, test/test_dispatch.py::TestDispatch::test_multiple_fallback, test/test_dispatch.py::TestDispatch::test_overwrite_math, test/test_dispatch.py::TestPythonDispatcher::test_autogradother, test/test_dispatch.py::TestPythonDispatcher::test_basic, test/test_dispatch.py::TestPythonDispatcher::test_defaultbackend_autogradcpu, test/test_dispatch.py::TestPythonDispatcher::test_defaultbackend_math, test/test_dispatch.py::TestPythonDispatcher::test_duplicate_registrations, test/test_dispatch.py::TestPythonDispatcher::test_math_autogradcpu, test/test_dispatch.py::TestPythonDispatcher::test_quantized_structured_not_implemented
2025-07-17T06:56:28.7140540Z 
2025-07-17T06:56:28.7140680Z Running test_python_dispatch 1/1 ... [2025-07-17 06:56:28.712396]
2025-07-17T06:56:28.7140970Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:56:28.7141760Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_python_dispatch.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:56:28.712667]
2025-07-17T06:56:34.5525160Z 
2025-07-17T06:56:34.5525740Z test_python_dispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_python_dispatch_1.1_5c692d6e6e14d249_.log
2025-07-17T06:56:34.5556200Z Running 118 items in this shard: test/test_python_dispatch.py::TestDispatcherPythonBindings::test_call_boxed, test/test_python_dispatch.py::TestPythonRegistration::test_alias_analysis, test/test_python_dispatch.py::TestPythonRegistration::test_create_new_library, test/test_python_dispatch.py::TestPythonRegistration::test_create_new_library_fragment_no_existing, test/test_python_dispatch.py::TestPythonRegistration::test_create_new_library_fragment_with_existing, test/test_python_dispatch.py::TestPythonRegistration::test_dispatchkeyset_eq, test/test_python_dispatch.py::TestPythonRegistration::test_dispatchkeyset_pickle, test/test_python_dispatch.py::TestPythonRegistration::test_error_for_unsupported_ns_or_kind, test/test_python_dispatch.py::TestPythonRegistration::test_error_if_fn_not_callable, test/test_python_dispatch.py::TestPythonRegistration::test_extend_library_with_dispatch_key_arg, test/test_python_dispatch.py::TestPythonRegistration::test_fallback, test/test_python_dispatch.py::TestPythonRegistration::test_fallback_fallthrough, test/test_python_dispatch.py::TestPythonRegistration::test_fallback_keyset, test/test_python_dispatch.py::TestPythonRegistration::test_fallthrough_for_dense_key_with_meta_in_tls, test/test_python_dispatch.py::TestPythonRegistration::test_finalizer, test/test_python_dispatch.py::TestPythonRegistration::test_override_aten_ops_with_multiple_libraries, test/test_python_dispatch.py::TestPythonRegistration::test_override_cpu_sum, test/test_python_dispatch.py::TestPythonRegistration::test_override_cuda_with_jiterator, test/test_python_dispatch.py::TestPythonRegistration::test_register_fallthrough, test/test_python_dispatch.py::TestPythonRegistration::test_returning_symint, test/test_python_dispatch.py::TestPythonDispatch::test_all_same_mode, test/test_python_dispatch.py::TestPythonDispatch::test_autograd_in_attr, test/test_python_dispatch.py::TestPythonDispatch::test_basic, test/test_python_dispatch.py::TestPythonDispatch::test_capture_logs_with_torch_dispatch_mode, test/test_python_dispatch.py::TestPythonDispatch::test_construct_int_tensor, test/test_python_dispatch.py::TestPythonDispatch::test_custom_autograd, test/test_python_dispatch.py::TestPythonDispatch::test_custom_dispatch_mode_not_supports_higher_order_operators, test/test_python_dispatch.py::TestPythonDispatch::test_custom_dispatch_mode_supports_higher_order_operators, test/test_python_dispatch.py::TestPythonDispatch::test_custom_size_policy_dynamic_shapes, test/test_python_dispatch.py::TestPythonDispatch::test_data_ptr_respects_numel_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_deepcopy_non_wrapper_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_deepcopy_wrapper_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_deepcopy_wrapper_subclass_with_clone_returning_different_type, test/test_python_dispatch.py::TestPythonDispatch::test_detach_appears_twice_when_called_once, test/test_python_dispatch.py::TestPythonDispatch::test_device_slowpath, test/test_python_dispatch.py::TestPythonDispatch::test_dim_slowpath, test/test_python_dispatch.py::TestPythonDispatch::test_dispatch_super_call, test/test_python_dispatch.py::TestPythonDispatch::test_dispatch_super_call_list_arg, test/test_python_dispatch.py::TestPythonDispatch::test_dispatch_super_dont_autograd, test/test_python_dispatch.py::TestPythonDispatch::test_error_using_class_method_on_mode, test/test_python_dispatch.py::TestPythonDispatch::test_exception_handling, test/test_python_dispatch.py::TestPythonDispatch::test_fancy_strides, test/test_python_dispatch.py::TestPythonDispatch::test_format, test/test_python_dispatch.py::TestPythonDispatch::test_get_cur_mode, test/test_python_dispatch.py::TestPythonDispatch::test_get_mode_stack, test/test_python_dispatch.py::TestPythonDispatch::test_index_put_where_only_index_is_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_invalid_ret, test/test_python_dispatch.py::TestPythonDispatch::test_is_contiguous_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_kwarg_only, test/test_python_dispatch.py::TestPythonDispatch::test_kwarg_only_and_positional_default, test/test_python_dispatch.py::TestPythonDispatch::test_layout_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_like, test/test_python_dispatch.py::TestPythonDispatch::test_list_ret, test/test_python_dispatch.py::TestPythonDispatch::test_make_fx_with_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_make_subclass_with_modes, test/test_python_dispatch.py::TestPythonDispatch::test_make_wrapper_subclass_noalloc, test/test_python_dispatch.py::TestPythonDispatch::test_make_wrapper_subclass_propagates_metadata, test/test_python_dispatch.py::TestPythonDispatch::test_maybe_tuple_bug, test/test_python_dispatch.py::TestPythonDispatch::test_mode_detection, test/test_python_dispatch.py::TestPythonDispatch::test_mode_with_make_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_multiple_ops_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_nested_push_logging_tensor_mode, test/test_python_dispatch.py::TestPythonDispatch::test_nesting_same_mode, test/test_python_dispatch.py::TestPythonDispatch::test_new_ones, test/test_python_dispatch.py::TestPythonDispatch::test_none_wrapping, test/test_python_dispatch.py::TestPythonDispatch::test_notimplemented_mode, test/test_python_dispatch.py::TestPythonDispatch::test_optional_tensor_list, test/test_python_dispatch.py::TestPythonDispatch::test_out, test/test_python_dispatch.py::TestPythonDispatch::test_produce_real_type, test/test_python_dispatch.py::TestPythonDispatch::test_record_stream, test/test_python_dispatch.py::TestPythonDispatch::test_return_and_correct_aliasing_gives_correct_stride, test/test_python_dispatch.py::TestPythonDispatch::test_return_stream, test/test_python_dispatch.py::TestPythonDispatch::test_set_data, test/test_python_dispatch.py::TestPythonDispatch::test_shallow_copy_and_detach, test/test_python_dispatch.py::TestPythonDispatch::test_sizes_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_standard_is_not_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_storage, test/test_python_dispatch.py::TestPythonDispatch::test_storage_can_be_converted_to_python_object, test/test_python_dispatch.py::TestPythonDispatch::test_strides_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_subclass_autograd_device_check, test/test_python_dispatch.py::TestPythonDispatch::test_subclass_creation, test/test_python_dispatch.py::TestPythonDispatch::test_subclass_priority, test/test_python_dispatch.py::TestPythonDispatch::test_sym_sizes_strides_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_tolist_numpy_with_torch_dispatch_mode, test/test_python_dispatch.py::TestPythonDispatch::test_torch_dispatch_mode_basic, test/test_python_dispatch.py::TestPythonDispatch::test_torch_dispatch_mode_respects_no_dispatch, test/test_python_dispatch.py::TestPythonDispatch::test_torch_dispatch_mode_subclass_priority, test/test_python_dispatch.py::TestPythonDispatch::test_torch_dispatch_mode_unrelated_tensors, test/test_python_dispatch.py::TestPythonDispatch::test_version, test/test_python_dispatch.py::TestPythonDispatch::test_view_returns_alias_under_torch_dispatch, test/test_python_dispatch.py::TestPythonDispatch::test_with_mode_created_separately, test/test_python_dispatch.py::TestPythonDispatch::test_with_nested_modes, test/test_python_dispatch.py::TestPythonDispatch::test_wrapper_subclass_extra_dispatch_keys, test/test_python_dispatch.py::TestPythonDispatch::test_wrapper_subclass_multiprocessing_preserves_dtype, test/test_python_dispatch.py::TestPythonDispatch::test_wrapper_subclass_reentrant_dispatch_with_mode, test/test_python_dispatch.py::TestPythonDispatch::test_wrapper_subclass_serializes, test/test_python_dispatch.py::TestPythonDispatcher::test_basic, test/test_python_dispatch.py::TestPythonDispatcher::test_lstsq, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_cat_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_conv2d_cpu, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyCatCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyCubeCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyMulCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyMulScalarCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyNMSCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyNonzeroCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpySortCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpySplitCopyCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyTakeCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyViewCopyCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_fft_fft2_cpu, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_mul_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_native_batch_norm_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_out_op_cpu, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_split_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_split_list_args_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_view_cpu_float32
2025-07-17T06:56:34.5585830Z 
2025-07-17T06:56:34.5585970Z Running test_autograd_fallback 1/1 ... [2025-07-17 06:56:34.552944]
2025-07-17T06:56:34.5586260Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:56:34.5587060Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_autograd_fallback.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:56:34.553236]
2025-07-17T06:56:36.4894350Z 
2025-07-17T06:56:36.4895420Z test_autograd_fallback 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_autograd_fallback_1.1_23621326865d6dc5_.log
2025-07-17T06:56:36.4903180Z Running 28 items in this shard: test/test_autograd_fallback.py::TestAutogradFallback::test_autograd_function_registered_to_cpu_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_autograd_function_registered_to_cpu_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_base_does_not_require_grad_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_base_does_not_require_grad_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_composite_registered_to_cpu_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_composite_registered_to_cpu_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_cpu_return_self_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_cpu_return_self_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_inplace_autograd_function_registered_to_cpu_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_inplace_autograd_function_registered_to_cpu_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_inplace_on_tensor_that_does_not_require_grad_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_inplace_on_tensor_that_does_not_require_grad_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_no_autograd_kernel_inplace_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_no_autograd_kernel_inplace_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_no_autograd_kernel_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_no_autograd_kernel_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_no_grad_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_no_grad_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_post_autograd_returns_leaf_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_post_autograd_returns_leaf_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_post_autograd_returns_mix_of_requires_grad_tensors_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_post_autograd_returns_mix_of_requires_grad_tensors_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_supports_tensor_lists_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_supports_tensor_lists_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_undefined_grads_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_undefined_grads_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_undefined_inputs_outputs_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_undefined_inputs_outputs_mode_warn
2025-07-17T06:56:36.4910340Z 
2025-07-17T06:56:36.4910490Z Running test_cuda_nvml_based_avail 1/1 ... [2025-07-17 06:56:36.489756]
2025-07-17T06:56:36.4910780Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:56:36.4911570Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_cuda_nvml_based_avail.py', '--shard-id=1', '--num-shards=1', '-v', '--subprocess', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:56:36.490007]
2025-07-17T06:56:38.1941330Z 
2025-07-17T06:56:38.1941970Z test_cuda_nvml_based_avail 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_nvml_based_avail_1.1_82950f51a68e9bd2_.log
2025-07-17T06:56:38.1942490Z Running 0 items in this shard:
2025-07-17T06:56:38.1942610Z 
2025-07-17T06:56:38.1944890Z Running test_tensor_creation_ops 1/1 ... [2025-07-17 06:56:38.194408]
2025-07-17T06:56:38.1945190Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:56:38.1947570Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_tensor_creation_ops.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:56:38.194663]
2025-07-17T06:56:48.0070580Z 
2025-07-17T06:56:48.0071160Z test_tensor_creation_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensor_creation_ops_1.1_a35229619fdbc723_.log
2025-07-17T06:56:48.0206820Z Running 641 items in this shard: test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_device_vs_cpu_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_device_vs_cpu_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_device_vs_cpu_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_device_vs_cpu_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_inference_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_lowp_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_lowp_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_as_strided_neg_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_as_tensor_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_block_diag_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_block_diag_scipy_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cartesian_prod_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat2_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat2_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat2_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_all_dtypes_and_devices_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_big_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_empty_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_empty_legacy_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_in_channels_last_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_mem_overlap_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_channels_last_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_uint16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_uint32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_uint64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_memory_format_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_preserve_channels_last_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_stack_cross_devices_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_combinations_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_complex_type_conversions_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_concat_empty_list_error_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_constructor_device_legacy_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_constructor_dtypes_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_ctor_with_numpy_array_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_device_rounding_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_device_rounding_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_diag_embed_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_diagflat_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dsplit_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dsplit_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dsplit_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_dstack_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_empty_full_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_empty_overflow_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_empty_strided_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_empty_tensor_props_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_eye_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_fill_all_dtypes_and_devices_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_finite_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_finite_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_finite_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_finite_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_finite_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_finite_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_nonfinite_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_nonfinite_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_nonfinite_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_nonfinite_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_nonfinite_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_float_to_int_conversion_nonfinite_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_from_file_shared_False_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_from_file_shared_True_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_full_inference_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_full_inference_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_full_inference_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_full_out_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hsplit_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hsplit_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hsplit_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_hstack_column_stack_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_window_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_window_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_window_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_window_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_kaiser_window_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_large_linspace_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_large_linspace_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_like_fn_stride_proparation_vs_tensoriterator_unary_op_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linlogspace_mem_overlap_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_deduction_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_device_vs_cpu_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_device_vs_cpu_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_device_vs_cpu_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_device_vs_cpu_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_device_vs_cpu_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_device_vs_cpu_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_special_steps_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_special_steps_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_special_steps_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_special_steps_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_special_steps_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_special_steps_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_complex_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_integral_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_integral_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_integral_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_integral_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_linspace_vs_numpy_integral_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_base2_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_base2_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_deduction_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_device_vs_cpu_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_device_vs_cpu_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_special_steps_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_special_steps_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_vs_numpy_complex_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_vs_numpy_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_logspace_vs_numpy_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_default_indexing_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_empty_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_ij_indexing_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_ij_indexing_is_default_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_inconsistent_device_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_inconsistent_dtype_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_non_1d_tensor_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_unsupported_indexing_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_vs_numpy_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_warns_if_no_indexing_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_meshgrid_xy_indexing_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_new_empty_strided_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_new_methods_requires_grad_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_new_tensor_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_new_tensor_device_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_offset_scalar_cast_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_ones_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_bool_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_default_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_bool_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_uint16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_uint32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_from_to_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_uint16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_uint32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_full_range_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_uint16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_uint32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_random_to_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_range_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_range_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_range_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_range_factories_64bit_indexing_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_range_warning_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_repeat_interleave_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_roll_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_bartlett_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_bartlett_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_bartlett_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_blackman_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_blackman_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_blackman_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hamming_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hamming_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hamming_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hann_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hann_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hann_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_bartlett_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_bartlett_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_blackman_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_blackman_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_cosine_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_cosine_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_hamming_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_hamming_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_hann_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_hann_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_nuttall_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_nuttall_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_simple_scalar_cast_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_stack_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_stack_out_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_storage_filename_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_strided_mismatched_stride_shape_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_ctor_device_inference_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_device_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factories_empty_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_copy_var_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_gpu_type_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_gpu_type_inference_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_type_inference_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_from_non_writable_numpy_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_from_sequence_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_out_dtype_error_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_out_dtype_error_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_same_dtype_error_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_same_dtype_error_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_polar_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_polar_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_unpack_double_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_unpack_double_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vsplit_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vsplit_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vsplit_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_out_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_normal_cpu_float32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_normal_cpu_float64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_normal_std_error_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_complex128, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_complex32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_complex64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_float32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_float64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randint_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randint_distribution_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randint_inference_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_bfloat16, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_complex128, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_complex32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_complex64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_float16, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_float32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_float64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_random_neg_values_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randperm_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randperm_device_compatibility_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randperm_large_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_uniform_from_to_cpu_float16, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_uniform_from_to_cpu_float32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_uniform_from_to_cpu_float64, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_empty_like_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_full_like_inference_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_ones_like_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_ones_like_multiple_device_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_zeros_like_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_zeros_like_multiple_device_cpu, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_byte_to_int_cpu, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_uint16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_uint32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_uint64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_astensor_consistency_cpu, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_uint16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_uint32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_uint64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_default_device_cpu, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_device_without_index_cpu, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_numpy_scalars_cpu, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_retain_autograd_history_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_retain_autograd_history_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_unsupported_alias_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_unsupported_alias_mult_devices_cpu_float32
2025-07-17T06:56:48.0336900Z 
2025-07-17T06:56:48.0337020Z Running test_cuda_trace 1/1 ... [2025-07-17 06:56:48.007707]
2025-07-17T06:56:48.0337260Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:56:48.0338000Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_cuda_trace.py', '--shard-id=1', '--num-shards=1', '-v', '--subprocess', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:56:48.007948]
2025-07-17T06:56:49.6971050Z 
2025-07-17T06:56:49.6971560Z test_cuda_trace 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_trace_1.1_321ac020137c74a1_.log
2025-07-17T06:56:49.6972050Z Running 0 items in this shard:
2025-07-17T06:56:49.6972180Z 
2025-07-17T06:56:49.6974690Z Running test_autocast 1/1 ... [2025-07-17 06:56:49.697394]
2025-07-17T06:56:49.6974940Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:56:49.6977630Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_autocast.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:56:49.697656]
2025-07-17T06:56:52.0576710Z 
2025-07-17T06:56:52.0577390Z test_autocast 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_autocast_1.1_c3de62423a563fd0_.log
2025-07-17T06:56:52.0582190Z Running 20 items in this shard: test/test_autocast.py::TestAutocastCPU::test_autocast_disabled_with_fp32_dtype, test/test_autocast.py::TestAutocastCPU::test_autocast_methods_expect_builtin_promote, test/test_autocast.py::TestAutocastCPU::test_autocast_nn_16, test/test_autocast.py::TestAutocastCPU::test_autocast_nn_fp32, test/test_autocast.py::TestAutocastCPU::test_autocast_rnn, test/test_autocast.py::TestAutocastCPU::test_autocast_torch_16, test/test_autocast.py::TestAutocastCPU::test_autocast_torch_expect_builtin_promote, test/test_autocast.py::TestAutocastCPU::test_autocast_torch_fp32, test/test_autocast.py::TestAutocastCPU::test_autocast_torch_need_autocast_promote, test/test_autocast.py::TestAutocastCPU::test_cpu_autocast_deprecated_warning, test/test_autocast.py::TestAutocastCPU::test_generic_autocast, test/test_autocast.py::TestAutocastGPU::test_autocast_prioritize, test/test_autocast.py::TestAutocastGPU::test_cache_disabled, test/test_autocast.py::TestAutocastGPU::test_cast_cache_is_global, test/test_autocast.py::TestAutocastMPS::test_cast_cache_is_global, test/test_autocast.py::TestAutocastMPS::test_mps_autocast_bfloat16_supported, test/test_autocast.py::TestAutocastMPS::test_mps_autocast_error_message, test/test_autocast.py::TestTorchAutocast::test_autocast_fast_dtype, test/test_autocast.py::TestTorchAutocast::test_invalid_device, test/test_autocast.py::TestTorchAutocast::test_non_string_device
2025-07-17T06:56:52.0586670Z 
2025-07-17T06:56:52.0586880Z Running inductor/test_distributed_patterns 1/1 ... [2025-07-17 06:56:52.058047]
2025-07-17T06:56:52.0587250Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:56:52.0588470Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_distributed_patterns.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:56:52.058346]
2025-07-17T06:56:54.2197840Z 
2025-07-17T06:56:54.2198510Z inductor/test_distributed_patterns 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_distributed_patterns_1.1_872de8765be72a34_.log
2025-07-17T06:56:54.2199310Z 
2025-07-17T06:56:54.2201330Z Running dynamo/test_fake_distributed 1/1 ... [2025-07-17 06:56:54.220048]
2025-07-17T06:56:54.2201630Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:56:54.2203820Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_fake_distributed.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:56:54.220304]
2025-07-17T06:56:56.0234920Z 
2025-07-17T06:56:56.0235510Z dynamo/test_fake_distributed 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_fake_distributed_1.1_ad5d85e6259a38cc_.log
2025-07-17T06:56:56.0236290Z Running 1 items in this shard: test/dynamo/test_fake_distributed.py::TestFakeDistributed::test_all_to_all_single_autograd
2025-07-17T06:56:56.0236630Z 
2025-07-17T06:56:56.0238400Z Running test_cpp_extensions_jit 1/1 ... [2025-07-17 06:56:56.023786]
2025-07-17T06:56:56.0238680Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:56:56.0241210Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_cpp_extensions_jit.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:56:56.024035]
2025-07-17T06:58:40.7865570Z 
2025-07-17T06:58:40.7867240Z test_cpp_extensions_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_jit_1.1_3cbdc639e1761d76_.log
2025-07-17T06:58:40.7875520Z Running 34 items in this shard: test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_aoti_torch_call_dispatcher, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_autograd_from_cpp, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_compilation_error_formatting, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cpp_frontend_module_has_same_output_as_python, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cpp_frontend_module_has_up_to_date_attributes, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cpp_frontend_module_python_inter_op, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cpp_frontend_module_python_inter_op_with_cuda, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cuda_arch_flags_default_gencode, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cuda_arch_flags_non_default_gencode, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cuda_pluggable_allocator_include, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_custom_compound_op_autograd, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_custom_functorch_error, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_gen_extension_h_pch, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_half_support, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_custom_op_cuda, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_cuda, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_multiple_sources_and_no_functions, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_throws_when_functions_is_bad, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_with_functions_as_dict, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_with_functions_as_list, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_xpu, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_compile_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_cuda_archflags, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_cuda_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_cudnn_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_xpu_archlists, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_xpu_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_lenient_flag_handling_in_jit_extensions, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_load_with_non_platform_default_encoding, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_mps_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_reload_jit_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_returns_shared_library_path_when_is_python_module_is_true, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_set_default_type_also_changes_aten_default_type, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_warning
2025-07-17T06:58:40.7883400Z 
2025-07-17T06:58:40.7883540Z Running test_cuda_primary_ctx 1/1 ... [2025-07-17 06:58:40.786909]
2025-07-17T06:58:40.7883800Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:58:40.7884570Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_cuda_primary_ctx.py', '--shard-id=1', '--num-shards=1', '-v', '--subprocess', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:58:40.787168]
2025-07-17T06:58:42.5890570Z 
2025-07-17T06:58:42.5891070Z test_cuda_primary_ctx 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_primary_ctx_1.1_14413bbe674c70bd_.log
2025-07-17T06:58:42.5891550Z Running 0 items in this shard:
2025-07-17T06:58:42.5891680Z 
2025-07-17T06:58:42.5894300Z Running test_torch 1/1 ... [2025-07-17 06:58:42.589359]
2025-07-17T06:58:42.5894570Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:58:42.5897300Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_torch.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:58:42.589626]
2025-07-17T06:58:49.9705610Z 
2025-07-17T06:58:49.9706130Z test_torch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_torch_1.1_07e4bdc95ab35519_.log
2025-07-17T06:58:49.9891060Z Running 1045 items in this shard: test/test_torch.py::TestBasicVitalSigns::test_basic_vitals, test/test_torch.py::TestBasicVitalSigns::test_basic_vitals_read_write, test/test_torch.py::TestBasicVitalSigns::test_dataloader_vitals, test/test_torch.py::TestTorch::test_RNGState, test/test_torch.py::TestTorch::test_RNGStateAliasing, test/test_torch.py::TestTorch::test_RNG_after_pickle, test/test_torch.py::TestTorch::test_Size, test/test_torch.py::TestTorch::test_Size_concat_non_tuple_sequence, test/test_torch.py::TestTorch::test_Size_concat_wildcard, test/test_torch.py::TestTorch::test_Size_iter, test/test_torch.py::TestTorch::test_Size_scalar, test/test_torch.py::TestTorch::test_add_meta_scalar, test/test_torch.py::TestTorch::test_allow_tensor_metadata_change, test/test_torch.py::TestTorch::test_apply, test/test_torch.py::TestTorch::test_as_subclass, test/test_torch.py::TestTorch::test_assert_async, test/test_torch.py::TestTorch::test_backward_hooks_traverse, test/test_torch.py::TestTorch::test_batch_norm_cpu_inference, test/test_torch.py::TestTorch::test_bf16_supported_on_cpu, test/test_torch.py::TestTorch::test_bmm_multithreaded, test/test_torch.py::TestTorch::test_boxMullerState, test/test_torch.py::TestTorch::test_cat_neg_dim, test/test_torch.py::TestTorch::test_check, test/test_torch.py::TestTorch::test_chunk_neg_dim, test/test_torch.py::TestTorch::test_conj_neg_tolist, test/test_torch.py::TestTorch::test_conj_physical_meta_stride, test/test_torch.py::TestTorch::test_contains, test/test_torch.py::TestTorch::test_copy_broadcast, test/test_torch.py::TestTorch::test_copy_dtypes, test/test_torch.py::TestTorch::test_copy_float16, test/test_torch.py::TestTorch::test_copy_many_to_one, test/test_torch.py::TestTorch::test_copy_transpose, test/test_torch.py::TestTorch::test_cuda_not_built, test/test_torch.py::TestTorch::test_cummax_neg_dim, test/test_torch.py::TestTorch::test_cummin_neg_dim, test/test_torch.py::TestTorch::test_cumprod_neg_dim, test/test_torch.py::TestTorch::test_cumsum_neg_dim, test/test_torch.py::TestTorch::test_cxx_flags, test/test_torch.py::TestTorch::test_data_ptr_of_empty_tensor_with_storage, test/test_torch.py::TestTorch::test_data_ptr_of_empty_view_with_storage, test/test_torch.py::TestTorch::test_deepcopy_gradient, test/test_torch.py::TestTorch::test_deepcopy_parameter, test/test_torch.py::TestTorch::test_deterministic_fill_uninitialized_memory, test/test_torch.py::TestTorch::test_deterministic_flag, test/test_torch.py::TestTorch::test_device, test/test_torch.py::TestTorch::test_dim_order, test/test_torch.py::TestTorch::test_dir, test/test_torch.py::TestTorch::test_doc, test/test_torch.py::TestTorch::test_doc_template, test/test_torch.py::TestTorch::test_dot_data_use, test/test_torch.py::TestTorch::test_dtype_is_signed, test/test_torch.py::TestTorch::test_element_size, test/test_torch.py::TestTorch::test_empty_meta, test/test_torch.py::TestTorch::test_empty_storage_view, 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test/test_torch.py::TestTorch::test_sobolengine_fast_forward_scrambled, test/test_torch.py::TestTorch::test_sobolengine_first_point, test/test_torch.py::TestTorch::test_sobolengine_high_dim, test/test_torch.py::TestTorch::test_sobolengine_raise, test/test_torch.py::TestTorch::test_sobolengine_reset, test/test_torch.py::TestTorch::test_sobolengine_reset_scrambled, test/test_torch.py::TestTorch::test_sort_neg_dim, test/test_torch.py::TestTorch::test_split_neg_dim, test/test_torch.py::TestTorch::test_split_with_sizes_copy_out, test/test_torch.py::TestTorch::test_squeeze_neg_dim, test/test_torch.py::TestTorch::test_std_neg_dim, test/test_torch.py::TestTorch::test_storage_base_init, test/test_torch.py::TestTorch::test_storage_base_new, test/test_torch.py::TestTorch::test_storage_byteswap, test/test_torch.py::TestTorch::test_storage_casts, test/test_torch.py::TestTorch::test_storage_cycle_via_dict, test/test_torch.py::TestTorch::test_storage_cycle_via_slots, 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test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_cuda_errors_with_cpu_scalars_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_float32, 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test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_addcdiv_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_addcmul_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_atan2_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_copy_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_dist_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_div_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_eq_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_fmod_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_ge_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_gt_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_le_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_lerp_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_lt_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_map2_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_map_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_masked_fill_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_masked_scatter_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_masked_select_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_max_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_min_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_mul_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_ne_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_pow_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_remainder_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_sub_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_bool, 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test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxPool3d_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool1d_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool1d_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool1d_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool2d_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool2d_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool2d_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool3d_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool3d_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_nondeterministic_alert_MaxUnpool3d_cpu_float64, 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test/test_torch.py::TestTorchDeviceTypeCPU::test_params_invalidated_with_grads_invalidated_and_graph_partition_Adam_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_params_invalidated_with_grads_invalidated_and_graph_partition_SGD_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_params_invalidated_with_grads_invalidated_between_unscale_and_step_AdamW_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_params_invalidated_with_grads_invalidated_between_unscale_and_step_Adam_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_params_invalidated_with_grads_invalidated_between_unscale_and_step_SGD_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_pdist_empty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_pdist_norm_large_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_pickle_gradscaler_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_pin_memory_from_constructor_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_empty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_mem_overlap_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_reduced_type_float_copy_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_reduced_type_float_copy_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_repeat_interleave_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scalar_check_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_add_bool_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_add_non_unique_index_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_add_one_dim_deterministic_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_add_to_large_input_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_bool_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_mem_overlap_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_multiply_unsupported_dtypes_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_multiply_unsupported_dtypes_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_to_large_input_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_zero_size_index_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_serialization_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_default_tensor_type_warnings_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_shift_mem_overlap_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_skip_xla_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_all_devices_non_blocking_False_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_all_devices_non_blocking_True_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_uint16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_uint32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_uint64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_qint32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_qint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_quint4x2, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_quint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_use_count_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_strides_propagation_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_sync_warning_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_empty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_uint16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_uint32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_uint64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_set_errors_multigpu_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_shape_empty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_type_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_ternary_op_mem_overlap_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_uniform_kstest_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_uniform_kstest_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_uniform_kstest_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_uniform_kstest_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_untyped_storage_meta_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_warn_always_caught_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_where_scalar_handcrafted_values_cpu
2025-07-17T06:58:50.0068560Z 
2025-07-17T06:58:50.0068690Z Running test_native_mha 1/1 ... [2025-07-17 06:58:49.971433]
2025-07-17T06:58:50.0068940Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:58:50.0069630Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_native_mha.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:58:49.971707]
2025-07-17T06:58:51.9663650Z 
2025-07-17T06:58:51.9664110Z test_native_mha 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_native_mha_1.1_42e6d8f2114b5b96_.log
2025-07-17T06:58:51.9676790Z Running 28 items in this shard: test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_attention_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_encoder_decoder_attention_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_transform_bias_rescale_qkv_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_transform_bias_rescale_qkv_nested_cpu_float32
2025-07-17T06:58:51.9688910Z 
2025-07-17T06:58:51.9689040Z Running test_sort_and_select 1/1 ... [2025-07-17 06:58:51.966683]
2025-07-17T06:58:51.9689300Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:58:51.9690030Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_sort_and_select.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:58:51.966935]
2025-07-17T06:58:54.8710320Z 
2025-07-17T06:58:54.8710850Z test_sort_and_select 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sort_and_select_1.1_42819f16d16ed848_.log
2025-07-17T06:58:54.8733510Z Running 113 items in this shard: test/test_sort_and_select.py::TestSortAndSelectCPU::test_complex_unsupported_cpu_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_dtypes_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_kthvalue_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_kthvalue_scalar_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_output_discontiguous_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_discontiguous_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_discontiguous_slow_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_expanded_tensor_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_large_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_large_slice_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_restride_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_stable_none_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_bool, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_bool, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_1d_output_discontiguous_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_4d_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_arguments_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_lower_precision_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_lower_precision_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_noncontiguous_gpu_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_nonfinite_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_nonfinite_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_nonfinite_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_nonfinite_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_quantized_scalar_input_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_bool, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_bool, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_dim_cpu
2025-07-17T06:58:54.8755100Z 
2025-07-17T06:58:54.8755250Z Running test_multiprocessing_spawn 1/1 ... [2025-07-17 06:58:54.871394]
2025-07-17T06:58:54.8755520Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T06:58:54.8756250Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_multiprocessing_spawn.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 06:58:54.871641]
2025-07-17T07:01:49.5342080Z 
2025-07-17T07:01:49.5342810Z test_multiprocessing_spawn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_multiprocessing_spawn_1.1_b99aa6e2df6504b2_.log
2025-07-17T07:01:49.5350060Z Running 31 items in this shard: test/test_multiprocessing_spawn.py::SpawnTest::test_exception_all, test/test_multiprocessing_spawn.py::SpawnTest::test_exception_raises, test/test_multiprocessing_spawn.py::SpawnTest::test_exception_single, test/test_multiprocessing_spawn.py::SpawnTest::test_first_argument_index, test/test_multiprocessing_spawn.py::SpawnTest::test_signal_raises, test/test_multiprocessing_spawn.py::SpawnTest::test_success, test/test_multiprocessing_spawn.py::SpawnTest::test_success_first_then_exception, test/test_multiprocessing_spawn.py::SpawnTest::test_success_non_blocking, test/test_multiprocessing_spawn.py::SpawnTest::test_terminate_exit_grace_period0, test/test_multiprocessing_spawn.py::SpawnTest::test_terminate_exit_grace_period_5, test/test_multiprocessing_spawn.py::SpawnTest::test_terminate_signal, test/test_multiprocessing_spawn.py::ForkTest::test_exception_all, test/test_multiprocessing_spawn.py::ForkTest::test_exception_single, test/test_multiprocessing_spawn.py::ForkTest::test_first_argument_index, test/test_multiprocessing_spawn.py::ForkTest::test_success, test/test_multiprocessing_spawn.py::ForkTest::test_success_first_then_exception, test/test_multiprocessing_spawn.py::ForkTest::test_success_non_blocking, test/test_multiprocessing_spawn.py::ForkTest::test_terminate_exit_grace_period0, test/test_multiprocessing_spawn.py::ForkTest::test_terminate_exit_grace_period_5, test/test_multiprocessing_spawn.py::ForkTest::test_terminate_signal, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_exception_all, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_exception_single, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_first_argument_index, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_success, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_success_first_then_exception, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_success_non_blocking, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_terminate_exit_grace_period0, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_terminate_exit_grace_period_5, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_terminate_signal, test/test_multiprocessing_spawn.py::ParallelForkServerPerfTest::test_forkserver_perf, test/test_multiprocessing_spawn.py::ErrorTest::test_errors_pickleable
2025-07-17T07:01:49.5356600Z 
2025-07-17T07:01:49.5356720Z Running nn/test_pooling 1/1 ... [2025-07-17 07:01:49.534526]
2025-07-17T07:01:49.5356980Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:01:49.5357700Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'nn/test_pooling.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:01:49.534780]
2025-07-17T07:02:07.7999500Z 
2025-07-17T07:02:07.8000820Z nn/test_pooling 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_pooling_1.1_528a02677640dc2a_.log
2025-07-17T07:02:07.8051280Z Running 188 items in this shard: test/nn/test_pooling.py::TestAvgPool::test_avg_pool1d_ceil_mode, test/nn/test_pooling.py::TestAvgPool::test_avg_pool2d_ceil_mode, test/nn/test_pooling.py::TestAvgPool::test_avg_pool3d_ceil_mode, test/nn/test_pooling.py::TestAvgPool::test_doubletensor_avg_pool2d, test/nn/test_pooling.py::TestAvgPool::test_doubletensor_avg_pool2d_with_divisor, test/nn/test_pooling.py::TestAvgPool::test_doubletensor_avg_pool3d, test/nn/test_pooling.py::TestAvgPool::test_doubletensor_avg_pool3d_with_divisor, test/nn/test_pooling.py::TestPoolingNN::test_MaxUnpool2d_output_size, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_avg_pooling_nhwc_overflow, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_avg_pooling_overflow, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_avg_nhwc, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_avg_nhwc_launch_config_backward, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_avg_nhwc_launch_config_forward, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_avg_nhwc_non_contiguous, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_lower_precision, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_size_none, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_size_overflow, test/nn/test_pooling.py::TestPoolingNN::test_max_unpool, test/nn/test_pooling.py::TestPoolingNN::test_max_unpool2d_nhwc_cpu, test/nn/test_pooling.py::TestPoolingNN::test_max_unpool3d_input_check, test/nn/test_pooling.py::TestPoolingNN::test_quantized_max_pool1d_empty_kernel, test/nn/test_pooling.py::TestPoolingNN::test_quantized_max_pool3d, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AdaptiveMaxPool1d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AdaptiveMaxPool2d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AdaptiveMaxPool3d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AdaptiveMaxPool_zero_batch_dim_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AvgPool2d_empty_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AvgPool3d_backward_after_cat_dim1_device_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool2d_zero_batch_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool2d_zero_out_size_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool2d_zero_samples_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool3d_errors_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool3d_zero_batch_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool3d_zero_out_size_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool3d_zero_samples_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxPool1d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxPool2d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxPool3d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxPool_zero_batch_dim_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case10_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case1_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case2_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case3_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case4_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case5_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case6_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case7_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case8_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case9_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_zero_batch_dim_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_avg_pool2d_output_size_one_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_avg_pool3d_output_size_one_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_avg_pooling_backward_fails_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_max_pooling_backward_fails_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pool_odd_size_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_empty_output_size_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_empty_output_size_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_max_nhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_max_nhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_int16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_int32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_int64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_int8, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_uint8, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_zero_batch_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_zero_batch_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_avg_pool2d_nhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_avg_pool2d_nhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_avg_pool2d_reduced_floating_cpu_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_avg_pool2d_reduced_floating_cpu_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_fractional_max_pool2d_backward_fails_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_fractional_max_pool2d_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_fractional_max_pool3d_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_fractional_max_pool_nan_inf_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool1d_corner_cases_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool1d_corner_cases_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool1d_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool1d_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_corner_cases_cpu_int32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_corner_cases_cpu_int64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_indices_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_nhwc_cpu_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_nhwc_cpu_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_nhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_nhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_with_indices_backward_fails_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool3d_ndhwc_cpu_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool3d_ndhwc_cpu_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool3d_ndhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool3d_ndhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool_bfloat16_half_cpu_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool_bfloat16_half_cpu_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool_nan_inf_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_maxpool3d_non_square_backward_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_maxpool_indices_no_batch_dim_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pool3d_large_size_int64_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pool3d_size_one_feature_dim_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pool_invalid_size_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pool_large_size_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_bfloat16_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_large_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_max_nhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_max_nhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_shape_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_zero_stride_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_AdaptiveMaxPool1d_indices_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_AdaptiveMaxPool2d_indices_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_AdaptiveMaxPool3d_indices_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_AdaptiveMaxPool_zero_batch_dim_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_AvgPool2d_empty_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_AvgPool3d_backward_after_cat_dim1_device_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_FractionalMaxPool2d_zero_batch_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_FractionalMaxPool2d_zero_out_size_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_FractionalMaxPool2d_zero_samples_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_FractionalMaxPool3d_errors_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_FractionalMaxPool3d_zero_batch_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_FractionalMaxPool3d_zero_out_size_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_FractionalMaxPool3d_zero_samples_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxPool1d_indices_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxPool2d_indices_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxPool3d_indices_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxPool_zero_batch_dim_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxUnpool_index_errors_case10_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxUnpool_index_errors_case1_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxUnpool_index_errors_case2_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxUnpool_index_errors_case3_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxUnpool_index_errors_case4_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxUnpool_index_errors_case5_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxUnpool_index_errors_case6_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxUnpool_index_errors_case7_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxUnpool_index_errors_case8_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxUnpool_index_errors_case9_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_MaxUnpool_zero_batch_dim_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_avg_pool2d_output_size_one_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_avg_pool3d_output_size_one_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_avg_pooling_backward_fails_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_max_pooling_backward_fails_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_pool_odd_size_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_pooling_empty_output_size_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_pooling_empty_output_size_mps_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_pooling_max_nhwc_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_pooling_no_suppot_input_mps_int16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_pooling_no_suppot_input_mps_int32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_pooling_no_suppot_input_mps_int64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_pooling_no_suppot_input_mps_int8, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_pooling_no_suppot_input_mps_uint8, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_pooling_zero_batch_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_adaptive_pooling_zero_batch_mps_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_avg_pool2d_nhwc_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_avg_pool2d_nhwc_mps_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_avg_pool2d_reduced_floating_mps_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_avg_pool2d_reduced_floating_mps_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_fractional_max_pool2d_backward_fails_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_fractional_max_pool2d_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_fractional_max_pool3d_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_fractional_max_pool_nan_inf_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool1d_corner_cases_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool1d_corner_cases_mps_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool1d_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool1d_mps_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool2d_corner_cases_mps_int32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool2d_corner_cases_mps_int64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool2d_indices_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool2d_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool2d_nhwc_mps_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool2d_nhwc_mps_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool2d_nhwc_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool2d_nhwc_mps_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool2d_with_indices_backward_fails_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool3d_ndhwc_mps_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool3d_ndhwc_mps_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool3d_ndhwc_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool3d_ndhwc_mps_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool_bfloat16_half_mps_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool_bfloat16_half_mps_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_max_pool_nan_inf_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_maxpool3d_non_square_backward_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_maxpool_indices_no_batch_dim_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_pool3d_large_size_int64_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_pool3d_size_one_feature_dim_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_pool_invalid_size_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_pool_large_size_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_pooling_bfloat16_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_pooling_large_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_pooling_max_nhwc_mps_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_pooling_shape_mps, test/nn/test_pooling.py::TestPoolingNNDeviceTypeMPS::test_pooling_zero_stride_mps
2025-07-17T07:02:07.8097390Z 
2025-07-17T07:02:07.8097540Z Running test_overrides 1/1 ... [2025-07-17 07:02:07.800481]
2025-07-17T07:02:07.8097840Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:02:07.8098620Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_overrides.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:02:07.800794]
2025-07-17T07:02:11.4082450Z 
2025-07-17T07:02:11.4082970Z test_overrides 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_overrides_1.1_6f29ab43fa9c20b0_.log
2025-07-17T07:02:11.4363730Z Running 1467 items in this shard: test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_H___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_T___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__backward_hooks___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__base___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__cdata___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__grad___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__grad_fn___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__post_accumulate_grad_hooks___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__version___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_data___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_device___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_dtype___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_grad___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_grad_fn___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_imag___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_cpu___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_cuda___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_ipu___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_leaf___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_maia___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_meta___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_mkldnn___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_is_mps___get__, 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test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_hsplit, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_hypot, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_hypot_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_i0, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_i0_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_igamma, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_igamma_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_igammac, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_igammac_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_add, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_add_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_copy, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_copy_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_fill, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_fill_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_put, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_put_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_reduce_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_select, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_indices, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_inner, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_int, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_int_repr, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ipu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_coalesced, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_complex, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_conj, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_contiguous, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_distributed, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_floating_point, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_inference, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_neg, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_pinned, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_same_size, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_set_to, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_shared, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_signed, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isclose, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isfinite, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isinf, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isnan, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isneginf, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isposinf, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isreal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_istft, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_item, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_kron, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_kthvalue, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lcm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lcm_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ldexp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ldexp_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_le, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_le_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lerp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lerp_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_less, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_less_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_less_equal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_less_equal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lgamma, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lgamma_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log10, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log10_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log1p, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log1p_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log2, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log2_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log_normal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logaddexp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logaddexp2, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logcumsumexp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logdet, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_and, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_and_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_not, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_not_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_or, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_or_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_xor, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_xor_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logit, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logit_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logsumexp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_long, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lt, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lt_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lu_solve, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_map2_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_map_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_fill, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_fill_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_scatter_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_select, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_matmul, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_matrix_exp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_matrix_power, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_max, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_maximum, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mean, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_median, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_min, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_minimum, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mode, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_module_load, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_moveaxis, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_movedim, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_msort, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mtia, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mul, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mul_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_multinomial, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_multiply, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_multiply_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mv, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mvlgamma, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mvlgamma_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nan_to_num, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nan_to_num_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nanmean, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nanmedian, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nanquantile, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nansum, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_narrow, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_narrow_copy, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ndimension, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ne, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ne_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_neg, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_neg_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_negative, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_negative_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nelement, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nextafter, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nextafter_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nonzero_static, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_norm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_normal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_not_equal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_not_equal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_numel, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_numpy, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_orgqr, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ormqr, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_outer, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_permute, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_pin_memory, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_pinverse, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_polygamma, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_polygamma_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_positive, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_pow, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_pow_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_prelu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_prod, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_put, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_put_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_q_per_channel_axis, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_q_per_channel_scales, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_q_per_channel_zero_points, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_q_scale, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_q_zero_point, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_qr, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_qscheme, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_quantile, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rad2deg, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rad2deg_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_random_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ravel, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_reciprocal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_reciprocal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_record_stream, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_refine_names, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_register_hook, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_register_post_accumulate_grad_hook, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_relu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_relu_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_remainder, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_remainder_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rename, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rename_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_renorm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_renorm_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_repeat, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_repeat_interleave, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_requires_grad_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_reshape, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_reshape_as, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resize, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resize_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resize_as, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resize_as_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resize_as_sparse_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resolve_conj, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_resolve_neg, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_retain_grad, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_roll, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rot90, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_round, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_round_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_row_indices, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rsqrt, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rsqrt_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_scatter_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_scatter_add, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_scatter_add_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_scatter_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_scatter_reduce_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_select, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_select_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_set_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sgn, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sgn_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_share_memory_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_short, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sigmoid, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sigmoid_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sign, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sign_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_signbit, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sin, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sin_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sinc, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sinc_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sinh, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sinh_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_size, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_slice_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_slice_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_slogdet, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_smm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sort, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sparse_dim, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sparse_mask, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sparse_resize_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sparse_resize_and_clear_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_split, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_split_with_sizes, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sqrt, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sqrt_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_square, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_square_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_squeeze, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_squeeze_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sspaddmm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_std, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_stft, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_storage, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_storage_offset, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_storage_type, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sub, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sub_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_subtract, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_subtract_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sum, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_sum_to_size, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_svd, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_swapaxes, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_swapaxes_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_swapdims, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_swapdims_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_t, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_t_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_take, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_take_along_dim, 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test/test_overrides.py::TestTorchFunctionOverride::test_torch__reshape_alias_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__rowwise_prune, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sparse_broadcast_to_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_acos, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_asin, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_atan, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_cos, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_cosh, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_sin, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_sinh, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_sqrt, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_tan, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_tanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch__values_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__wrapped_linear_prepack, test/test_overrides.py::TestTorchFunctionOverride::test_torch__wrapped_quantized_linear_prepacked, test/test_overrides.py::TestTorchFunctionOverride::test_torch_abs, test/test_overrides.py::TestTorchFunctionOverride::test_torch_absolute, test/test_overrides.py::TestTorchFunctionOverride::test_torch_acos, test/test_overrides.py::TestTorchFunctionOverride::test_torch_acosh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_adaptive_avg_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_adaptive_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_add, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addbmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addcdiv, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addcmul, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addmv, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_adjoint, test/test_overrides.py::TestTorchFunctionOverride::test_torch_affine_grid_generator, test/test_overrides.py::TestTorchFunctionOverride::test_torch_alias_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_all, test/test_overrides.py::TestTorchFunctionOverride::test_torch_allclose, test/test_overrides.py::TestTorchFunctionOverride::test_torch_alpha_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_amax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_amin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_aminmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_angle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_any, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arccos, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arccosh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arcsin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arcsinh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arctan, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arctan2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arctanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_argmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_argmin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_argsort, test/test_overrides.py::TestTorchFunctionOverride::test_torch_argwhere, test/test_overrides.py::TestTorchFunctionOverride::test_torch_as_strided_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_as_strided_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_asin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_asinh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_atan, test/test_overrides.py::TestTorchFunctionOverride::test_torch_atan2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_atanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_avg_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_baddbmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_backward_elemt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_backward_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_elemt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_gather_stats, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_gather_stats_with_counts, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_stats, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_update_stats, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bernoulli, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bilinear, test/test_overrides.py::TestTorchFunctionOverride::test_torch_binary_cross_entropy_with_logits, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bincount, test/test_overrides.py::TestTorchFunctionOverride::test_torch_binomial, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_and, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_left_shift, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_not, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_or, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_right_shift, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_xor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_broadcast_to, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bucketize, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cat, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ccol_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ceil, test/test_overrides.py::TestTorchFunctionOverride::test_torch_celu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_channel_shuffle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cholesky, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cholesky_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cholesky_solve, test/test_overrides.py::TestTorchFunctionOverride::test_torch_choose_qparams_optimized, test/test_overrides.py::TestTorchFunctionOverride::test_torch_chunk, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clamp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clamp_max, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clamp_min, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clip, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clone, test/test_overrides.py::TestTorchFunctionOverride::test_torch_col_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_column_stack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_combinations, test/test_overrides.py::TestTorchFunctionOverride::test_torch_complex, test/test_overrides.py::TestTorchFunctionOverride::test_torch_concat, test/test_overrides.py::TestTorchFunctionOverride::test_torch_concatenate, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conj, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conj_physical, test/test_overrides.py::TestTorchFunctionOverride::test_torch_constant_pad_nd, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv_tbc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv_transpose1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv_transpose2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv_transpose3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_convolution, test/test_overrides.py::TestTorchFunctionOverride::test_torch_copysign, test/test_overrides.py::TestTorchFunctionOverride::test_torch_corrcoef, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cos, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cosh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cosine_embedding_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cosine_similarity, test/test_overrides.py::TestTorchFunctionOverride::test_torch_count_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cov, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cross, test/test_overrides.py::TestTorchFunctionOverride::test_torch_crow_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ctc_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cummax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cummin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cumprod, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cumsum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cumulative_trapezoid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_deg2rad, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dequantize, test/test_overrides.py::TestTorchFunctionOverride::test_torch_det, test/test_overrides.py::TestTorchFunctionOverride::test_torch_detach, test/test_overrides.py::TestTorchFunctionOverride::test_torch_detach_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diag_embed, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diagflat, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diagonal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diagonal_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diagonal_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diff, test/test_overrides.py::TestTorchFunctionOverride::test_torch_digamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dist, test/test_overrides.py::TestTorchFunctionOverride::test_torch_div, test/test_overrides.py::TestTorchFunctionOverride::test_torch_divide, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dot, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dsmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dsplit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dstack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_embedding, test/test_overrides.py::TestTorchFunctionOverride::test_torch_embedding_bag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_empty_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_eq, test/test_overrides.py::TestTorchFunctionOverride::test_torch_equal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_erf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_erfc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_erfinv, test/test_overrides.py::TestTorchFunctionOverride::test_torch_exp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_exp2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_expand_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_expm1, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fake_quantize_per_channel_affine, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fake_quantize_per_tensor_affine, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_fp16_weight, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_fp16_weight_fp32_activation, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_int8_weight, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_int8_weight_fp32_activation, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_quantize_weight, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_pack_gemm_matrix_fp16, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_pack_quantized_matrix, test/test_overrides.py::TestTorchFunctionOverride::test_torch_feature_alpha_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_feature_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fix, test/test_overrides.py::TestTorchFunctionOverride::test_torch_flatten, test/test_overrides.py::TestTorchFunctionOverride::test_torch_flip, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fliplr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_flipud, test/test_overrides.py::TestTorchFunctionOverride::test_torch_float_power, test/test_overrides.py::TestTorchFunctionOverride::test_torch_floor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_floor_divide, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fmin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fmod, test/test_overrides.py::TestTorchFunctionOverride::test_torch_frac, test/test_overrides.py::TestTorchFunctionOverride::test_torch_frexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_frobenius_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_full_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_atleast_1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_atleast_2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_atleast_3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_block_diag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_broadcast_tensors, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_cartesian_prod, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_cdist, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_chain_matmul, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_einsum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_lu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_meshgrid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_split, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_stft, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_tensordot, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_unique, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_unique_consecutive, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_unravel_index, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fused_moving_avg_obs_fake_quant, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gather, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gcd, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ge, test/test_overrides.py::TestTorchFunctionOverride::test_torch_geqrf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ger, test/test_overrides.py::TestTorchFunctionOverride::test_torch_get_device, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gradient, test/test_overrides.py::TestTorchFunctionOverride::test_torch_greater, test/test_overrides.py::TestTorchFunctionOverride::test_torch_greater_equal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_grid_sampler, test/test_overrides.py::TestTorchFunctionOverride::test_torch_grid_sampler_2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_grid_sampler_3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_group_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gru, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gru_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hardshrink, test/test_overrides.py::TestTorchFunctionOverride::test_torch_heaviside, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hinge_embedding_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_histc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_histogram, test/test_overrides.py::TestTorchFunctionOverride::test_torch_histogramdd, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hsmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hsplit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hstack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hypot, test/test_overrides.py::TestTorchFunctionOverride::test_torch_i0, test/test_overrides.py::TestTorchFunctionOverride::test_torch_igamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_igammac, test/test_overrides.py::TestTorchFunctionOverride::test_torch_imag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_add, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_fill, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_put, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_select, test/test_overrides.py::TestTorchFunctionOverride::test_torch_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_inner, test/test_overrides.py::TestTorchFunctionOverride::test_torch_instance_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_int_repr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_complex, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_conj, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_distributed, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_floating_point, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_inference, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_neg, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_same_size, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_signed, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isclose, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isfinite, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isinf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isnan, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isneginf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isposinf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isreal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_istft, test/test_overrides.py::TestTorchFunctionOverride::test_torch_kl_div, test/test_overrides.py::TestTorchFunctionOverride::test_torch_kron, test/test_overrides.py::TestTorchFunctionOverride::test_torch_kthvalue, test/test_overrides.py::TestTorchFunctionOverride::test_torch_layer_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lcm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ldexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_le, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lerp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_less, test/test_overrides.py::TestTorchFunctionOverride::test_torch_less_equal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lgamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log10, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log1p, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logaddexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logaddexp2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logcumsumexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logdet, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logical_and, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logical_not, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logical_or, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logical_xor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logsumexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lstm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lstm_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lu_solve, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lu_unpack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_margin_ranking_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_masked_fill, test/test_overrides.py::TestTorchFunctionOverride::test_torch_masked_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_masked_select, test/test_overrides.py::TestTorchFunctionOverride::test_torch_matmul, test/test_overrides.py::TestTorchFunctionOverride::test_torch_matrix_exp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_matrix_power, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max_pool1d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_maximum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mean, test/test_overrides.py::TestTorchFunctionOverride::test_torch_median, test/test_overrides.py::TestTorchFunctionOverride::test_torch_min, test/test_overrides.py::TestTorchFunctionOverride::test_torch_minimum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_convolution, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_convolution_add_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_convolution_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_convolution_transpose, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_depthwise_convolution, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_rnn, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mode, test/test_overrides.py::TestTorchFunctionOverride::test_torch_moveaxis, test/test_overrides.py::TestTorchFunctionOverride::test_torch_movedim, test/test_overrides.py::TestTorchFunctionOverride::test_torch_msort, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mul, test/test_overrides.py::TestTorchFunctionOverride::test_torch_multinomial, test/test_overrides.py::TestTorchFunctionOverride::test_torch_multiply, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mv, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mvlgamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nan_to_num, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nanmean, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nanmedian, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nanquantile, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nansum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_narrow, test/test_overrides.py::TestTorchFunctionOverride::test_torch_narrow_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_channel_shuffle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_group_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_layer_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ne, test/test_overrides.py::TestTorchFunctionOverride::test_torch_neg, test/test_overrides.py::TestTorchFunctionOverride::test_torch_negative, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nextafter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional__threshold, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_avg_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_avg_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool1d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool2d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool3d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_affine_grid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_alpha_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_binary_cross_entropy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_binary_cross_entropy_with_logits, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_celu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_cosine_embedding_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_cross_entropy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_ctc_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_dropout1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_dropout2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_dropout3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_elu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_embedding, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_embedding_bag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_feature_alpha_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fold, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fractional_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fractional_max_pool2d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fractional_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fractional_max_pool3d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_gaussian_nll_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_glu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_grid_sample, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_group_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_gumbel_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_hardtanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_hinge_embedding_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_huber_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_instance_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_interpolate, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_kl_div, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_l1_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_layer_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_leaky_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_local_response_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_log_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_lp_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_lp_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_lp_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_margin_ranking_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool1d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool2d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool3d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_unpool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_unpool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_unpool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_mish, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_mse_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_multi_head_attention_forward, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_multi_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_multilabel_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_multilabel_soft_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_nll_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_normalize, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_pad, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_poisson_nll_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_relu6, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_rms_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_rrelu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_selu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_silu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_smooth_l1_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_soft_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_softmin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_softsign, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_tanhshrink, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_triplet_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_triplet_margin_with_distance_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_unfold, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_init_constant_, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_init_kaiming_uniform_, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_init_normal_, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_init_uniform_, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nonzero_static, test/test_overrides.py::TestTorchFunctionOverride::test_torch_norm_except_dim, test/test_overrides.py::TestTorchFunctionOverride::test_torch_not_equal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nuclear_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_numel, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ones_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_orgqr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ormqr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_outer, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pairwise_distance, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pdist, test/test_overrides.py::TestTorchFunctionOverride::test_torch_permute, test/test_overrides.py::TestTorchFunctionOverride::test_torch_permute_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pinverse, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pixel_shuffle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pixel_unshuffle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_poisson, test/test_overrides.py::TestTorchFunctionOverride::test_torch_poisson_nll_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_polar, test/test_overrides.py::TestTorchFunctionOverride::test_torch_polygamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_positive, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pow, test/test_overrides.py::TestTorchFunctionOverride::test_torch_prelu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_prod, test/test_overrides.py::TestTorchFunctionOverride::test_torch_put, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_per_channel_axis, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_per_channel_scales, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_per_channel_zero_points, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_scale, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_zero_point, test/test_overrides.py::TestTorchFunctionOverride::test_torch_qr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantile, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantize_per_channel, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantize_per_tensor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantize_per_tensor_dynamic, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_gru_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_lstm_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_rnn_relu_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_rnn_tanh_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rad2deg, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rand_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_randint_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_randn_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ravel, test/test_overrides.py::TestTorchFunctionOverride::test_torch_real, test/test_overrides.py::TestTorchFunctionOverride::test_torch_reciprocal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_remainder, test/test_overrides.py::TestTorchFunctionOverride::test_torch_renorm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_repeat_interleave, test/test_overrides.py::TestTorchFunctionOverride::test_torch_reshape, test/test_overrides.py::TestTorchFunctionOverride::test_torch_resolve_conj, test/test_overrides.py::TestTorchFunctionOverride::test_torch_resolve_neg, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rms_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rnn_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rnn_relu_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rnn_tanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rnn_tanh_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_roll, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rot90, test/test_overrides.py::TestTorchFunctionOverride::test_torch_round, test/test_overrides.py::TestTorchFunctionOverride::test_torch_row_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_row_stack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rrelu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rsqrt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rsub, test/test_overrides.py::TestTorchFunctionOverride::test_torch_saddmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_scatter_add, test/test_overrides.py::TestTorchFunctionOverride::test_torch_scatter_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_torch_searchsorted, test/test_overrides.py::TestTorchFunctionOverride::test_torch_segment_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_torch_select, test/test_overrides.py::TestTorchFunctionOverride::test_torch_select_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_select_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_selu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sgn, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sigmoid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sign, test/test_overrides.py::TestTorchFunctionOverride::test_torch_signbit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sinc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sinh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_slice_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_slice_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_torch_slice_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_slogdet, test/test_overrides.py::TestTorchFunctionOverride::test_torch_smm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sort, test/test_overrides.py::TestTorchFunctionOverride::test_torch_split_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_split_with_sizes, test/test_overrides.py::TestTorchFunctionOverride::test_torch_split_with_sizes_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sqrt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_square, test/test_overrides.py::TestTorchFunctionOverride::test_torch_squeeze, test/test_overrides.py::TestTorchFunctionOverride::test_torch_squeeze_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_stack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_std, test/test_overrides.py::TestTorchFunctionOverride::test_torch_std_mean, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sub, test/test_overrides.py::TestTorchFunctionOverride::test_torch_subtract, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_svd, test/test_overrides.py::TestTorchFunctionOverride::test_torch_swapaxes, test/test_overrides.py::TestTorchFunctionOverride::test_torch_swapdims, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_float, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_int, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_ite, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_max, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_min, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_not, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_sum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_t, test/test_overrides.py::TestTorchFunctionOverride::test_torch_t_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_take, test/test_overrides.py::TestTorchFunctionOverride::test_torch_take_along_dim, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tan, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tensor_split, test/test_overrides.py::TestTorchFunctionOverride::test_torch_threshold, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tile, test/test_overrides.py::TestTorchFunctionOverride::test_torch_topk, test/test_overrides.py::TestTorchFunctionOverride::test_torch_trace, test/test_overrides.py::TestTorchFunctionOverride::test_torch_transpose, test/test_overrides.py::TestTorchFunctionOverride::test_torch_transpose_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_trapezoid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_trapz, test/test_overrides.py::TestTorchFunctionOverride::test_torch_triangular_solve, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tril, test/test_overrides.py::TestTorchFunctionOverride::test_torch_triplet_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_triu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_true_divide, test/test_overrides.py::TestTorchFunctionOverride::test_torch_trunc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unbind, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unbind_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unflatten, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unfold_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsafe_chunk, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsafe_split, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsafe_split_with_sizes, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsqueeze, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsqueeze_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_values_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_var, test/test_overrides.py::TestTorchFunctionOverride::test_torch_var_mean, test/test_overrides.py::TestTorchFunctionOverride::test_torch_vdot, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_as_complex, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_as_complex_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_as_real, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_as_real_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_vsplit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_vstack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_where, test/test_overrides.py::TestTorchFunctionOverride::test_torch_xlogy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_zeros_like, test/test_overrides.py::TestTorchFunctionOverride::test_user_implementation_raises, test/test_overrides.py::TestEinsumOverride::test_wrapper, test/test_overrides.py::TestGradCheckOverride::test_gradcheck, test/test_overrides.py::TestNamedTuple::test_max, test/test_overrides.py::TestGradNewOnesOverride::test_newones, test/test_overrides.py::TestPickle::test_pickle, test/test_overrides.py::TestBroadcastAllOverride::test_broadcast_all, test/test_overrides.py::TestWrapTorchFunction::test_wrap_torch_function, test/test_overrides.py::TestIndexing::test_getitem, test/test_overrides.py::TestIndexing::test_getitem_subclass, test/test_overrides.py::TestIndexing::test_setitem, test/test_overrides.py::TestIndexing::test_setitem_subclass, test/test_overrides.py::TestIndexing::test_setitem_val, test/test_overrides.py::TestIterator::test_iterator, test/test_overrides.py::TestRNN::test_rnn, test/test_overrides.py::TestDisabledTorchFunction::test_parameter_does_not_prevent_dispatch, test/test_overrides.py::TestResolveName::test_resolve_name, test/test_overrides.py::TestTorchFunctionWarning::test_warn_on_invalid_torch_function_standalone_class, test/test_overrides.py::TestTorchFunctionWarning::test_warn_on_invalid_torch_function_tensor_subclass, test/test_overrides.py::TestDisabledUserWarnings::test_no_implicit_user_warning_for_deprecated_functions, test/test_overrides.py::TestTorchFunctionMode::test_all_same_mode, test/test_overrides.py::TestTorchFunctionMode::test_basic, test/test_overrides.py::TestTorchFunctionMode::test_custom_device_type, test/test_overrides.py::TestTorchFunctionMode::test_device_context_semantics, test/test_overrides.py::TestTorchFunctionMode::test_disable_enable_subclass, test/test_overrides.py::TestTorchFunctionMode::test_disable_enable_torch_function_ctx, test/test_overrides.py::TestTorchFunctionMode::test_disable_subclass_mode, test/test_overrides.py::TestTorchFunctionMode::test_disable_subclass_not_mode, test/test_overrides.py::TestTorchFunctionMode::test_distributions_bernoulli, test/test_overrides.py::TestTorchFunctionMode::test_error_using_class_method_on_mode, test/test_overrides.py::TestTorchFunctionMode::test_factory_override, test/test_overrides.py::TestTorchFunctionMode::test_get_cur_mode, test/test_overrides.py::TestTorchFunctionMode::test_get_mode_stack, test/test_overrides.py::TestTorchFunctionMode::test_getitem_call, test/test_overrides.py::TestTorchFunctionMode::test_mode_notimplemented_loop, test/test_overrides.py::TestTorchFunctionMode::test_modes_handle_first, test/test_overrides.py::TestTorchFunctionMode::test_modes_return_notimplemented, test/test_overrides.py::TestTorchFunctionMode::test_nested_modes_with_python_has_torch_function, test/test_overrides.py::TestTorchFunctionMode::test_nested_same_mode, test/test_overrides.py::TestTorchFunctionMode::test_nn_parse_to, test/test_overrides.py::TestTorchFunctionMode::test_reentrant_mode_idiom, test/test_overrides.py::TestTorchFunctionMode::test_restacking_with_ancestor, test/test_overrides.py::TestTorchFunctionMode::test_subclass_hash, test/test_overrides.py::TestTorchFunctionMode::test_torch_function_all_disabled_api, test/test_overrides.py::TestTorchFunctionMode::test_with_mode, test/test_overrides.py::TestTorchFunctionMode::test_with_mode_created_separately, test/test_overrides.py::TestTorchFunctionMode::test_with_nested_modes
2025-07-17T07:02:11.4627450Z 
2025-07-17T07:02:11.4627610Z Running test_mobile_optimizer 1/1 ... [2025-07-17 07:02:11.409410]
2025-07-17T07:02:11.4627870Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:02:11.4628580Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_mobile_optimizer.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:02:11.409683]
2025-07-17T07:02:13.4085810Z 
2025-07-17T07:02:13.4086410Z test_mobile_optimizer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mobile_optimizer_1.1_1f80f656ff5a8067_.log
2025-07-17T07:02:13.4089220Z Running 7 items in this shard: test/test_mobile_optimizer.py::TestOptimizer::test_clone_module_with_class, test/test_mobile_optimizer.py::TestOptimizer::test_generate_mobile_module_lints, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_mobilenet_optimize_for_mobile, test/test_mobile_optimizer.py::TestOptimizer::test_optimize_for_mobile, test/test_mobile_optimizer.py::TestOptimizer::test_preserve_bundled_inputs_methods, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures
2025-07-17T07:02:13.4090890Z 
2025-07-17T07:02:13.4091040Z Running nn/test_convolution 1/1 ... [2025-07-17 07:02:13.408924]
2025-07-17T07:02:13.4091360Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:02:13.4092990Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'nn/test_convolution.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:02:13.409206]
2025-07-17T07:04:15.7899740Z 
2025-07-17T07:04:15.7900260Z nn/test_convolution 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_convolution_1.1_48227bc79a5073bd_.log
2025-07-17T07:04:15.8283600Z Running 1151 items in this shard: test/nn/test_convolution.py::TestConvolutionNN::test_Conv1d_module_same_padding, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_1x1, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_OneDNN, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_backward_twice, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_groups_nobias, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_groups_nobias_v2, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_inconsistent_types, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_inconsistent_types_on_GPU_with_cudnn, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_inconsistent_types_on_GPU_without_cudnn, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_missing_argument, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_module_same_padding, test/nn/test_convolution.py::TestConvolutionNN::test_Conv3d_groups_nobias, test/nn/test_convolution.py::TestConvolutionNN::test_Conv3d_groups_wbias, test/nn/test_convolution.py::TestConvolutionNN::test_Conv3d_module_same_padding, test/nn/test_convolution.py::TestConvolutionNN::test_ConvTranspose2d_half_cublas_gemm, test/nn/test_convolution.py::TestConvolutionNN::test_ConvTranspose2d_output_size, test/nn/test_convolution.py::TestConvolutionNN::test_ConvTranspose2d_output_size_downsample_upsample, test/nn/test_convolution.py::TestConvolutionNN::test_ConvTranspose3d_correct_output_size, test/nn/test_convolution.py::TestConvolutionNN::test_conv1d_issue_120547, test/nn/test_convolution.py::TestConvolutionNN::test_conv2d_discontiguous_weight, test/nn/test_convolution.py::TestConvolutionNN::test_conv3d_issue_120406, test/nn/test_convolution.py::TestConvolutionNN::test_conv_backcompat, test/nn/test_convolution.py::TestConvolutionNN::test_conv_cudnn_memory_layout_dominance, test/nn/test_convolution.py::TestConvolutionNN::test_conv_invalid_groups, test/nn/test_convolution.py::TestConvolutionNN::test_conv_modules_raise_error_on_incorrect_input_size, test/nn/test_convolution.py::TestConvolutionNN::test_conv_padding_mode, test/nn/test_convolution.py::TestConvolutionNN::test_conv_shapecheck, test/nn/test_convolution.py::TestConvolutionNN::test_conv_tbc, test/nn/test_convolution.py::TestConvolutionNN::test_cudnn_non_contiguous, test/nn/test_convolution.py::TestConvolutionNN::test_cudnn_noncontiguous_weight, test/nn/test_convolution.py::TestConvolutionNN::test_cudnn_not_mutate_stride, test/nn/test_convolution.py::TestConvolutionNN::test_functional_grad_conv, test/nn/test_convolution.py::TestConvolutionNN::test_functional_grad_conv2d, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv1d_input, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv1d_weight, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv2d_input, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv2d_weight, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv3d_input, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv3d_weight, test/nn/test_convolution.py::TestConvolutionNN::test_grouped_conv_cudnn_nhwc_support, test/nn/test_convolution.py::TestConvolutionNN::test_invalid_conv1d, test/nn/test_convolution.py::TestConvolutionNN::test_invalid_conv2d, test/nn/test_convolution.py::TestConvolutionNN::test_invalid_conv3d, test/nn/test_convolution.py::TestConvolutionNN::test_mismatch_shape_conv2d, test/nn/test_convolution.py::TestConvolutionNN::test_nnpack_conv, test/nn/test_convolution.py::TestConvolutionNN::test_permute_conv2d_issue_120211, test/nn/test_convolution.py::TestConvolutionNN::test_thnn_conv_strided_padded_dilated, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_backward_depthwise_cpu_complex128, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_backward_depthwise_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_depthwise_naive_groups_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_depthwise_naive_groups_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_depthwise_naive_groups_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_1_cpu_complex128, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_1_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_1_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_1_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_1_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_2_cpu_complex128, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_2_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_2_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_2_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_2_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_3_cpu_complex128, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_3_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_3_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_3_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_3_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_large_workspace_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_large_workspace_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_large_workspace_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_naive_groups_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_size_1_kernel_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv3d_depthwise_naive_groups_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv3d_depthwise_naive_groups_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv3d_depthwise_naive_groups_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_ConvTranspose2d_large_output_padding_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_ConvTranspose2d_large_output_padding_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_ConvTranspose2d_size_1_kernel_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_ConvTranspose3d_size_1_kernel_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_contig_wrong_stride_cudnn_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_same_padding_backward_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_same_padding_backward_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_same_padding_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_same_padding_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_valid_padding_backward_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_valid_padding_backward_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_valid_padding_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_valid_padding_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_vs_scipy_mode_same_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_vs_scipy_mode_same_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_vs_scipy_mode_valid_cpu_complex64, 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test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_cudnn_nhwc_support_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_cudnn_nhwc_support_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_double_backward_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_double_backward_groups_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_double_backward_no_bias_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_double_backward_stride_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_double_backward_strided_with_3D_input_and_weight_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_empty_channel_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_empty_channel_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_ic1_channels_last_for_oneDNN_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_large_batch_1_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_large_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_large_nosplit_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_noncontig_weights_and_bias_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_noncontig_weights_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_thnn_nhwc_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_thnn_nhwc_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_transpose_with_output_size_and_no_batch_dim_ConvTranspose2d_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_transpose_with_output_size_and_no_batch_dim_ConvTranspose3d_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_transposed_large_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_convert_conv2d_weight_memory_format_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_convert_conv3d_weight_memory_format_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_cudnn_convolution_add_relu_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_cudnn_convolution_add_relu_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_cudnn_convolution_relu_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_cudnn_convolution_relu_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_depthwise_conv_64bit_indexing_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_group_convTranspose_empty_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_group_conv_empty_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_noncontig_conv_grad_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_noncontig_conv_grad_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_noncontig_conv_grad_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_backward_depthwise_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_backward_depthwise_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_depthwise_naive_groups_mps_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_depthwise_naive_groups_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_depthwise_naive_groups_mps_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_1_mps_complex128, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_1_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_1_mps_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_1_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_1_mps_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_2_mps_complex128, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_2_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_2_mps_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_2_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_2_mps_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_3_mps_complex128, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_3_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_3_mps_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_3_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_deterministic_cudnn_dilation_3_mps_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_large_workspace_mps_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_large_workspace_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_large_workspace_mps_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_naive_groups_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv2d_size_1_kernel_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv3d_depthwise_naive_groups_mps_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv3d_depthwise_naive_groups_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_Conv3d_depthwise_naive_groups_mps_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_ConvTranspose2d_large_output_padding_mps_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_ConvTranspose2d_large_output_padding_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_ConvTranspose2d_size_1_kernel_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_ConvTranspose3d_size_1_kernel_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_contig_wrong_stride_cudnn_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv1d_same_padding_backward_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv1d_same_padding_backward_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv1d_same_padding_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv1d_same_padding_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv1d_valid_padding_backward_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv1d_valid_padding_backward_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv1d_valid_padding_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv1d_valid_padding_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv1d_vs_scipy_mode_same_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv1d_vs_scipy_mode_same_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv1d_vs_scipy_mode_valid_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv1d_vs_scipy_mode_valid_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv2d_no_grad_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv2d_same_padding_backward_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv2d_same_padding_backward_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv2d_same_padding_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv2d_same_padding_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv2d_valid_padding_backward_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv2d_valid_padding_backward_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv2d_valid_padding_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv2d_valid_padding_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv2d_vs_scipy_mode_same_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv2d_vs_scipy_mode_same_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv2d_vs_scipy_mode_valid_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv2d_vs_scipy_mode_valid_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_64bit_indexing_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_large_batch_1_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_same_padding_backward_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_same_padding_backward_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_same_padding_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_same_padding_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_valid_padding_backward_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_valid_padding_backward_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_valid_padding_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_valid_padding_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_vs_scipy_mode_same_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_vs_scipy_mode_same_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_vs_scipy_mode_valid_mps_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv3d_vs_scipy_mode_valid_mps_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_convTranspose_empty_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise1d_has_bias_False_strided_False_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise1d_has_bias_False_strided_False_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise1d_has_bias_False_strided_True_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise1d_has_bias_False_strided_True_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise1d_has_bias_True_strided_False_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise1d_has_bias_True_strided_False_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise1d_has_bias_True_strided_True_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise1d_has_bias_True_strided_True_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise2d_has_bias_False_strided_False_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise2d_has_bias_False_strided_False_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise2d_has_bias_False_strided_True_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise2d_has_bias_False_strided_True_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise2d_has_bias_True_strided_False_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise2d_has_bias_True_strided_False_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise2d_has_bias_True_strided_True_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise2d_has_bias_True_strided_True_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise3d_has_bias_False_strided_False_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise3d_has_bias_False_strided_False_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise3d_has_bias_False_strided_True_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise3d_has_bias_False_strided_True_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise3d_has_bias_True_strided_False_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise3d_has_bias_True_strided_False_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise3d_has_bias_True_strided_True_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cuda_depthwise3d_has_bias_True_strided_True_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_has_bias_False_strided_False_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_has_bias_False_strided_False_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_has_bias_False_strided_True_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_has_bias_False_strided_True_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_has_bias_True_strided_False_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_has_bias_True_strided_False_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_has_bias_True_strided_True_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_has_bias_True_strided_True_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_transposed_has_bias_False_strided_False_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_transposed_has_bias_False_strided_False_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_transposed_has_bias_False_strided_True_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_transposed_has_bias_False_strided_True_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_transposed_has_bias_True_strided_False_contiguous_False_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_transposed_has_bias_True_strided_False_contiguous_True_mps, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeMPS::test_conv_backend_cudnn1d_transposed_has_bias_True_strided_True_contiguous_False_mps, 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2025-07-17T07:04:15.8652210Z 
2025-07-17T07:04:15.8652350Z Running test_reductions 1/1 ... [2025-07-17 07:04:15.791529]
2025-07-17T07:04:15.8652600Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:04:15.8653320Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_reductions.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:04:15.791973]
2025-07-17T07:05:37.8223040Z 
2025-07-17T07:05:37.8223600Z test_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_reductions_1.1_47d01aaf61c89c72_.log
2025-07-17T07:05:37.9204350Z Running 4565 items in this shard: test/test_reductions.py::TestReductionsCPU::test_accreal_type_cpu, test/test_reductions.py::TestReductionsCPU::test_all_any_cpu, test/test_reductions.py::TestReductionsCPU::test_all_any_empty_cpu, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_int64, 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test/test_reductions.py::TestReductionsCPU::test_sum_dim_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_dim_reduction_uint8_overflow_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_integer_upcast_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_noncontig_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_noncontig_lowp_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_sum_noncontig_lowp_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_sum_out_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_parallel_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_tensor_compare_ops_argmax_argmix_kthvalue_dim_empty_cpu, test/test_reductions.py::TestReductionsCPU::test_tensor_compare_ops_empty_cpu, test/test_reductions.py::TestReductionsCPU::test_tensor_reduce_ops_empty_cpu, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_var_cpu, test/test_reductions.py::TestReductionsCPU::test_var_dim_cpu, test/test_reductions.py::TestReductionsCPU::test_var_large_input_cpu, test/test_reductions.py::TestReductionsCPU::test_var_mean_all_dims_cpu, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_var_mean_cpu, test/test_reductions.py::TestReductionsCPU::test_var_mean_some_dims_cpu, test/test_reductions.py::TestReductionsCPU::test_var_stability2_cpu, test/test_reductions.py::TestReductionsCPU::test_var_stability_cpu, test/test_reductions.py::TestReductionsCPU::test_var_unbiased_cpu, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_warn_invalid_degrees_of_freedom_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_warn_invalid_degrees_of_freedom_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_warn_invalid_degrees_of_freedom_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_warn_invalid_degrees_of_freedom_cpu_float64
2025-07-17T07:05:38.0154640Z 
2025-07-17T07:05:38.0154770Z Running doctests 1/1 ... [2025-07-17 07:05:37.825445]
2025-07-17T07:05:38.0155180Z Start doctest_module('/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch')
2025-07-17T07:05:38.0155530Z Listing tests
2025-07-17T07:05:38.0155980Z msg = Cannot scrape callname=Library.fallback in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py line=374.
2025-07-17T07:05:38.0156550Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:38.0156910Z Registers the function implementation as the fallback for the given key.
2025-07-17T07:05:38.0157120Z 
2025-07-17T07:05:38.0157260Z         This function only works for a library with global namespace ("_").
2025-07-17T07:05:38.0157460Z 
2025-07-17T07:05:38.0157510Z         Args:
2025-07-17T07:05:38.0157770Z             fn: function used as fallback for the given dispatch key or :func:`~fallthrough_kernel`
2025-07-17T07:05:38.0158080Z                 to register a fallthrough.
2025-07-17T07:05:38.0158410Z             dispatch_key: dispatch key that the input function should be registered for. By default, it uses
2025-07-17T07:05:38.0158770Z                           the dispatch key that the library was created with.
2025-07-17T07:05:38.0159160Z             with_keyset: flag controlling if the current dispatcher call keyset should be passed as the first argument
2025-07-17T07:05:38.0159650Z                          to :attr:`fn` when calling. This should be used to create the appropriate keyset for redispatch calls.
2025-07-17T07:05:38.0159910Z 
2025-07-17T07:05:38.0159980Z         Example::
2025-07-17T07:05:38.0160070Z 
2025-07-17T07:05:38.0160140Z             >>> my_lib = Library("_", "IMPL")
2025-07-17T07:05:38.0160360Z             >>> def fallback_kernel(op, *args, **kwargs):
2025-07-17T07:05:38.0160590Z             >>>     # Handle all autocast ops generically
2025-07-17T07:05:38.0160790Z             >>>     # ...
2025-07-17T07:05:38.0160970Z             >>> my_lib.fallback(fallback_kernel, "Autocast")
2025-07-17T07:05:38.0161170Z         
2025-07-17T07:05:38.0161600Z Original Error: IndentationError('expected an indented block after function definition on line 2', ('<source_block>', 5, 1, 'my_lib.fallback(fallback_kernel, "Autocast")\n', 5, 7))
2025-07-17T07:05:38.0162020Z 
2025-07-17T07:05:38.0162100Z my_lib.fallback(fallback_kernel, "Autocast")
2025-07-17T07:05:38.0162290Z ^
2025-07-17T07:05:38.0162700Z msg = Cannot scrape callname=register_fake in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py line=933.
2025-07-17T07:05:38.0163260Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:38.0163610Z Register a FakeTensor implementation ("fake impl") for this operator.
2025-07-17T07:05:38.0163820Z 
2025-07-17T07:05:38.0163930Z     Also sometimes known as a "meta kernel", "abstract impl".
2025-07-17T07:05:38.0164110Z 
2025-07-17T07:05:38.0164460Z     An "FakeTensor implementation" specifies the behavior of this operator on
2025-07-17T07:05:38.0164820Z     Tensors that carry no data ("FakeTensor"). Given some input Tensors with
2025-07-17T07:05:38.0165160Z     certain properties (sizes/strides/storage_offset/device), it specifies
2025-07-17T07:05:38.0165510Z     what the properties of the output Tensors are.
2025-07-17T07:05:38.0165660Z 
2025-07-17T07:05:38.0165810Z     The FakeTensor implementation has the same signature as the operator.
2025-07-17T07:05:38.0166140Z     It is run for both FakeTensors and meta tensors. To write a FakeTensor
2025-07-17T07:05:38.0166460Z     implementation, assume that all Tensor inputs to the operator are
2025-07-17T07:05:38.0166780Z     regular CPU/CUDA/Meta tensors, but they do not have storage, and
2025-07-17T07:05:38.0167090Z     you are trying to return regular CPU/CUDA/Meta tensor(s) as output.
2025-07-17T07:05:38.0167670Z     The FakeTensor implementation must consist of only PyTorch operations
2025-07-17T07:05:38.0168190Z     (and may not directly access the storage or data of any input or
2025-07-17T07:05:38.0168430Z     intermediate Tensors).
2025-07-17T07:05:38.0168540Z 
2025-07-17T07:05:38.0168630Z     This API may be used as a decorator (see examples).
2025-07-17T07:05:38.0168800Z 
2025-07-17T07:05:38.0168880Z     For a detailed guide on custom ops, please see
2025-07-17T07:05:38.0169180Z     https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html
2025-07-17T07:05:38.0169380Z 
2025-07-17T07:05:38.0169430Z     Args:
2025-07-17T07:05:38.0169630Z         op_name: Operator name (along with the overload) or OpOverload object.
2025-07-17T07:05:38.0169900Z         func: Fake tensor implementation.
2025-07-17T07:05:38.0170150Z         lib (Optional[Library]): Library to register the fake tensor to.
2025-07-17T07:05:38.0170450Z         allow_override: Flag controlling if we want to override an
2025-07-17T07:05:38.0170740Z                         existing registered fake impl. This is by default off,
2025-07-17T07:05:38.0171030Z                         and will error you're trying to register a fake impl to
2025-07-17T07:05:38.0171310Z                         an operator that already has a fake impl. This also only
2025-07-17T07:05:38.0171590Z                         applies if the custom operator was not created via
2025-07-17T07:05:38.0171880Z                         torch.library.custom_op, as overriding and existing fake
2025-07-17T07:05:38.0172140Z                         impl is already allowed.
2025-07-17T07:05:38.0172270Z 
2025-07-17T07:05:38.0172310Z     Examples:
2025-07-17T07:05:38.0172440Z         >>> import torch
2025-07-17T07:05:38.0172600Z         >>> import numpy as np
2025-07-17T07:05:38.0172760Z         >>> from torch import Tensor
2025-07-17T07:05:38.0172930Z         >>>
2025-07-17T07:05:38.0173120Z         >>> # Example 1: an operator without data-dependent output shape
2025-07-17T07:05:38.0173440Z         >>> @torch.library.custom_op("mylib::custom_linear", mutates_args=())
2025-07-17T07:05:38.0173780Z         >>> def custom_linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor:
2025-07-17T07:05:38.0174100Z         >>>     raise NotImplementedError("Implementation goes here")
2025-07-17T07:05:38.0174310Z         >>>
2025-07-17T07:05:38.0174490Z         >>> @torch.library.register_fake("mylib::custom_linear")
2025-07-17T07:05:38.0174710Z         >>> def _(x, weight, bias):
2025-07-17T07:05:38.0174880Z         >>>     assert x.dim() == 2
2025-07-17T07:05:38.0175060Z         >>>     assert weight.dim() == 2
2025-07-17T07:05:38.0175260Z         >>>     assert bias.dim() == 1
2025-07-17T07:05:38.0175460Z         >>>     assert x.shape[1] == weight.shape[1]
2025-07-17T07:05:38.0175680Z         >>>     assert weight.shape[0] == bias.shape[0]
2025-07-17T07:05:38.0175900Z         >>>     assert x.device == weight.device
2025-07-17T07:05:38.0176090Z         >>>
2025-07-17T07:05:38.0176220Z         >>>     return (x @ weight.t()) + bias
2025-07-17T07:05:38.0176390Z         >>>
2025-07-17T07:05:38.0176590Z         >>> with torch._subclasses.fake_tensor.FakeTensorMode():
2025-07-17T07:05:38.0176830Z         >>>     x = torch.randn(2, 3)
2025-07-17T07:05:38.0177010Z         >>>     w = torch.randn(3, 3)
2025-07-17T07:05:38.0177190Z         >>>     b = torch.randn(3)
2025-07-17T07:05:38.0177420Z         >>>     y = torch.ops.mylib.custom_linear(x, w, b)
2025-07-17T07:05:38.0177610Z         >>>
2025-07-17T07:05:38.0177740Z         >>> assert y.shape == (2, 3)
2025-07-17T07:05:38.0177890Z         >>>
2025-07-17T07:05:38.0178070Z         >>> # Example 2: an operator with data-dependent output shape
2025-07-17T07:05:38.0178370Z         >>> @torch.library.custom_op("mylib::custom_nonzero", mutates_args=())
2025-07-17T07:05:38.0178660Z         >>> def custom_nonzero(x: Tensor) -> Tensor:
2025-07-17T07:05:38.0178860Z         >>>     x_np = x.numpy(force=True)
2025-07-17T07:05:38.0179080Z         >>>     res = np.stack(np.nonzero(x_np), axis=1)
2025-07-17T07:05:38.0179400Z         >>>     return torch.tensor(res, device=x.device)
2025-07-17T07:05:38.0179660Z         >>>
2025-07-17T07:05:38.0179840Z         >>> @torch.library.register_fake("mylib::custom_nonzero")
2025-07-17T07:05:38.0180050Z         >>> def _(x):
2025-07-17T07:05:38.0180230Z         >>> # Number of nonzero-elements is data-dependent.
2025-07-17T07:05:38.0180480Z         >>> # Since we cannot peek at the data in an fake impl,
2025-07-17T07:05:38.0180740Z         >>> # we use the ctx object to construct a new symint that
2025-07-17T07:05:38.0180970Z         >>> # represents the data-dependent size.
2025-07-17T07:05:38.0181190Z         >>>     ctx = torch.library.get_ctx()
2025-07-17T07:05:38.0181390Z         >>>     nnz = ctx.new_dynamic_size()
2025-07-17T07:05:38.0181570Z         >>>     shape = [nnz, x.dim()]
2025-07-17T07:05:38.0181790Z         >>>     result = x.new_empty(shape, dtype=torch.int64)
2025-07-17T07:05:38.0182000Z         >>>     return result
2025-07-17T07:05:38.0182150Z         >>>
2025-07-17T07:05:38.0182330Z         >>> from torch.fx.experimental.proxy_tensor import make_fx
2025-07-17T07:05:38.0182560Z         >>>
2025-07-17T07:05:38.0182690Z         >>> x = torch.tensor([0, 1, 2, 3, 4, 0])
2025-07-17T07:05:38.0182970Z         >>> trace = make_fx(torch.ops.mylib.custom_nonzero, tracing_mode="symbolic")(x)
2025-07-17T07:05:38.0183250Z         >>> trace.print_readable()
2025-07-17T07:05:38.0183410Z         >>>
2025-07-17T07:05:38.0183610Z         >>> assert torch.allclose(trace(x), torch.ops.mylib.custom_nonzero(x))
2025-07-17T07:05:38.0183810Z 
2025-07-17T07:05:38.0183850Z     
2025-07-17T07:05:38.0184230Z Original Error: IndentationError('expected an indented block after function definition on line 37', ('<source_block>', 38, 1, '_._ = None\n', 38, 2))
2025-07-17T07:05:38.0184620Z 
2025-07-17T07:05:38.0184670Z _._ = None
2025-07-17T07:05:38.0184770Z ^
2025-07-17T07:05:38.0185210Z msg = Cannot scrape callname=register_autograd in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py line=1068.
2025-07-17T07:05:38.0185800Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.0186100Z Register a backward formula for this custom op.
2025-07-17T07:05:38.0186250Z 
2025-07-17T07:05:38.0186380Z     In order for an operator to work with autograd, you need to register
2025-07-17T07:05:38.0186630Z     a backward formula:
2025-07-17T07:05:38.0186850Z     1. You must tell us how to compute gradients during the backward pass
2025-07-17T07:05:38.0187110Z     by providing us a "backward" function.
2025-07-17T07:05:38.0187370Z     2. If you need any values from the forward to compute gradients, you can
2025-07-17T07:05:38.0187650Z     use `setup_context` to save values for backward.
2025-07-17T07:05:38.0187800Z 
2025-07-17T07:05:38.0187940Z     ``backward`` runs during the backward pass. It accepts ``(ctx, *grads)``:
2025-07-17T07:05:38.0188260Z     - ``grads`` is one or more gradients. The number of gradients matches
2025-07-17T07:05:38.0188520Z     the number of outputs of the operator.
2025-07-17T07:05:38.0188820Z     The ``ctx`` object is `the same ctx object <context_method_mixins>`_ used by
2025-07-17T07:05:38.0189180Z     :class:`torch.autograd.Function`. The semantics of ``backward_fn`` are the
2025-07-17T07:05:38.0189510Z     same as :meth:`torch.autograd.Function.backward`.
2025-07-17T07:05:38.0189680Z 
2025-07-17T07:05:38.0189810Z     ``setup_context(ctx, inputs, output)`` runs during the forward pass.
2025-07-17T07:05:38.0190140Z     Please save quantities needed for backward onto the ``ctx`` object via
2025-07-17T07:05:38.0190480Z     either :meth:`torch.autograd.function.FunctionCtx.save_for_backward`
2025-07-17T07:05:38.0190810Z     or assigning them as attributes of ``ctx``. If your custom op has
2025-07-17T07:05:38.0191130Z     kwarg-only arguments, we expect the signature of ``setup_context``
2025-07-17T07:05:38.0191440Z     to be ``setup_context(ctx, inputs, keyword_only_inputs, output)``.
2025-07-17T07:05:38.0191710Z 
2025-07-17T07:05:38.0191910Z     Both ``setup_context_fn`` and ``backward_fn`` must be traceable. That is,
2025-07-17T07:05:38.0192250Z     they may not directly access :meth:`torch.Tensor.data_ptr` and they must
2025-07-17T07:05:38.0192590Z     not depend on or mutate global state. If you need a non-traceable backward,
2025-07-17T07:05:38.0192930Z     you can make it a separate custom_op that you call inside ``backward_fn``.
2025-07-17T07:05:38.0193140Z 
2025-07-17T07:05:38.0193270Z     If you need different autograd behavior on different devices, then we
2025-07-17T07:05:38.0193610Z     recommend creating two different custom operators, one for each device
2025-07-17T07:05:38.0193960Z     that needs different behavior, and switching between them at runtime.
2025-07-17T07:05:38.0194160Z 
2025-07-17T07:05:38.0194210Z     Examples:
2025-07-17T07:05:38.0194340Z         >>> import torch
2025-07-17T07:05:38.0194490Z         >>> import numpy as np
2025-07-17T07:05:38.0194660Z         >>> from torch import Tensor
2025-07-17T07:05:38.0194830Z         >>>
2025-07-17T07:05:38.0195030Z         >>> @torch.library.custom_op("mylib::numpy_sin", mutates_args=())
2025-07-17T07:05:38.0195290Z         >>> def numpy_sin(x: Tensor) -> Tensor:
2025-07-17T07:05:38.0195490Z         >>>     x_np = x.cpu().numpy()
2025-07-17T07:05:38.0195670Z         >>>     y_np = np.sin(x_np)
2025-07-17T07:05:38.0195880Z         >>>     return torch.from_numpy(y_np).to(device=x.device)
2025-07-17T07:05:38.0196090Z         >>>
2025-07-17T07:05:38.0196250Z         >>> def setup_context(ctx, inputs, output) -> Tensor:
2025-07-17T07:05:38.0196450Z         >>>     x, = inputs
2025-07-17T07:05:38.0196620Z         >>>     ctx.save_for_backward(x)
2025-07-17T07:05:38.0196790Z         >>>
2025-07-17T07:05:38.0196910Z         >>> def backward(ctx, grad):
2025-07-17T07:05:38.0197080Z         >>>     x, = ctx.saved_tensors
2025-07-17T07:05:38.0197260Z         >>>     return grad * x.cos()
2025-07-17T07:05:38.0197420Z         >>>
2025-07-17T07:05:38.0197560Z         >>> torch.library.register_autograd(
2025-07-17T07:05:38.0197820Z         ...     "mylib::numpy_sin", backward, setup_context=setup_context
2025-07-17T07:05:38.0198040Z         ... )
2025-07-17T07:05:38.0198160Z         >>>
2025-07-17T07:05:38.0198300Z         >>> x = torch.randn(3, requires_grad=True)
2025-07-17T07:05:38.0198500Z         >>> y = numpy_sin(x)
2025-07-17T07:05:38.0198710Z         >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y))
2025-07-17T07:05:38.0198950Z         >>> assert torch.allclose(grad_x, x.cos())
2025-07-17T07:05:38.0199140Z         >>>
2025-07-17T07:05:38.0199280Z         >>> # Example with a keyword-only arg
2025-07-17T07:05:38.0199530Z         >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=())
2025-07-17T07:05:38.0199810Z         >>> def numpy_mul(x: Tensor, *, val: float) -> Tensor:
2025-07-17T07:05:38.0200030Z         >>>     x_np = x.cpu().numpy()
2025-07-17T07:05:38.0200220Z         >>>     y_np = x_np * val
2025-07-17T07:05:38.0200440Z         >>>     return torch.from_numpy(y_np).to(device=x.device)
2025-07-17T07:05:38.0200660Z         >>>
2025-07-17T07:05:38.0200870Z         >>> def setup_context(ctx, inputs, keyword_only_inputs, output) -> Tensor:
2025-07-17T07:05:38.0201150Z         >>>     ctx.val = keyword_only_inputs["val"]
2025-07-17T07:05:38.0201380Z         >>>
2025-07-17T07:05:38.0201500Z         >>> def backward(ctx, grad):
2025-07-17T07:05:38.0201680Z         >>>     return grad * ctx.val
2025-07-17T07:05:38.0201850Z         >>>
2025-07-17T07:05:38.0201990Z         >>> torch.library.register_autograd(
2025-07-17T07:05:38.0202230Z         ...     "mylib::numpy_mul", backward, setup_context=setup_context
2025-07-17T07:05:38.0202450Z         ... )
2025-07-17T07:05:38.0202570Z         >>>
2025-07-17T07:05:38.0202700Z         >>> x = torch.randn(3, requires_grad=True)
2025-07-17T07:05:38.0203040Z         >>> y = numpy_mul(x, val=3.14)
2025-07-17T07:05:38.0203340Z         >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y))
2025-07-17T07:05:38.0203680Z         >>> assert torch.allclose(grad_x, torch.full_like(x, 3.14))
2025-07-17T07:05:38.0203850Z 
2025-07-17T07:05:38.0203900Z     
2025-07-17T07:05:38.0204120Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.0204330Z 
2025-07-17T07:05:38.0204690Z msg = Cannot scrape callname=opcheck in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py line=1482.
2025-07-17T07:05:38.0205240Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.0205600Z Given an operator and some sample arguments, tests if the operator is
2025-07-17T07:05:38.0205850Z     registered correctly.
2025-07-17T07:05:38.0205960Z 
2025-07-17T07:05:38.0206090Z     That is, when you use the torch.library/TORCH_LIBRARY APIs to create a
2025-07-17T07:05:38.0206430Z     custom op, you specified metadata (e.g. mutability info) about the custom op
2025-07-17T07:05:38.0206780Z     and these APIs require that the functions you pass them satisfy certain
2025-07-17T07:05:38.0207130Z     properties (e.g. no data pointer access in the fake/meta/abstract kernel)
2025-07-17T07:05:38.0207420Z     ``opcheck`` tests these metadata and properties.
2025-07-17T07:05:38.0207580Z 
2025-07-17T07:05:38.0207650Z     Concretely, we test the following:
2025-07-17T07:05:38.0207790Z 
2025-07-17T07:05:38.0207890Z     - test_schema: If the schema matches the implementation of
2025-07-17T07:05:38.0208210Z       the operator. For example: if the schema specifies a Tensor is mutated,
2025-07-17T07:05:38.0208540Z       then we check the implementation mutates the Tensor. If the schema
2025-07-17T07:05:38.0208850Z       specifies that we return a new Tensor, then we check that the
2025-07-17T07:05:38.0209160Z       implementation returns a new Tensor (instead of an existing one or
2025-07-17T07:05:38.0209420Z       a view of an existing one).
2025-07-17T07:05:38.0209670Z     - test_autograd_registration: If the operator supports training
2025-07-17T07:05:38.0210070Z       (autograd): we check that its autograd formula is registered via
2025-07-17T07:05:38.0210400Z       torch.library.register_autograd or a manual registration to one
2025-07-17T07:05:38.0210770Z       or more DispatchKey::Autograd keys. Any other DispatchKey-based
2025-07-17T07:05:38.0217210Z       registrations may lead to undefined behavior.
2025-07-17T07:05:38.0217500Z     - test_faketensor: If the operator has a FakeTensor kernel
2025-07-17T07:05:38.0217790Z       (and if it is correct). The FakeTensor kernel is necessary (
2025-07-17T07:05:38.0218100Z       but not sufficient) for the operator to work with PyTorch compilation
2025-07-17T07:05:38.0218430Z       APIs (torch.compile/export/FX). We check that a FakeTensor kernel
2025-07-17T07:05:38.0218740Z       (also sometimes known as a meta kernel) was registered for the
2025-07-17T07:05:38.0219040Z       operator and that it is correct. This test takes the result of
2025-07-17T07:05:38.0219460Z       running the operator on real tensors and the result of running
2025-07-17T07:05:38.0219770Z       the operator on FakeTensors and checks that they have the same
2025-07-17T07:05:38.0220050Z       Tensor metadata (sizes/strides/dtype/device/etc).
2025-07-17T07:05:38.0220360Z     - test_aot_dispatch_dynamic: If the operator has correct behavior
2025-07-17T07:05:38.0220660Z       with PyTorch compilation APIs (torch.compile/export/FX).
2025-07-17T07:05:38.0220960Z       This checks that the outputs (and gradients, if applicable) are the
2025-07-17T07:05:38.0221240Z       same under eager-mode PyTorch and torch.compile.
2025-07-17T07:05:38.0221510Z       This test is a superset of ``test_faketensor`` and is an e2e test;
2025-07-17T07:05:38.0221790Z       other things it tests are that the operator supports
2025-07-17T07:05:38.0222080Z       functionalization and that the backward pass (if it exists) also
2025-07-17T07:05:38.0222350Z       supports FakeTensor and functionalization.
2025-07-17T07:05:38.0222600Z 
2025-07-17T07:05:38.0222800Z     For best results, please call ``opcheck`` multiple times with a
2025-07-17T07:05:38.0223090Z     representative set of inputs. If your operator supports
2025-07-17T07:05:38.0223410Z     autograd, please use ``opcheck`` with inputs with ``requires_grad = True``;
2025-07-17T07:05:38.0223760Z     if your operator supports multiple devices (e.g. CPU and CUDA), please
2025-07-17T07:05:38.0224060Z     use ``opcheck`` with inputs on all supported devices.
2025-07-17T07:05:38.0224230Z 
2025-07-17T07:05:38.0224270Z     Args:
2025-07-17T07:05:38.0224450Z         op: The operator. Must either be a function decorated with
2025-07-17T07:05:38.0224760Z             :func:`torch.library.custom_op` or an OpOverload/OpOverloadPacket
2025-07-17T07:05:38.0225100Z             found in torch.ops.* (e.g. torch.ops.aten.sin, torch.ops.mylib.foo)
2025-07-17T07:05:38.0225360Z         args: The args to the operator
2025-07-17T07:05:38.0225560Z         kwargs: The kwargs to the operator
2025-07-17T07:05:38.0225810Z         test_utils: Tests that we should run. Default: all of them.
2025-07-17T07:05:38.0226070Z             Example: ("test_schema", "test_faketensor")
2025-07-17T07:05:38.0226340Z         raise_exception: If we should raise an exception on the first
2025-07-17T07:05:38.0226630Z             error. If False, we will return a dict with information
2025-07-17T07:05:38.0226870Z             on if each test passed or not.
2025-07-17T07:05:38.0227150Z         rtol (Optional[float]): Relative tolerance for floating point comparisons.
2025-07-17T07:05:38.0227450Z             If specified ``atol`` must also be specified.
2025-07-17T07:05:38.0227720Z             If omitted, default values based on the ``dtype`` are selected
2025-07-17T07:05:38.0228010Z             (see the table in :func:`torch.testing.assert_close`).
2025-07-17T07:05:38.0228320Z         atol (Optional[float]): Absolute tolerance for floating point comparisons.
2025-07-17T07:05:38.0228620Z             If specified ``rtol`` must also be specified.
2025-07-17T07:05:38.0228880Z             If omitted, default values based on the ``dtype`` are selected
2025-07-17T07:05:38.0229170Z             (see the table in :func:`torch.testing.assert_close`).
2025-07-17T07:05:38.0229340Z 
2025-07-17T07:05:38.0229390Z     .. warning::
2025-07-17T07:05:38.0229490Z 
2025-07-17T07:05:38.0229630Z         opcheck and :func:`torch.autograd.gradcheck` test different things;
2025-07-17T07:05:38.0229950Z         opcheck tests if your usage of torch.library APIs is correct while
2025-07-17T07:05:38.0230270Z         :func:`torch.autograd.gradcheck` tests if your autograd formula is
2025-07-17T07:05:38.0230600Z         mathematically correct. Use both to test custom ops that support
2025-07-17T07:05:38.0230850Z         gradient computation.
2025-07-17T07:05:38.0230960Z 
2025-07-17T07:05:38.0231010Z     Example:
2025-07-17T07:05:38.0231080Z 
2025-07-17T07:05:38.0231170Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-07-17T07:05:38.0231440Z         >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=())
2025-07-17T07:05:38.0231770Z         >>> def numpy_mul(x: Tensor, y: float) -> Tensor:
2025-07-17T07:05:38.0231980Z         >>>     x_np = x.numpy(force=True)
2025-07-17T07:05:38.0232160Z         >>>     z_np = x_np * y
2025-07-17T07:05:38.0232380Z         >>>     return torch.from_numpy(z_np).to(x.device)
2025-07-17T07:05:38.0232570Z         >>>
2025-07-17T07:05:38.0232700Z         >>> @numpy_mul.register_fake
2025-07-17T07:05:38.0232870Z         >>> def _(x, y):
2025-07-17T07:05:38.0233040Z         >>>     return torch.empty_like(x)
2025-07-17T07:05:38.0233250Z         >>>
2025-07-17T07:05:38.0233390Z         >>> def setup_context(ctx, inputs, output):
2025-07-17T07:05:38.0233590Z         >>>     y, = inputs
2025-07-17T07:05:38.0233740Z         >>>     ctx.y = y
2025-07-17T07:05:38.0233880Z         >>>
2025-07-17T07:05:38.0234000Z         >>> def backward(ctx, grad):
2025-07-17T07:05:38.0234260Z         >>>     return grad * ctx.y, None
2025-07-17T07:05:38.0234500Z         >>>
2025-07-17T07:05:38.0234700Z         >>> numpy_mul.register_autograd(backward, setup_context=setup_context)
2025-07-17T07:05:38.0234940Z         >>>
2025-07-17T07:05:38.0235060Z         >>> sample_inputs = [
2025-07-17T07:05:38.0235240Z         >>>     (torch.randn(3), 3.14),
2025-07-17T07:05:38.0235450Z         >>>     (torch.randn(2, 3, device='cuda'), 2.718),
2025-07-17T07:05:38.0235680Z         >>>     (torch.randn(1, 10, requires_grad=True), 1.234),
2025-07-17T07:05:38.0235950Z         >>>     (torch.randn(64, 64, device='cuda', requires_grad=True), 90.18),
2025-07-17T07:05:38.0236180Z         >>> ]
2025-07-17T07:05:38.0236290Z         >>>
2025-07-17T07:05:38.0236420Z         >>> for args in sample_inputs:
2025-07-17T07:05:38.0236630Z         >>>     torch.library.opcheck(numpy_mul, args)
2025-07-17T07:05:38.0236770Z 
2025-07-17T07:05:38.0236820Z     
2025-07-17T07:05:38.0237030Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.0237250Z 
2025-07-17T07:05:38.0237630Z msg = Cannot scrape callname=Tensor.dim_order in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py line=1493.
2025-07-17T07:05:38.0238210Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.0238440Z 
2025-07-17T07:05:38.0238510Z dim_order(ambiguity_check=False) -> tuple
2025-07-17T07:05:38.0238650Z 
2025-07-17T07:05:38.0238790Z Returns the uniquely determined tuple of int describing the dim order or
2025-07-17T07:05:38.0239060Z physical layout of :attr:`self`.
2025-07-17T07:05:38.0239180Z 
2025-07-17T07:05:38.0239330Z The dim order represents how dimensions are laid out in memory of dense tensors,
2025-07-17T07:05:38.0239650Z starting from the outermost to the innermost dimension.
2025-07-17T07:05:38.0239820Z 
2025-07-17T07:05:38.0239930Z Note that the dim order may not always be uniquely determined.
2025-07-17T07:05:38.0240350Z If `ambiguity_check` is True, this function raises a RuntimeError when the dim order cannot be uniquely determined;
2025-07-17T07:05:38.0240870Z If `ambiguity_check` is a list of memory formats, this function raises a RuntimeError when tensor can not be interpreted
2025-07-17T07:05:38.0241330Z into exactly one of the given memory formats, or it cannot be uniquely determined.
2025-07-17T07:05:38.0241750Z If `ambiguity_check` is False, it will return one of legal dim order(s) without checking its uniqueness.
2025-07-17T07:05:38.0242080Z Otherwise, it will raise TypeError.
2025-07-17T07:05:38.0242200Z 
2025-07-17T07:05:38.0242250Z Args:
2025-07-17T07:05:38.0242500Z     ambiguity_check (bool or List[torch.memory_format]): The check method for ambiguity of dim order.
2025-07-17T07:05:38.0242760Z 
2025-07-17T07:05:38.0242810Z Examples::
2025-07-17T07:05:38.0242880Z 
2025-07-17T07:05:38.0242950Z     >>> torch.empty((2, 3, 5, 7)).dim_order()
2025-07-17T07:05:38.0243130Z     (0, 1, 2, 3)
2025-07-17T07:05:38.0243310Z     >>> torch.empty((2, 3, 5, 7)).transpose(1, 2).dim_order()
2025-07-17T07:05:38.0243560Z     (0, 2, 1, 3)
2025-07-17T07:05:38.0243770Z     >>> torch.empty((2, 3, 5, 7), memory_format=torch.channels_last).dim_order()
2025-07-17T07:05:38.0244000Z     (0, 2, 3, 1)
2025-07-17T07:05:38.0244150Z     >>> torch.empty((1, 2, 3, 4)).dim_order()
2025-07-17T07:05:38.0244340Z     (0, 1, 2, 3)
2025-07-17T07:05:38.0244460Z     >>> try:
2025-07-17T07:05:38.0244640Z     ...     torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check=True)
2025-07-17T07:05:38.0244870Z     ... except RuntimeError as e:
2025-07-17T07:05:38.0245040Z     ...     print(e)
2025-07-17T07:05:38.0245320Z     The tensor does not have unique dim order, or cannot map to exact one of the given memory formats.
2025-07-17T07:05:38.0245640Z     >>> torch.empty((1, 2, 3, 4)).dim_order(
2025-07-17T07:05:38.0245900Z     ...     ambiguity_check=[torch.contiguous_format, torch.channels_last]
2025-07-17T07:05:38.0246170Z     ... )  # It can be mapped to contiguous format
2025-07-17T07:05:38.0246440Z     (0, 1, 2, 3)
2025-07-17T07:05:38.0246620Z     >>> try:
2025-07-17T07:05:38.0246810Z     ...     torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check="ILLEGAL")
2025-07-17T07:05:38.0247040Z     ... except TypeError as e:
2025-07-17T07:05:38.0247200Z     ...     print(e)
2025-07-17T07:05:38.0247430Z     The ambiguity_check argument must be a bool or a list of memory formats.
2025-07-17T07:05:38.0247640Z 
2025-07-17T07:05:38.0247680Z .. warning::
2025-07-17T07:05:38.0247880Z     The dim_order tensor API is experimental and subject to change.
2025-07-17T07:05:38.0248060Z 
2025-07-17T07:05:38.0248220Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.0248430Z 
2025-07-17T07:05:38.0248760Z msg = Cannot scrape callname=load in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/hub.py line=560.
2025-07-17T07:05:38.0249300Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.0249520Z 
2025-07-17T07:05:38.0249620Z Load a model from a github repo or a local directory.
2025-07-17T07:05:38.0249780Z 
2025-07-17T07:05:38.0249920Z Note: Loading a model is the typical use case, but this can also be used to
2025-07-17T07:05:38.0250250Z for loading other objects such as tokenizers, loss functions, etc.
2025-07-17T07:05:38.0250450Z 
2025-07-17T07:05:38.0250550Z If ``source`` is 'github', ``repo_or_dir`` is expected to be
2025-07-17T07:05:38.0250820Z of the form ``repo_owner/repo_name[:ref]`` with an optional
2025-07-17T07:05:38.0251040Z ref (a tag or a branch).
2025-07-17T07:05:38.0251140Z 
2025-07-17T07:05:38.0251240Z If ``source`` is 'local', ``repo_or_dir`` is expected to be a
2025-07-17T07:05:38.0251470Z path to a local directory.
2025-07-17T07:05:38.0251570Z 
2025-07-17T07:05:38.0251620Z Args:
2025-07-17T07:05:38.0251760Z     repo_or_dir (str): If ``source`` is 'github',
2025-07-17T07:05:38.0252080Z         this should correspond to a github repo with format ``repo_owner/repo_name[:ref]`` with
2025-07-17T07:05:38.0252500Z         an optional ref (tag or branch), for example 'pytorch/vision:0.10'. If ``ref`` is not specified,
2025-07-17T07:05:38.0252900Z         the default branch is assumed to be ``main`` if it exists, and otherwise ``master``.
2025-07-17T07:05:38.0253250Z         If ``source`` is 'local'  then it should be a path to a local directory.
2025-07-17T07:05:38.0253560Z     model (str): the name of a callable (entrypoint) defined in the
2025-07-17T07:05:38.0253800Z         repo/dir's ``hubconf.py``.
2025-07-17T07:05:38.0254050Z     *args (optional): the corresponding args for callable ``model``.
2025-07-17T07:05:38.0254340Z     source (str, optional): 'github' or 'local'. Specifies how
2025-07-17T07:05:38.0254620Z         ``repo_or_dir`` is to be interpreted. Default is 'github'.
2025-07-17T07:05:38.0254920Z     trust_repo (bool, str or None): ``"check"``, ``True``, ``False`` or ``None``.
2025-07-17T07:05:38.0255260Z         This parameter was introduced in v1.12 and helps ensuring that users
2025-07-17T07:05:38.0255580Z         only run code from repos that they trust.
2025-07-17T07:05:38.0255720Z 
2025-07-17T07:05:38.0255840Z         - If ``False``, a prompt will ask the user whether the repo should
2025-07-17T07:05:38.0256070Z           be trusted.
2025-07-17T07:05:38.0256340Z         - If ``True``, the repo will be added to the trusted list and loaded
2025-07-17T07:05:38.0256590Z           without requiring explicit confirmation.
2025-07-17T07:05:38.0256850Z         - If ``"check"``, the repo will be checked against the list of
2025-07-17T07:05:38.0257140Z           trusted repos in the cache. If it is not present in that list, the
2025-07-17T07:05:38.0257450Z           behaviour will fall back onto the ``trust_repo=False`` option.
2025-07-17T07:05:38.0257740Z         - If ``None``: this will raise a warning, inviting the user to set
2025-07-17T07:05:38.0258030Z           ``trust_repo`` to either ``False``, ``True`` or ``"check"``. This
2025-07-17T07:05:38.0258390Z           is only present for backward compatibility and will be removed in
2025-07-17T07:05:38.0258680Z           v2.0.
2025-07-17T07:05:38.0258760Z 
2025-07-17T07:05:38.0258890Z         Default is ``None`` and will eventually change to ``"check"`` in v2.0.
2025-07-17T07:05:38.0259210Z     force_reload (bool, optional): whether to force a fresh download of
2025-07-17T07:05:38.0259530Z         the github repo unconditionally. Does not have any effect if
2025-07-17T07:05:38.0259780Z         ``source = 'local'``. Default is ``False``.
2025-07-17T07:05:38.0260050Z     verbose (bool, optional): If ``False``, mute messages about hitting
2025-07-17T07:05:38.0260360Z         local caches. Note that the message about first download cannot be
2025-07-17T07:05:38.0260660Z         muted. Does not have any effect if ``source = 'local'``.
2025-07-17T07:05:38.0260890Z         Default is ``True``.
2025-07-17T07:05:38.0261170Z     skip_validation (bool, optional): if ``False``, torchhub will check that the branch or commit
2025-07-17T07:05:38.0261590Z         specified by the ``github`` argument properly belongs to the repo owner. This will make
2025-07-17T07:05:38.0261990Z         requests to the GitHub API; you can specify a non-default GitHub token by setting the
2025-07-17T07:05:38.0262330Z         ``GITHUB_TOKEN`` environment variable. Default is ``False``.
2025-07-17T07:05:38.0262630Z     **kwargs (optional): the corresponding kwargs for callable ``model``.
2025-07-17T07:05:38.0262830Z 
2025-07-17T07:05:38.0262870Z Returns:
2025-07-17T07:05:38.0263050Z     The output of the ``model`` callable when called with the given
2025-07-17T07:05:38.0263290Z     ``*args`` and ``**kwargs``.
2025-07-17T07:05:38.0263400Z 
2025-07-17T07:05:38.0263450Z Example:
2025-07-17T07:05:38.0263600Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB)
2025-07-17T07:05:38.0263800Z     >>> # from a github repo
2025-07-17T07:05:38.0263960Z     >>> repo = "pytorch/vision"
2025-07-17T07:05:38.0264130Z     >>> model = torch.hub.load(
2025-07-17T07:05:38.0264350Z     ...     repo, "resnet50", weights="ResNet50_Weights.IMAGENET1K_V1"
2025-07-17T07:05:38.0264580Z     ... )
2025-07-17T07:05:38.0264700Z     >>> # from a local directory
2025-07-17T07:05:38.0264890Z     >>> path = "/some/local/path/pytorch/vision"
2025-07-17T07:05:38.0265080Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:38.0265330Z     >>> model = torch.hub.load(path, "resnet50", weights="ResNet50_Weights.DEFAULT")
2025-07-17T07:05:38.0265550Z 
2025-07-17T07:05:38.0265700Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.0702010Z 
2025-07-17T07:05:38.0702530Z msg = Cannot scrape callname=_load_local in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/hub.py line=652.
2025-07-17T07:05:38.0703120Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.0703420Z 
2025-07-17T07:05:38.0703540Z Load a model from a local directory with a ``hubconf.py``.
2025-07-17T07:05:38.0703720Z 
2025-07-17T07:05:38.0703770Z Args:
2025-07-17T07:05:38.0704080Z     hubconf_dir (str): path to a local directory that contains a
2025-07-17T07:05:38.0704320Z         ``hubconf.py``.
2025-07-17T07:05:38.0704540Z     model (str): name of an entrypoint defined in the directory's
2025-07-17T07:05:38.0704840Z         ``hubconf.py``.
2025-07-17T07:05:38.0705060Z     *args (optional): the corresponding args for callable ``model``.
2025-07-17T07:05:38.0705390Z     **kwargs (optional): the corresponding kwargs for callable ``model``.
2025-07-17T07:05:38.0705590Z 
2025-07-17T07:05:38.0705640Z Returns:
2025-07-17T07:05:38.0705810Z     a single model with corresponding pretrained weights.
2025-07-17T07:05:38.0705980Z 
2025-07-17T07:05:38.0706030Z Example:
2025-07-17T07:05:38.0706170Z     >>> # xdoctest: +SKIP("stub local path")
2025-07-17T07:05:38.0706370Z     >>> path = "/some/local/path/pytorch/vision"
2025-07-17T07:05:38.0706570Z     >>> model = _load_local(
2025-07-17T07:05:38.0706870Z     ...     path,
2025-07-17T07:05:38.0707080Z     ...     "resnet50",
2025-07-17T07:05:38.0707260Z     ...     weights="ResNet50_Weights.IMAGENET1K_V1",
2025-07-17T07:05:38.0707460Z     ... )
2025-07-17T07:05:38.0707520Z 
2025-07-17T07:05:38.0707680Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.0707890Z 
2025-07-17T07:05:38.0708250Z msg = Cannot scrape callname=download_url_to_file in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/hub.py line=691.
2025-07-17T07:05:38.0708820Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.0709130Z Download object at the given URL to a local path.
2025-07-17T07:05:38.0709280Z 
2025-07-17T07:05:38.0709330Z     Args:
2025-07-17T07:05:38.0709470Z         url (str): URL of the object to download
2025-07-17T07:05:38.0709750Z         dst (str): Full path where object will be saved, e.g. ``/tmp/temporary_file``
2025-07-17T07:05:38.0710160Z         hash_prefix (str, optional): If not None, the SHA256 downloaded file should start with ``hash_prefix``.
2025-07-17T07:05:38.0710480Z             Default: None
2025-07-17T07:05:38.0710740Z         progress (bool, optional): whether or not to display a progress bar to stderr
2025-07-17T07:05:38.0711020Z             Default: True
2025-07-17T07:05:38.0711120Z 
2025-07-17T07:05:38.0711160Z     Example:
2025-07-17T07:05:38.0711310Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB)
2025-07-17T07:05:38.0711530Z         >>> # xdoctest: +REQUIRES(POSIX)
2025-07-17T07:05:38.0711730Z         >>> torch.hub.download_url_to_file(
2025-07-17T07:05:38.0712000Z         ...     "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth",
2025-07-17T07:05:38.0712270Z         ...     "/tmp/temporary_file",
2025-07-17T07:05:38.0712460Z         ... )
2025-07-17T07:05:38.0712540Z 
2025-07-17T07:05:38.0712580Z     
2025-07-17T07:05:38.0712790Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.0713000Z 
2025-07-17T07:05:38.0713370Z msg = Cannot scrape callname=load_state_dict_from_url in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/hub.py line=816.
2025-07-17T07:05:38.0713950Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.0714260Z Loads the Torch serialized object at the given URL.
2025-07-17T07:05:38.0714420Z 
2025-07-17T07:05:38.0714530Z     If downloaded file is a zip file, it will be automatically
2025-07-17T07:05:38.0714760Z     decompressed.
2025-07-17T07:05:38.0714850Z 
2025-07-17T07:05:38.0714980Z     If the object is already present in `model_dir`, it's deserialized and
2025-07-17T07:05:38.0715220Z     returned.
2025-07-17T07:05:38.0715430Z     The default value of ``model_dir`` is ``<hub_dir>/checkpoints`` where
2025-07-17T07:05:38.0715750Z     ``hub_dir`` is the directory returned by :func:`~torch.hub.get_dir`.
2025-07-17T07:05:38.0715930Z 
2025-07-17T07:05:38.0715980Z     Args:
2025-07-17T07:05:38.0716140Z         url (str): URL of the object to download
2025-07-17T07:05:38.0716410Z         model_dir (str, optional): directory in which to save the object
2025-07-17T07:05:38.0716800Z         map_location (optional): a function or a dict specifying how to remap storage locations (see torch.load)
2025-07-17T07:05:38.0717290Z         progress (bool, optional): whether or not to display a progress bar to stderr.
2025-07-17T07:05:38.0717560Z             Default: True
2025-07-17T07:05:38.0717860Z         check_hash(bool, optional): If True, the filename part of the URL should follow the naming convention
2025-07-17T07:05:38.0718260Z             ``filename-<sha256>.ext`` where ``<sha256>`` is the first eight or more
2025-07-17T07:05:38.0718600Z             digits of the SHA256 hash of the contents of the file. The hash is used to
2025-07-17T07:05:38.0718930Z             ensure unique names and to verify the contents of the file.
2025-07-17T07:05:38.0719220Z             Default: False
2025-07-17T07:05:38.0719580Z         file_name (str, optional): name for the downloaded file. Filename from ``url`` will be used if not set.
2025-07-17T07:05:38.0720050Z         weights_only(bool, optional): If True, only weights will be loaded and no complex pickled objects.
2025-07-17T07:05:38.0720470Z             Recommended for untrusted sources. See :func:`~torch.load` for more details.
2025-07-17T07:05:38.0720690Z 
2025-07-17T07:05:38.0720740Z     Example:
2025-07-17T07:05:38.0720890Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB)
2025-07-17T07:05:38.0721130Z         >>> state_dict = torch.hub.load_state_dict_from_url(
2025-07-17T07:05:38.0721420Z         ...     "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth"
2025-07-17T07:05:38.0721670Z         ... )
2025-07-17T07:05:38.0721740Z 
2025-07-17T07:05:38.0721780Z     
2025-07-17T07:05:38.0721990Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.0722240Z 
2025-07-17T07:05:38.0722650Z msg = Cannot scrape callname=meshgrid in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py line=446.
2025-07-17T07:05:38.0723300Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.0723680Z Creates grids of coordinates specified by the 1D inputs in `attr`:tensors.
2025-07-17T07:05:38.0723930Z 
2025-07-17T07:05:38.0724050Z         This is helpful when you want to visualize data over some
2025-07-17T07:05:38.0729940Z         range of inputs. See below for a plotting example.
2025-07-17T07:05:38.0730120Z 
2025-07-17T07:05:38.0730230Z         Given :math:`N` 1D tensors :math:`T_0 \ldots T_{N-1}` as
2025-07-17T07:05:38.0730510Z         inputs with corresponding sizes :math:`S_0 \ldots S_{N-1}`,
2025-07-17T07:05:38.0730810Z         this creates :math:`N` N-dimensional tensors :math:`G_0 \ldots
2025-07-17T07:05:38.0731080Z         G_{N-1}`, each with shape :math:`(S_0, ..., S_{N-1})` where
2025-07-17T07:05:38.0731370Z         the output :math:`G_i` is constructed by expanding :math:`T_i`
2025-07-17T07:05:38.0731610Z         to the result shape.
2025-07-17T07:05:38.0731730Z 
2025-07-17T07:05:38.0731790Z         .. note::
2025-07-17T07:05:38.0731970Z             0D inputs are treated equivalently to 1D inputs of a
2025-07-17T07:05:38.0732200Z             single element.
2025-07-17T07:05:38.0732300Z 
2025-07-17T07:05:38.0732350Z         .. warning::
2025-07-17T07:05:38.0732550Z             `torch.meshgrid(*tensors)` currently has the same behavior
2025-07-17T07:05:38.0732830Z             as calling `numpy.meshgrid(*arrays, indexing='ij')`.
2025-07-17T07:05:38.0732990Z 
2025-07-17T07:05:38.0733090Z             In the future `torch.meshgrid` will transition to
2025-07-17T07:05:38.0733310Z             `indexing='xy'` as the default.
2025-07-17T07:05:38.0733440Z 
2025-07-17T07:05:38.0733550Z             https://github.com/pytorch/pytorch/issues/50276 tracks
2025-07-17T07:05:38.0733840Z             this issue with the goal of migrating to NumPy's behavior.
2025-07-17T07:05:38.0734020Z 
2025-07-17T07:05:38.0734160Z         .. seealso::
2025-07-17T07:05:38.0734250Z 
2025-07-17T07:05:38.0734360Z             :func:`torch.cartesian_prod` has the same effect but it
2025-07-17T07:05:38.0734610Z             collects the data in a tensor of vectors.
2025-07-17T07:05:38.0734790Z 
2025-07-17T07:05:38.0734840Z         Args:
2025-07-17T07:05:38.0735070Z             tensors (list of Tensor): list of scalars or 1 dimensional tensors. Scalars will be
2025-07-17T07:05:38.0735400Z                 treated as tensors of size :math:`(1,)` automatically
2025-07-17T07:05:38.0735570Z 
2025-07-17T07:05:38.0735680Z             indexing: (str, optional): the indexing mode, either "xy"
2025-07-17T07:05:38.0735960Z                 or "ij", defaults to "ij". See warning for future changes.
2025-07-17T07:05:38.0736130Z 
2025-07-17T07:05:38.0736230Z                 If "xy" is selected, the first dimension corresponds
2025-07-17T07:05:38.0736560Z                 to the cardinality of the second input and the second
2025-07-17T07:05:38.0736890Z                 dimension corresponds to the cardinality of the first
2025-07-17T07:05:38.0737110Z                 input.
2025-07-17T07:05:38.0737200Z 
2025-07-17T07:05:38.0737290Z                 If "ij" is selected, the dimensions are in the same
2025-07-17T07:05:38.0737530Z                 order as the cardinality of the inputs.
2025-07-17T07:05:38.0737680Z 
2025-07-17T07:05:38.0737730Z         Returns:
2025-07-17T07:05:38.0737910Z             seq (sequence of Tensors): If the input has :math:`N`
2025-07-17T07:05:38.0738170Z             tensors of size :math:`S_0 \ldots S_{N-1}``, then the
2025-07-17T07:05:38.0738440Z             output will also have :math:`N` tensors, where each tensor
2025-07-17T07:05:38.0738700Z             is of shape :math:`(S_0, ..., S_{N-1})`.
2025-07-17T07:05:38.0738840Z 
2025-07-17T07:05:38.0738880Z         Example::
2025-07-17T07:05:38.0738970Z 
2025-07-17T07:05:38.0739030Z             >>> x = torch.tensor([1, 2, 3])
2025-07-17T07:05:38.0739230Z             >>> y = torch.tensor([4, 5, 6])
2025-07-17T07:05:38.0739360Z 
2025-07-17T07:05:38.0739480Z             Observe the element-wise pairings across the grid, (1, 4),
2025-07-17T07:05:38.0739740Z             (1, 5), ..., (3, 6). This is the same thing as the
2025-07-17T07:05:38.0739940Z             cartesian product.
2025-07-17T07:05:38.0740160Z             >>> grid_x, grid_y = torch.meshgrid(x, y, indexing='ij')
2025-07-17T07:05:38.0740370Z             >>> grid_x
2025-07-17T07:05:38.0740510Z             tensor([[1, 1, 1],
2025-07-17T07:05:38.0740660Z                     [2, 2, 2],
2025-07-17T07:05:38.0740810Z                     [3, 3, 3]])
2025-07-17T07:05:38.0740960Z             >>> grid_y
2025-07-17T07:05:38.0741100Z             tensor([[4, 5, 6],
2025-07-17T07:05:38.0741260Z                     [4, 5, 6],
2025-07-17T07:05:38.0741410Z                     [4, 5, 6]])
2025-07-17T07:05:38.0741510Z 
2025-07-17T07:05:38.0741620Z             This correspondence can be seen when these grids are
2025-07-17T07:05:38.0741840Z             stacked properly.
2025-07-17T07:05:38.0742070Z             >>> torch.equal(torch.cat(tuple(torch.dstack([grid_x, grid_y]))),
2025-07-17T07:05:38.0742340Z             ...             torch.cartesian_prod(x, y))
2025-07-17T07:05:38.0742530Z             True
2025-07-17T07:05:38.0742610Z 
2025-07-17T07:05:38.0742720Z             `torch.meshgrid` is commonly used to produce a grid for
2025-07-17T07:05:38.0742940Z             plotting.
2025-07-17T07:05:38.0743110Z             >>> # xdoctest: +REQUIRES(module:matplotlib)
2025-07-17T07:05:38.0743330Z             >>> # xdoctest: +REQUIRES(env:DOCTEST_SHOW)
2025-07-17T07:05:38.0743550Z             >>> import matplotlib.pyplot as plt
2025-07-17T07:05:38.0743780Z             >>> xs = torch.linspace(-5, 5, steps=100)
2025-07-17T07:05:38.0744000Z             >>> ys = torch.linspace(-5, 5, steps=100)
2025-07-17T07:05:38.0744220Z             >>> x, y = torch.meshgrid(xs, ys, indexing='xy')
2025-07-17T07:05:38.0744500Z             >>> z = torch.sin(torch.sqrt(x * x + y * y))
2025-07-17T07:05:38.0744720Z             >>> ax = plt.axes(projection='3d')
2025-07-17T07:05:38.0744950Z             >>> ax.plot_surface(x.numpy(), y.numpy(), z.numpy())
2025-07-17T07:05:38.0745480Z             >>> plt.show()
2025-07-17T07:05:38.0745610Z 
2025-07-17T07:05:38.0745690Z         .. image:: ../_static/img/meshgrid.png
2025-07-17T07:05:38.0745870Z             :width: 512
2025-07-17T07:05:38.0745970Z 
2025-07-17T07:05:38.0746010Z         
2025-07-17T07:05:38.0746230Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.0746450Z 
2025-07-17T07:05:38.0746820Z msg = Cannot scrape callname=_unique_impl in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py line=842.
2025-07-17T07:05:38.0747390Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.0747900Z unique(input, sorted=True, return_inverse=False, return_counts=False, dim=None) -> tuple[Tensor, Tensor, Tensor]
2025-07-17T07:05:38.0748250Z 
2025-07-17T07:05:38.0748340Z     Returns the unique elements of the input tensor.
2025-07-17T07:05:38.0748500Z 
2025-07-17T07:05:38.0748680Z     .. note:: This function is different from :func:`torch.unique_consecutive` in the sense that
2025-07-17T07:05:38.0749050Z         this function also eliminates non-consecutive duplicate values.
2025-07-17T07:05:38.0749240Z 
2025-07-17T07:05:38.0749380Z     .. note:: Currently in the CUDA implementation and the CPU implementation,
2025-07-17T07:05:38.0749750Z         `torch.unique` always sort the tensor at the beginning regardless of the `sort` argument.
2025-07-17T07:05:38.0750160Z         Sorting could be slow, so if your input tensor is already sorted, it is recommended to use
2025-07-17T07:05:38.0750510Z         :func:`torch.unique_consecutive` which avoids the sorting.
2025-07-17T07:05:38.0750680Z 
2025-07-17T07:05:38.0750730Z     Args:
2025-07-17T07:05:38.0750870Z         input (Tensor): the input tensor
2025-07-17T07:05:38.0751130Z         sorted (bool): Whether to sort the unique elements in ascending order
2025-07-17T07:05:38.0751380Z             before returning as output.
2025-07-17T07:05:38.0751650Z         return_inverse (bool): Whether to also return the indices for where
2025-07-17T07:05:38.0751980Z             elements in the original input ended up in the returned unique list.
2025-07-17T07:05:38.0752310Z         return_counts (bool): Whether to also return the counts for each unique
2025-07-17T07:05:38.0752560Z             element.
2025-07-17T07:05:38.0752770Z         dim (int, optional): the dimension to operate upon. If ``None``, the
2025-07-17T07:05:38.0753090Z             unique of the flattened input is returned. Otherwise, each of the
2025-07-17T07:05:38.0753400Z             tensors indexed by the given dimension is treated as one of the
2025-07-17T07:05:38.0753720Z             elements to apply the unique operation upon. See examples for more
2025-07-17T07:05:38.0753980Z             details. Default: ``None``
2025-07-17T07:05:38.0754110Z 
2025-07-17T07:05:38.0754150Z     Returns:
2025-07-17T07:05:38.0754400Z         (Tensor, Tensor (optional), Tensor (optional)): A tensor or a tuple of tensors containing
2025-07-17T07:05:38.0754640Z 
2025-07-17T07:05:38.0754760Z             - **output** (*Tensor*): the output list of unique scalar elements.
2025-07-17T07:05:38.0755040Z             - **inverse_indices** (*Tensor*): (optional) if
2025-07-17T07:05:38.0755310Z               :attr:`return_inverse` is True, there will be an additional
2025-07-17T07:05:38.0755610Z               returned tensor (same shape as input) representing the indices
2025-07-17T07:05:38.0755930Z               for where elements in the original input map to in the output;
2025-07-17T07:05:38.0756220Z               otherwise, this function will only return a single tensor.
2025-07-17T07:05:38.0756480Z             - **counts** (*Tensor*): (optional) if
2025-07-17T07:05:38.0756780Z               :attr:`return_counts` is True, there will be an additional
2025-07-17T07:05:38.0757070Z               returned tensor (same shape as output or output.size(dim),
2025-07-17T07:05:38.0757360Z               if dim was specified) representing the number of occurrences
2025-07-17T07:05:38.0757630Z               for each unique value or tensor.
2025-07-17T07:05:38.0757770Z 
2025-07-17T07:05:38.0757820Z     Example::
2025-07-17T07:05:38.0757900Z 
2025-07-17T07:05:38.0758030Z         >>> output = torch.unique(torch.tensor([1, 3, 2, 3], dtype=torch.long))
2025-07-17T07:05:38.0758270Z         >>> output
2025-07-17T07:05:38.0758410Z         tensor([1, 2, 3])
2025-07-17T07:05:38.0758510Z 
2025-07-17T07:05:38.0758580Z         >>> output, inverse_indices = torch.unique(
2025-07-17T07:05:38.0758870Z         ...     torch.tensor([1, 3, 2, 3], dtype=torch.long), sorted=True, return_inverse=True)
2025-07-17T07:05:38.0759120Z         >>> output
2025-07-17T07:05:38.0759330Z         tensor([1, 2, 3])
2025-07-17T07:05:38.0759540Z         >>> inverse_indices
2025-07-17T07:05:38.0759700Z         tensor([0, 2, 1, 2])
2025-07-17T07:05:38.0759800Z 
2025-07-17T07:05:38.0759880Z         >>> output, inverse_indices = torch.unique(
2025-07-17T07:05:38.0760170Z         ...     torch.tensor([[1, 3], [2, 3]], dtype=torch.long), sorted=True, return_inverse=True)
2025-07-17T07:05:38.0760420Z         >>> output
2025-07-17T07:05:38.0760550Z         tensor([1, 2, 3])
2025-07-17T07:05:38.0760700Z         >>> inverse_indices
2025-07-17T07:05:38.0760850Z         tensor([[0, 2],
2025-07-17T07:05:38.0760990Z                 [1, 2]])
2025-07-17T07:05:38.0761080Z 
2025-07-17T07:05:38.0761140Z         >>> a = torch.tensor([
2025-07-17T07:05:38.0761290Z         ...     [
2025-07-17T07:05:38.0761420Z         ...         [1, 1, 0, 0],
2025-07-17T07:05:38.0761590Z         ...         [1, 1, 0, 0],
2025-07-17T07:05:38.0761740Z         ...         [0, 0, 1, 1],
2025-07-17T07:05:38.0761890Z         ...     ],
2025-07-17T07:05:38.0762020Z         ...     [
2025-07-17T07:05:38.0762150Z         ...         [0, 0, 1, 1],
2025-07-17T07:05:38.0762300Z         ...         [0, 0, 1, 1],
2025-07-17T07:05:38.0762460Z         ...         [1, 1, 1, 1],
2025-07-17T07:05:38.0762610Z         ...     ],
2025-07-17T07:05:38.0762730Z         ...     [
2025-07-17T07:05:38.0762860Z         ...         [1, 1, 0, 0],
2025-07-17T07:05:38.0763010Z         ...         [1, 1, 0, 0],
2025-07-17T07:05:38.0763170Z         ...         [0, 0, 1, 1],
2025-07-17T07:05:38.0763320Z         ...     ],
2025-07-17T07:05:38.0763440Z         ... ])
2025-07-17T07:05:38.0763510Z 
2025-07-17T07:05:38.0763640Z         >>> # If we call `torch.unique(a, dim=0)`, each of the tensors `a[idx, :, :]`
2025-07-17T07:05:38.0763980Z         >>> # will be compared. We can see that `a[0, :, :]` and `a[2, :, :]` match
2025-07-17T07:05:38.0764260Z         >>> # each other, so one of them will be removed.
2025-07-17T07:05:38.0764460Z         >>> (a[0, :, :] == a[2, :, :]).all()
2025-07-17T07:05:38.0764640Z         tensor(True)
2025-07-17T07:05:38.0764800Z         >>> a_unique_dim0 = torch.unique(a, dim=0)
2025-07-17T07:05:38.0765000Z         >>> a_unique_dim0
2025-07-17T07:05:38.0765150Z         tensor([[[0, 0, 1, 1],
2025-07-17T07:05:38.0765300Z                  [0, 0, 1, 1],
2025-07-17T07:05:38.0765450Z                  [1, 1, 1, 1]],
2025-07-17T07:05:38.0765600Z                 [[1, 1, 0, 0],
2025-07-17T07:05:38.0765750Z                  [1, 1, 0, 0],
2025-07-17T07:05:38.0765900Z                  [0, 0, 1, 1]]])
2025-07-17T07:05:38.0766000Z 
2025-07-17T07:05:38.0766140Z         >>> # Notice which sub-tensors from `a` match with the sub-tensors from
2025-07-17T07:05:38.0766390Z         >>> # `a_unique_dim0`:
2025-07-17T07:05:38.0766570Z         >>> (a_unique_dim0[0, :, :] == a[1, :, :]).all()
2025-07-17T07:05:38.0766750Z         tensor(True)
2025-07-17T07:05:38.0766910Z         >>> (a_unique_dim0[1, :, :] == a[0, :, :]).all()
2025-07-17T07:05:38.0767100Z         tensor(True)
2025-07-17T07:05:38.0767180Z 
2025-07-17T07:05:38.0767330Z         >>> # For `torch.unique(a, dim=1)`, each of the tensors `a[:, idx, :]` are
2025-07-17T07:05:38.0767640Z         >>> # compared. `a[:, 0, :]` and `a[:, 1, :]` match each other, so one of
2025-07-17T07:05:38.0767880Z         >>> # them will be removed.
2025-07-17T07:05:38.0768080Z         >>> (a[:, 0, :] == a[:, 1, :]).all()
2025-07-17T07:05:38.0768250Z         tensor(True)
2025-07-17T07:05:38.0768400Z         >>> torch.unique(a, dim=1)
2025-07-17T07:05:38.0768560Z         tensor([[[0, 0, 1, 1],
2025-07-17T07:05:38.0768720Z                  [1, 1, 0, 0]],
2025-07-17T07:05:38.0768870Z                 [[1, 1, 1, 1],
2025-07-17T07:05:38.0769030Z                  [0, 0, 1, 1]],
2025-07-17T07:05:38.0769180Z                 [[0, 0, 1, 1],
2025-07-17T07:05:38.0769330Z                  [1, 1, 0, 0]]])
2025-07-17T07:05:38.0769440Z 
2025-07-17T07:05:38.0769570Z         >>> # For `torch.unique(a, dim=2)`, the tensors `a[:, :, idx]` are compared.
2025-07-17T07:05:38.0769920Z         >>> # `a[:, :, 0]` and `a[:, :, 1]` match each other. Also, `a[:, :, 2]` and
2025-07-17T07:05:38.0770250Z         >>> # `a[:, :, 3]` match each other as well. So in this case, two of the
2025-07-17T07:05:38.0770490Z         >>> # sub-tensors will be removed.
2025-07-17T07:05:38.0770690Z         >>> (a[:, :, 0] == a[:, :, 1]).all()
2025-07-17T07:05:38.0770860Z         tensor(True)
2025-07-17T07:05:38.0771000Z         >>> (a[:, :, 2] == a[:, :, 3]).all()
2025-07-17T07:05:38.0771170Z         tensor(True)
2025-07-17T07:05:38.0771320Z         >>> torch.unique(a, dim=2)
2025-07-17T07:05:38.0771490Z         tensor([[[0, 1],
2025-07-17T07:05:38.0771620Z                  [0, 1],
2025-07-17T07:05:38.0771760Z                  [1, 0]],
2025-07-17T07:05:38.0771900Z                 [[1, 0],
2025-07-17T07:05:38.0772040Z                  [1, 0],
2025-07-17T07:05:38.0772180Z                  [1, 1]],
2025-07-17T07:05:38.0772310Z                 [[0, 1],
2025-07-17T07:05:38.0772450Z                  [0, 1],
2025-07-17T07:05:38.0772590Z                  [1, 0]]])
2025-07-17T07:05:38.0772730Z     
2025-07-17T07:05:38.0772940Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.1101850Z 
2025-07-17T07:05:38.1102460Z msg = Cannot scrape callname=load in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/serialization.py line=1285.
2025-07-17T07:05:38.1103110Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.1103560Z load(f, map_location=None, pickle_module=pickle, *, weights_only=True, mmap=None, **pickle_load_args)
2025-07-17T07:05:38.1103860Z 
2025-07-17T07:05:38.1103980Z     Loads an object saved with :func:`torch.save` from a file.
2025-07-17T07:05:38.1104170Z 
2025-07-17T07:05:38.1104330Z     :func:`torch.load` uses Python's unpickling facilities but treats storages,
2025-07-17T07:05:38.1104710Z     which underlie tensors, specially. They are first deserialized on the
2025-07-17T07:05:38.1105070Z     CPU and are then moved to the device they were saved from. If this fails
2025-07-17T07:05:38.1105430Z     (e.g. because the run time system doesn't have certain devices), an exception
2025-07-17T07:05:38.1105800Z     is raised. However, storages can be dynamically remapped to an alternative
2025-07-17T07:05:38.1106130Z     set of devices using the :attr:`map_location` argument.
2025-07-17T07:05:38.1106300Z 
2025-07-17T07:05:38.1106460Z     If :attr:`map_location` is a callable, it will be called once for each serialized
2025-07-17T07:05:38.1106830Z     storage with two arguments: storage and location. The storage argument
2025-07-17T07:05:38.1107190Z     will be the initial deserialization of the storage, residing on the CPU.
2025-07-17T07:05:38.1107540Z     Each serialized storage has a location tag associated with it which
2025-07-17T07:05:38.1107880Z     identifies the device it was saved from, and this tag is the second
2025-07-17T07:05:38.1108270Z     argument passed to :attr:`map_location`. The builtin location tags are ``'cpu'``
2025-07-17T07:05:38.1108820Z     for CPU tensors and ``'cuda:device_id'`` (e.g. ``'cuda:2'``) for CUDA tensors.
2025-07-17T07:05:38.1109170Z     :attr:`map_location` should return either ``None`` or a storage. If
2025-07-17T07:05:38.1109570Z     :attr:`map_location` returns a storage, it will be used as the final deserialized
2025-07-17T07:05:38.1109930Z     object, already moved to the right device. Otherwise, :func:`torch.load` will
2025-07-17T07:05:38.1110300Z     fall back to the default behavior, as if :attr:`map_location` wasn't specified.
2025-07-17T07:05:38.1110510Z 
2025-07-17T07:05:38.1110650Z     If :attr:`map_location` is a :class:`torch.device` object or a string containing
2025-07-17T07:05:38.1111000Z     a device tag, it indicates the location where all tensors should be loaded.
2025-07-17T07:05:38.1111210Z 
2025-07-17T07:05:38.1111360Z     Otherwise, if :attr:`map_location` is a dict, it will be used to remap location tags
2025-07-17T07:05:38.1111920Z     appearing in the file (keys), to ones that specify where to put the
2025-07-17T07:05:38.1112240Z     storages (values).
2025-07-17T07:05:38.1112340Z 
2025-07-17T07:05:38.1112480Z     User extensions can register their own location tags and tagging and
2025-07-17T07:05:38.1112830Z     deserialization methods using :func:`torch.serialization.register_package`.
2025-07-17T07:05:38.1113070Z 
2025-07-17T07:05:38.1113210Z     See :ref:`layout-control` for more advanced tools to manipulate a checkpoint.
2025-07-17T07:05:38.1113430Z 
2025-07-17T07:05:38.1113470Z     Args:
2025-07-17T07:05:38.1113730Z         f: a file-like object (has to implement :meth:`read`, :meth:`readline`, :meth:`tell`, and :meth:`seek`),
2025-07-17T07:05:38.1114100Z             or a string or os.PathLike object containing a file name
2025-07-17T07:05:38.1114470Z         map_location: a function, :class:`torch.device`, string or a dict specifying how to remap storage
2025-07-17T07:05:38.1114780Z             locations
2025-07-17T07:05:38.1115020Z         pickle_module: module used for unpickling metadata and objects (has to
2025-07-17T07:05:38.1115330Z             match the :attr:`pickle_module` used to serialize file)
2025-07-17T07:05:38.1115630Z         weights_only: Indicates whether unpickler should be restricted to
2025-07-17T07:05:38.1115930Z             loading only tensors, primitive types, dictionaries
2025-07-17T07:05:38.1116230Z             and any types added via :func:`torch.serialization.add_safe_globals`.
2025-07-17T07:05:38.1116540Z             See :ref:`weights-only` for more details.
2025-07-17T07:05:38.1116880Z         mmap: Indicates whether the file should be mapped rather than loading all the storages into memory.
2025-07-17T07:05:38.1117350Z             Typically, tensor storages in the file will first be moved from disk to CPU memory, after which they
2025-07-17T07:05:38.1117820Z             are moved to the location that they were tagged with when saving, or specified by ``map_location``. This
2025-07-17T07:05:38.1118320Z             second step is a no-op if the final location is CPU. When the ``mmap`` flag is set, instead of copying the
2025-07-17T07:05:38.1118780Z             tensor storages from disk to CPU memory in the first step, ``f`` is mapped, which means tensor storages
2025-07-17T07:05:38.1119130Z             will be lazily loaded when their data is accessed.
2025-07-17T07:05:38.1119440Z         pickle_load_args: (Python 3 only) optional keyword arguments passed over to
2025-07-17T07:05:38.1119790Z             :func:`pickle_module.load` and :func:`pickle_module.Unpickler`, e.g.,
2025-07-17T07:05:38.1120050Z             :attr:`errors=...`.
2025-07-17T07:05:38.1120160Z 
2025-07-17T07:05:38.1120230Z     .. warning::
2025-07-17T07:05:38.1120440Z         :func:`torch.load()` unless `weights_only` parameter is set to `True`,
2025-07-17T07:05:38.1120760Z         uses ``pickle`` module implicitly, which is known to be insecure.
2025-07-17T07:05:38.1121110Z         It is possible to construct malicious pickle data which will execute arbitrary code
2025-07-17T07:05:38.1121540Z         during unpickling. Never load data that could have come from an untrusted
2025-07-17T07:05:38.1121990Z         source in an unsafe mode, or that could have been tampered with. **Only load data you trust**.
2025-07-17T07:05:38.1122270Z 
2025-07-17T07:05:38.1122310Z     .. note::
2025-07-17T07:05:38.1122560Z         When you call :func:`torch.load()` on a file which contains GPU tensors, those tensors
2025-07-17T07:05:38.1122940Z         will be loaded to GPU by default. You can call ``torch.load(.., map_location='cpu')``
2025-07-17T07:05:38.1123320Z         and then :meth:`load_state_dict` to avoid GPU RAM surge when loading a model checkpoint.
2025-07-17T07:05:38.1123560Z 
2025-07-17T07:05:38.1123600Z     .. note::
2025-07-17T07:05:38.1123830Z         By default, we decode byte strings as ``utf-8``.  This is to avoid a common error
2025-07-17T07:05:38.1124240Z         case ``UnicodeDecodeError: 'ascii' codec can't decode byte 0x...``
2025-07-17T07:05:38.1124620Z         when loading files saved by Python 2 in Python 3.  If this default
2025-07-17T07:05:38.1124970Z         is incorrect, you may use an extra :attr:`encoding` keyword argument to specify how
2025-07-17T07:05:38.1125370Z         these objects should be loaded, e.g., :attr:`encoding='latin1'` decodes them
2025-07-17T07:05:38.1125820Z         to strings using ``latin1`` encoding, and :attr:`encoding='bytes'` keeps them
2025-07-17T07:05:38.1126180Z         as byte arrays which can be decoded later with ``byte_array.decode(...)``.
2025-07-17T07:05:38.1134940Z 
2025-07-17T07:05:38.1135000Z     Example:
2025-07-17T07:05:38.1135170Z         >>> # xdoctest: +SKIP("undefined filepaths")
2025-07-17T07:05:38.1135420Z         >>> torch.load("tensors.pt", weights_only=True)
2025-07-17T07:05:38.1135640Z         # Load all tensors onto the CPU
2025-07-17T07:05:38.1135820Z         >>> torch.load(
2025-07-17T07:05:38.1135970Z         ...     "tensors.pt",
2025-07-17T07:05:38.1136150Z         ...     map_location=torch.device("cpu"),
2025-07-17T07:05:38.1136350Z         ...     weights_only=True,
2025-07-17T07:05:38.1136510Z         ... )
2025-07-17T07:05:38.1136670Z         # Load all tensors onto the CPU, using a function
2025-07-17T07:05:38.1136870Z         >>> torch.load(
2025-07-17T07:05:38.1137020Z         ...     "tensors.pt",
2025-07-17T07:05:38.1137200Z         ...     map_location=lambda storage, loc: storage,
2025-07-17T07:05:38.1137400Z         ...     weights_only=True,
2025-07-17T07:05:38.1137560Z         ... )
2025-07-17T07:05:38.1137690Z         # Load all tensors onto GPU 1
2025-07-17T07:05:38.1137860Z         >>> torch.load(
2025-07-17T07:05:38.1138000Z         ...     "tensors.pt",
2025-07-17T07:05:38.1138200Z         ...     map_location=lambda storage, loc: storage.cuda(1),
2025-07-17T07:05:38.1138420Z         ...     weights_only=True,
2025-07-17T07:05:38.1138600Z         ... )  # type: ignore[attr-defined]
2025-07-17T07:05:38.1138800Z         # Map tensors from GPU 1 to GPU 0
2025-07-17T07:05:38.1138980Z         >>> torch.load(
2025-07-17T07:05:38.1139120Z         ...     "tensors.pt",
2025-07-17T07:05:38.1139300Z         ...     map_location={"cuda:1": "cuda:0"},
2025-07-17T07:05:38.1139510Z         ...     weights_only=True,
2025-07-17T07:05:38.1139670Z         ... )
2025-07-17T07:05:38.1139800Z         # Load tensor from io.BytesIO object
2025-07-17T07:05:38.1140090Z         # Loading from a buffer setting weights_only=False, warning this can be unsafe
2025-07-17T07:05:38.1140380Z         >>> with open("tensor.pt", "rb") as f:
2025-07-17T07:05:38.1140580Z         ...     buffer = io.BytesIO(f.read())
2025-07-17T07:05:38.1140780Z         >>> torch.load(buffer, weights_only=False)
2025-07-17T07:05:38.1141010Z         # Load a module with 'ascii' encoding for unpickling
2025-07-17T07:05:38.1141310Z         # Loading from a module setting weights_only=False, warning this can be unsafe
2025-07-17T07:05:38.1141650Z         >>> torch.load("module.pt", encoding="ascii", weights_only=False)
2025-07-17T07:05:38.1141880Z     
2025-07-17T07:05:38.1142190Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.1142430Z 
2025-07-17T07:05:38.1142810Z msg = Cannot scrape callname=Future.then in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/futures/__init__.py line=101.
2025-07-17T07:05:38.1143420Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.1143650Z 
2025-07-17T07:05:38.1143790Z Append the given callback function to this ``Future``, which will be run
2025-07-17T07:05:38.1144110Z when the ``Future`` is completed.  Multiple callbacks can be added to
2025-07-17T07:05:38.1144430Z the same ``Future``, but the order in which they will be executed cannot
2025-07-17T07:05:38.1144730Z be guaranteed (to enforce a certain order consider chaining:
2025-07-17T07:05:38.1145030Z ``fut.then(cb1).then(cb2)``). The callback must take one argument, which
2025-07-17T07:05:38.1145460Z is the reference to this ``Future``. The callback function can use the
2025-07-17T07:05:38.1145860Z :meth:`value` method to get the value. Note that if this ``Future`` is
2025-07-17T07:05:38.1146180Z already completed, the given callback will be run immediately inline.
2025-07-17T07:05:38.1146380Z 
2025-07-17T07:05:38.1146500Z If the ``Future``'s value contains tensors that reside on GPUs, the
2025-07-17T07:05:38.1146810Z callback might be invoked while the async kernels that are populating
2025-07-17T07:05:38.1147140Z those tensors haven't yet finished executing on the device. However, the
2025-07-17T07:05:38.1147460Z callback will be invoked with some dedicated streams set as current
2025-07-17T07:05:38.1147780Z (fetched from a global pool) which will be synchronized with those
2025-07-17T07:05:38.1148110Z kernels. Hence any operation performed by the callback on these tensors
2025-07-17T07:05:38.1148430Z will be scheduled on the device after the kernels complete. In other
2025-07-17T07:05:38.1148750Z words, as long as the callback doesn't switch streams, it can safely
2025-07-17T07:05:38.1149070Z manipulate the result without any additional synchronization. This is
2025-07-17T07:05:38.1149370Z similar to the non-blocking behavior of :meth:`wait`.
2025-07-17T07:05:38.1149530Z 
2025-07-17T07:05:38.1149670Z Similarly, if the callback returns a value that contains tensors that
2025-07-17T07:05:38.1149980Z reside on a GPU, it can do so even if the kernels that are producing
2025-07-17T07:05:38.1150290Z these tensors are still running on the device, as long as the callback
2025-07-17T07:05:38.1150600Z didn't change streams during its execution. If one wants to change
2025-07-17T07:05:38.1150930Z streams, one must be careful to re-synchronize them with the original
2025-07-17T07:05:38.1151250Z streams, that is, those that were current when the callback was invoked.
2025-07-17T07:05:38.1151450Z 
2025-07-17T07:05:38.1151490Z Args:
2025-07-17T07:05:38.1151690Z     callback(``Callable``): a ``Callable`` that takes this ``Future`` as
2025-07-17T07:05:38.1151940Z                             the only argument.
2025-07-17T07:05:38.1152070Z 
2025-07-17T07:05:38.1152120Z Returns:
2025-07-17T07:05:38.1152280Z     A new ``Future`` object that holds the return value of the
2025-07-17T07:05:38.1152560Z     ``callback`` and will be marked as completed when the given
2025-07-17T07:05:38.1152790Z     ``callback`` finishes.
2025-07-17T07:05:38.1152890Z 
2025-07-17T07:05:38.1153000Z .. note:: Note that if the callback function throws, either
2025-07-17T07:05:38.1153290Z     through the original future being completed with an exception and
2025-07-17T07:05:38.1153600Z     calling ``fut.wait()``, or through other code in the callback, the
2025-07-17T07:05:38.1153910Z     future returned by ``then`` will be marked appropriately with the
2025-07-17T07:05:38.1154210Z     encountered error. However, if this callback later completes
2025-07-17T07:05:38.1154530Z     additional futures, those futures are not marked as completed with
2025-07-17T07:05:38.1154870Z     an error and the user is responsible for handling completion/waiting
2025-07-17T07:05:38.1155130Z     on those futures independently.
2025-07-17T07:05:38.1155250Z 
2025-07-17T07:05:38.1155300Z Example::
2025-07-17T07:05:38.1155370Z 
2025-07-17T07:05:38.1155490Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES)
2025-07-17T07:05:38.1155700Z     >>> def callback(fut):
2025-07-17T07:05:38.1155880Z     ...     print(f"RPC return value is {fut.wait()}.")
2025-07-17T07:05:38.1156090Z     >>> fut = torch.futures.Future()
2025-07-17T07:05:38.1156320Z     >>> # The inserted callback will print the return value when
2025-07-17T07:05:38.1156550Z     >>> # receiving the response from "worker1"
2025-07-17T07:05:38.1156750Z     >>> cb_fut = fut.then(callback)
2025-07-17T07:05:38.1156930Z     >>> chain_cb_fut = cb_fut.then(
2025-07-17T07:05:38.1157140Z     ...     lambda x : print(f"Chained cb done. {x.wait()}")
2025-07-17T07:05:38.1157340Z     ... )
2025-07-17T07:05:38.1157520Z     >>> fut.set_result(5)
2025-07-17T07:05:38.1157730Z     RPC return value is 5.
2025-07-17T07:05:38.1157890Z     Chained cb done. None
2025-07-17T07:05:38.1157990Z 
2025-07-17T07:05:38.1158140Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.2396480Z 
2025-07-17T07:05:38.2396950Z msg = Cannot scrape callname=Future.set_result in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/futures/__init__.py line=211.
2025-07-17T07:05:38.2397620Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.2397860Z 
2025-07-17T07:05:38.2398000Z Set the result for this ``Future``, which will mark this ``Future`` as
2025-07-17T07:05:38.2398340Z completed and trigger all attached callbacks. Note that a ``Future``
2025-07-17T07:05:38.2398610Z cannot be marked completed twice.
2025-07-17T07:05:38.2398740Z 
2025-07-17T07:05:38.2398890Z If the result contains tensors that reside on GPUs, this method can be
2025-07-17T07:05:38.2399230Z called even if the asynchronous kernels that are populating those
2025-07-17T07:05:38.2399570Z tensors haven't yet completed running on the device, provided that the
2025-07-17T07:05:38.2399910Z streams on which those kernels were enqueued are set as the current ones
2025-07-17T07:05:38.2400260Z when this method is called. Put simply, it's safe to call this method
2025-07-17T07:05:38.2400600Z immediately after launching those kernels, without any additional
2025-07-17T07:05:38.2400940Z synchronization, as long as one doesn't change streams in between. This
2025-07-17T07:05:38.2401290Z method will record events on all the relevant current streams and will
2025-07-17T07:05:38.2401620Z use them to ensure proper scheduling for all the consumers of this
2025-07-17T07:05:38.2401860Z ``Future``.
2025-07-17T07:05:38.2401940Z 
2025-07-17T07:05:38.2401980Z Args:
2025-07-17T07:05:38.2402150Z     result (object): the result object of this ``Future``.
2025-07-17T07:05:38.2402330Z 
2025-07-17T07:05:38.2402400Z Example::
2025-07-17T07:05:38.2402470Z 
2025-07-17T07:05:38.2402570Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES)
2025-07-17T07:05:38.2402780Z     >>> import threading
2025-07-17T07:05:38.2402980Z     >>> import time
2025-07-17T07:05:38.2403140Z     >>> def slow_set_future(fut, value):
2025-07-17T07:05:38.2403330Z     ...     time.sleep(0.5)
2025-07-17T07:05:38.2403500Z     ...     fut.set_result(value)
2025-07-17T07:05:38.2403690Z     >>> fut = torch.futures.Future()
2025-07-17T07:05:38.2403870Z     >>> t = threading.Thread(
2025-07-17T07:05:38.2404040Z     ...     target=slow_set_future,
2025-07-17T07:05:38.2404230Z     ...     args=(fut, torch.ones(2) * 3)
2025-07-17T07:05:38.2404410Z     ... )
2025-07-17T07:05:38.2404530Z     >>> t.start()
2025-07-17T07:05:38.2404670Z     >>> print(fut.wait())
2025-07-17T07:05:38.2404820Z     tensor([3., 3.])
2025-07-17T07:05:38.2404950Z     >>> t.join()
2025-07-17T07:05:38.2405040Z 
2025-07-17T07:05:38.2405200Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.2405680Z 
2025-07-17T07:05:38.2406070Z msg = Cannot scrape callname=compile_shader in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/mps/__init__.py line=145.
2025-07-17T07:05:38.2406750Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.2407110Z Compiles compute shader from source and allows one to invoke kernels
2025-07-17T07:05:38.2407410Z     defined there from the comfort of Python runtime
2025-07-17T07:05:38.2407640Z     Example::
2025-07-17T07:05:38.2407720Z 
2025-07-17T07:05:38.2407810Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_MPS)
2025-07-17T07:05:38.2408030Z         >>> lib = torch.mps.compile_shader(
2025-07-17T07:05:38.2408430Z         ... "kernel void full(device float* out, constant float& val, uint idx [[thread_position_in_grid]]) { out[idx] = val; }"
2025-07-17T07:05:38.2408780Z         ...  )
2025-07-17T07:05:38.2409120Z         >>> x = torch.zeros(16, device="mps")
2025-07-17T07:05:38.2409410Z         >>> lib.full(x, 3.14)
2025-07-17T07:05:38.2409570Z     
2025-07-17T07:05:38.2409790Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.2410020Z 
2025-07-17T07:05:38.2410480Z msg = Cannot scrape callname=compute_required_storage_length in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_prims_common/__init__.py line=1848.
2025-07-17T07:05:38.2411150Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.2411520Z Computes the minimum storage size to hold the given tensor geometry.
2025-07-17T07:05:38.2411730Z 
2025-07-17T07:05:38.2411780Z     Example
2025-07-17T07:05:38.2411890Z     =======
2025-07-17T07:05:38.2411960Z 
2025-07-17T07:05:38.2412100Z     This is the size of a newly allocated tensor's storage, in units of elements
2025-07-17T07:05:38.2412320Z 
2025-07-17T07:05:38.2412380Z     >>> t = torch.empty((10, 20))
2025-07-17T07:05:38.2412660Z     >>> compute_required_storage_length(t.shape, t.stride(), t.storage_offset())
2025-07-17T07:05:38.2412930Z     200
2025-07-17T07:05:38.2413000Z 
2025-07-17T07:05:38.2413060Z     >>> # xdoctest: +SKIP(failing)
2025-07-17T07:05:38.2413270Z     >>> t2 = torch.empty_strided((1, 2, 3), (5, 7, 11))
2025-07-17T07:05:38.2413500Z     >>> size = compute_required_storage_length(
2025-07-17T07:05:38.2413730Z     ...     t2.shape, t2.stride(), t2.storage_offset()
2025-07-17T07:05:38.2413930Z     ... )
2025-07-17T07:05:38.2414050Z     >>> size == t.storage().size()
2025-07-17T07:05:38.2414220Z     True
2025-07-17T07:05:38.2414280Z 
2025-07-17T07:05:38.2414410Z     A valid tensor may have a larger storage size, but never smaller
2025-07-17T07:05:38.2414600Z 
2025-07-17T07:05:38.2414670Z     >>> slice = torch.empty(100)[20:40]
2025-07-17T07:05:38.2414850Z     >>> slice.storage().size()
2025-07-17T07:05:38.2415010Z     100
2025-07-17T07:05:38.2415070Z 
2025-07-17T07:05:38.2415140Z     >>> compute_required_storage_length(
2025-07-17T07:05:38.2415380Z     ...     slice.shape, slice.stride(), slice.storage_offset()
2025-07-17T07:05:38.2415590Z     ... )
2025-07-17T07:05:38.2415700Z     40
2025-07-17T07:05:38.2415760Z 
2025-07-17T07:05:38.2415800Z     
2025-07-17T07:05:38.2416010Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.2416230Z 
2025-07-17T07:05:38.2416580Z msg = Cannot scrape callname=cudart in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/__init__.py line=434.
2025-07-17T07:05:38.2417140Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:38.2417420Z Retrieves the CUDA runtime API module.
2025-07-17T07:05:38.2417550Z 
2025-07-17T07:05:38.2417560Z 
2025-07-17T07:05:38.2417710Z     This function initializes the CUDA runtime environment if it is not already
2025-07-17T07:05:38.2418060Z     initialized and returns the CUDA runtime API module (_cudart). The CUDA
2025-07-17T07:05:38.2418440Z     runtime API module provides access to various CUDA runtime functions.
2025-07-17T07:05:38.2418650Z 
2025-07-17T07:05:38.2418690Z     Args:
2025-07-17T07:05:38.2418800Z         ``None``
2025-07-17T07:05:38.2418930Z 
2025-07-17T07:05:38.2418970Z     Returns:
2025-07-17T07:05:38.2419130Z         module: The CUDA runtime API module (_cudart).
2025-07-17T07:05:38.2419280Z 
2025-07-17T07:05:38.2419330Z     Raises:
2025-07-17T07:05:38.2419530Z         RuntimeError: If CUDA cannot be re-initialized in a forked subprocess.
2025-07-17T07:05:38.2419950Z         AssertionError: If PyTorch is not compiled with CUDA support or if libcudart functions are unavailable.
2025-07-17T07:05:38.2420220Z 
2025-07-17T07:05:38.2420300Z     Example of CUDA operations with profiling:
2025-07-17T07:05:38.2420500Z         >>> import torch
2025-07-17T07:05:38.2420680Z         >>> from torch.cuda import cudart, check_error
2025-07-17T07:05:38.2420930Z         >>> import os
2025-07-17T07:05:38.2421110Z         >>>
2025-07-17T07:05:38.2421250Z         >>> os.environ["CUDA_PROFILE"] = "1"
2025-07-17T07:05:38.2421420Z         >>>
2025-07-17T07:05:38.2421570Z         >>> def perform_cuda_operations_with_streams():
2025-07-17T07:05:38.2421790Z         >>>     stream = torch.cuda.Stream()
2025-07-17T07:05:38.2421990Z         >>>     with torch.cuda.stream(stream):
2025-07-17T07:05:38.2422210Z         >>>         x = torch.randn(100, 100, device='cuda')
2025-07-17T07:05:38.2422430Z         >>>         y = torch.randn(100, 100, device='cuda')
2025-07-17T07:05:38.2422640Z         >>>         z = torch.mul(x, y)
2025-07-17T07:05:38.2422810Z         >>>     return z
2025-07-17T07:05:38.2422950Z         >>>
2025-07-17T07:05:38.2423080Z         >>> torch.cuda.synchronize()
2025-07-17T07:05:38.2423280Z         >>> print("====== Start nsys profiling ======")
2025-07-17T07:05:38.2423510Z         >>> check_error(cudart().cudaProfilerStart())
2025-07-17T07:05:38.2423740Z         >>> with torch.autograd.profiler.emit_nvtx():
2025-07-17T07:05:38.2423990Z         >>>     result = perform_cuda_operations_with_streams()
2025-07-17T07:05:38.2424220Z         >>>     print("CUDA operations completed.")
2025-07-17T07:05:38.2424470Z         >>> check_error(torch.cuda.cudart().cudaProfilerStop())
2025-07-17T07:05:38.2424710Z         >>> print("====== End nsys profiling ======")
2025-07-17T07:05:38.2424860Z 
2025-07-17T07:05:38.2424980Z     To run this example and save the profiling information, execute:
2025-07-17T07:05:38.2425390Z         >>> $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py
2025-07-17T07:05:38.2425670Z 
2025-07-17T07:05:38.2425810Z     This command profiles the CUDA operations in the provided script and saves
2025-07-17T07:05:38.2426140Z     the profiling information to a file named `trace_name.prof`.
2025-07-17T07:05:38.2426470Z     The `--profile-from-start off` option ensures that profiling starts only
2025-07-17T07:05:38.2426770Z     after the `cudaProfilerStart` call in the script.
2025-07-17T07:05:38.2427060Z     The `--csv` and `--print-summary` options format the profiling output as a
2025-07-17T07:05:38.2427340Z     CSV file and print a summary, respectively.
2025-07-17T07:05:38.2427630Z     The `-o` option specifies the output file name, and the `-f` option forces the
2025-07-17T07:05:38.2427940Z     overwrite of the output file if it already exists.
2025-07-17T07:05:38.2428130Z     
2025-07-17T07:05:38.2428570Z Original Error: SyntaxError('invalid syntax', ('<source_block>', 1, 1, '$ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py\n', 1, 2))
2025-07-17T07:05:38.2429010Z 
2025-07-17T07:05:38.2429220Z $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py
2025-07-17T07:05:38.2429540Z ^
2025-07-17T07:05:38.2429990Z msg = Cannot scrape callname=is_available in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/accelerator/__init__.py line=66.
2025-07-17T07:05:38.2430600Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:38.2430980Z Check if the current accelerator is available at runtime: it was build, all the
2025-07-17T07:05:38.2431360Z     required drivers are available and at least one device is visible.
2025-07-17T07:05:38.2431660Z     See :ref:`accelerator<accelerators>` for details.
2025-07-17T07:05:38.2431810Z 
2025-07-17T07:05:38.2431860Z     Returns:
2025-07-17T07:05:38.2432120Z         bool: A boolean indicating if there is an available :ref:`accelerator<accelerators>`.
2025-07-17T07:05:38.2432350Z 
2025-07-17T07:05:38.2432510Z     .. note:: This API delegates to the device-specific version of `is_available`.
2025-07-17T07:05:38.2432880Z         On CUDA, when the environment variable ``PYTORCH_NVML_BASED_CUDA_CHECK=1`` is set,
2025-07-17T07:05:38.2433330Z         this function will NOT poison fork. Otherwise, it will. For more details, see
2025-07-17T07:05:38.2433710Z         :ref:`multiprocessing-poison-fork-note`.
2025-07-17T07:05:38.2433870Z 
2025-07-17T07:05:38.2433920Z     Example::
2025-07-17T07:05:38.2434000Z 
2025-07-17T07:05:38.2434160Z         >>> assert torch.accelerator.is_available() "No available accelerators detected."
2025-07-17T07:05:38.2434430Z     
2025-07-17T07:05:38.2434820Z Original Error: SyntaxError('invalid syntax', ('<source_block>', 1, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 1, 78))
2025-07-17T07:05:38.2435210Z 
2025-07-17T07:05:38.2435360Z assert torch.accelerator.is_available() "No available accelerators detected."
2025-07-17T07:05:38.2441820Z                                         ^
2025-07-17T07:05:38.2442390Z msg = Cannot scrape callname=synchronize in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/accelerator/__init__.py line=212.
2025-07-17T07:05:38.2443010Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:38.2443350Z Wait for all kernels in all streams on the given device to complete.
2025-07-17T07:05:38.2443540Z 
2025-07-17T07:05:38.2443580Z     Args:
2025-07-17T07:05:38.2443840Z         device (:class:`torch.device`, str, int, optional): device for which to synchronize. It must match
2025-07-17T07:05:38.2444230Z             the current :ref:`accelerator<accelerators>` device type. If not given,
2025-07-17T07:05:38.2444560Z             use :func:`torch.accelerator.current_device_index` by default.
2025-07-17T07:05:38.2444760Z 
2025-07-17T07:05:38.2444950Z     .. note:: This function is a no-op if the current :ref:`accelerator<accelerators>` is not initialized.
2025-07-17T07:05:38.2445200Z 
2025-07-17T07:05:38.2445250Z     Example::
2025-07-17T07:05:38.2445320Z 
2025-07-17T07:05:38.2445410Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-07-17T07:05:38.2445720Z         >>> assert torch.accelerator.is_available() "No available accelerators detected."
2025-07-17T07:05:38.2446040Z         >>> start_event = torch.Event(enable_timing=True)
2025-07-17T07:05:38.2446260Z         >>> end_event = torch.Event(enable_timing=True)
2025-07-17T07:05:38.2446470Z         >>> start_event.record()
2025-07-17T07:05:38.2446730Z         >>> tensor = torch.randn(100, device=torch.accelerator.current_accelerator())
2025-07-17T07:05:38.2447000Z         >>> sum = torch.sum(tensor)
2025-07-17T07:05:38.2447170Z         >>> end_event.record()
2025-07-17T07:05:38.2447350Z         >>> torch.accelerator.synchronize()
2025-07-17T07:05:38.2447600Z         >>> elapsed_time_ms = start_event.elapsed_time(end_event)
2025-07-17T07:05:38.2447810Z     
2025-07-17T07:05:38.2448190Z Original Error: SyntaxError('invalid syntax', ('<source_block>', 2, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 2, 78))
2025-07-17T07:05:38.2448580Z 
2025-07-17T07:05:38.2448730Z assert torch.accelerator.is_available() "No available accelerators detected."
2025-07-17T07:05:38.3437130Z                                         ^
2025-07-17T07:05:38.3437870Z msg = Cannot scrape callname=sum in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/sparse/__init__.py line=202.
2025-07-17T07:05:38.3438620Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.3438950Z Return the sum of each row of the given sparse tensor.
2025-07-17T07:05:38.3439120Z 
2025-07-17T07:05:38.3439260Z     Returns the sum of each row of the sparse tensor :attr:`input` in the given
2025-07-17T07:05:38.3439600Z     dimensions :attr:`dim`. If :attr:`dim` is a list of dimensions,
2025-07-17T07:05:38.3439920Z     reduce over all of them. When sum over all ``sparse_dim``, this method
2025-07-17T07:05:38.3440220Z     returns a dense tensor instead of a sparse tensor.
2025-07-17T07:05:38.3440380Z 
2025-07-17T07:05:38.3440740Z     All summed :attr:`dim` are squeezed (see :func:`torch.squeeze`), resulting an output
2025-07-17T07:05:38.3441190Z     tensor having :attr:`dim` fewer dimensions than :attr:`input`.
2025-07-17T07:05:38.3441380Z 
2025-07-17T07:05:38.3441520Z     During backward, only gradients at ``nnz`` locations of :attr:`input`
2025-07-17T07:05:38.3441880Z     will propagate back. Note that the gradients of :attr:`input` is coalesced.
2025-07-17T07:05:38.3442110Z 
2025-07-17T07:05:38.3442150Z     Args:
2025-07-17T07:05:38.3442300Z         input (Tensor): the input sparse tensor
2025-07-17T07:05:38.3442620Z         dim (int or tuple of ints): a dimension or a list of dimensions to reduce. Default: reduce
2025-07-17T07:05:38.3442920Z             over all dims.
2025-07-17T07:05:38.3443180Z         dtype (:class:`torch.dtype`, optional): the desired data type of returned Tensor.
2025-07-17T07:05:38.3443480Z             Default: dtype of :attr:`input`.
2025-07-17T07:05:38.3443620Z 
2025-07-17T07:05:38.3443690Z     Example::
2025-07-17T07:05:38.3443770Z 
2025-07-17T07:05:38.3443810Z         >>> nnz = 3
2025-07-17T07:05:38.3443960Z         >>> dims = [5, 5, 2, 3]
2025-07-17T07:05:38.3444170Z         >>> I = torch.cat([torch.randint(0, dims[0], size=(nnz,)),
2025-07-17T07:05:38.3444460Z                            torch.randint(0, dims[1], size=(nnz,))], 0).reshape(2, nnz)
2025-07-17T07:05:38.3444730Z         >>> V = torch.randn(nnz, dims[2], dims[3])
2025-07-17T07:05:38.3444940Z         >>> size = torch.Size(dims)
2025-07-17T07:05:38.3445150Z         >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-07-17T07:05:38.3445390Z         >>> S = torch.sparse_coo_tensor(I, V, size)
2025-07-17T07:05:38.3445580Z         >>> S
2025-07-17T07:05:38.3445720Z         tensor(indices=tensor([[2, 0, 3],
2025-07-17T07:05:38.3445910Z                                [2, 4, 1]]),
2025-07-17T07:05:38.3446130Z                values=tensor([[[-0.6438, -1.6467,  1.4004],
2025-07-17T07:05:38.3446350Z                                [ 0.3411,  0.0918, -0.2312]],
2025-07-17T07:05:38.3446490Z 
2025-07-17T07:05:38.3446560Z                               [[ 0.5348,  0.0634, -2.0494],
2025-07-17T07:05:38.3446770Z                                [-0.7125, -1.0646,  2.1844]],
2025-07-17T07:05:38.3446910Z 
2025-07-17T07:05:38.3446980Z                               [[ 0.1276,  0.1874, -0.6334],
2025-07-17T07:05:38.3447210Z                                [-1.9682, -0.5340,  0.7483]]]),
2025-07-17T07:05:38.3447440Z                size=(5, 5, 2, 3), nnz=3, layout=torch.sparse_coo)
2025-07-17T07:05:38.3447590Z 
2025-07-17T07:05:38.3447710Z         # when sum over only part of sparse_dims, return a sparse tensor
2025-07-17T07:05:38.3447960Z         >>> torch.sparse.sum(S, [1, 3])
2025-07-17T07:05:38.3448150Z         tensor(indices=tensor([[0, 2, 3]]),
2025-07-17T07:05:38.3448350Z                values=tensor([[-1.4512,  0.4073],
2025-07-17T07:05:38.3448540Z                               [-0.8901,  0.2017],
2025-07-17T07:05:38.3448730Z                               [-0.3183, -1.7539]]),
2025-07-17T07:05:38.3448940Z                size=(5, 2), nnz=3, layout=torch.sparse_coo)
2025-07-17T07:05:38.3449100Z 
2025-07-17T07:05:38.3449240Z         # when sum over all sparse dim, return a dense tensor
2025-07-17T07:05:38.3449460Z         # with summed dims squeezed
2025-07-17T07:05:38.3449650Z         >>> torch.sparse.sum(S, [0, 1, 3])
2025-07-17T07:05:38.3449860Z         tensor([-2.6596, -1.1450])
2025-07-17T07:05:38.3450020Z     
2025-07-17T07:05:38.3450230Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.3450450Z 
2025-07-17T07:05:38.3450810Z msg = Cannot scrape callname=vmap in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/apis.py line=39.
2025-07-17T07:05:38.3451470Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.3451700Z 
2025-07-17T07:05:38.3451840Z vmap is the vectorizing map; ``vmap(func)`` returns a new function that
2025-07-17T07:05:38.3452220Z maps ``func`` over some dimension of the inputs. Semantically, vmap
2025-07-17T07:05:38.3452600Z pushes the map into PyTorch operations called by ``func``, effectively
2025-07-17T07:05:38.3452860Z vectorizing those operations.
2025-07-17T07:05:38.3452980Z 
2025-07-17T07:05:38.3453110Z vmap is useful for handling batch dimensions: one can write a function
2025-07-17T07:05:38.3453430Z ``func`` that runs on examples and then lift it to a function that can
2025-07-17T07:05:38.3453750Z take batches of examples with ``vmap(func)``. vmap can also be used to
2025-07-17T07:05:38.3454040Z compute batched gradients when composed with autograd.
2025-07-17T07:05:38.3454210Z 
2025-07-17T07:05:38.3454250Z .. note::
2025-07-17T07:05:38.3454430Z     :func:`torch.vmap` is aliased to :func:`torch.func.vmap` for
2025-07-17T07:05:38.3454690Z     convenience. Use whichever one you'd like.
2025-07-17T07:05:38.3454830Z 
2025-07-17T07:05:38.3454870Z Args:
2025-07-17T07:05:38.3455070Z     func (function): A Python function that takes one or more arguments.
2025-07-17T07:05:38.3455320Z         Must return one or more Tensors.
2025-07-17T07:05:38.3455580Z     in_dims (int or nested structure): Specifies which dimension of the
2025-07-17T07:05:38.3455870Z         inputs should be mapped over. ``in_dims`` should have a
2025-07-17T07:05:38.3456160Z         structure like the inputs. If the ``in_dim`` for a particular
2025-07-17T07:05:38.3456460Z         input is None, then that indicates there is no map dimension.
2025-07-17T07:05:38.3456690Z         Default: 0.
2025-07-17T07:05:38.3456890Z     out_dims (int or Tuple[int]): Specifies where the mapped dimension
2025-07-17T07:05:38.3457190Z         should appear in the outputs. If ``out_dims`` is a Tuple, then
2025-07-17T07:05:38.3457460Z         it should have one element per output. Default: 0.
2025-07-17T07:05:38.3457730Z     randomness (str): Specifies whether the randomness in this
2025-07-17T07:05:38.3458040Z         vmap should be the same or different across batches. If 'different',
2025-07-17T07:05:38.3458350Z         the randomness for each batch will be different. If 'same', the
2025-07-17T07:05:38.3458670Z         randomness will be the same across batches. If 'error', any calls to
2025-07-17T07:05:38.3458990Z         random functions will error. Default: 'error'. WARNING: this flag
2025-07-17T07:05:38.3459300Z         only applies to random PyTorch operations and does not apply to
2025-07-17T07:05:38.3459610Z         Python's random module or numpy randomness.
2025-07-17T07:05:38.3459890Z     chunk_size (None or int): If None (default), apply a single vmap over inputs.
2025-07-17T07:05:38.3460230Z         If not None, then compute the vmap :attr:`chunk_size` samples at a time.
2025-07-17T07:05:38.3460580Z         Note that :attr:`chunk_size=1` is equivalent to computing the vmap with a for-loop.
2025-07-17T07:05:38.3460960Z         If you run into memory issues computing the vmap, please try a non-None chunk_size.
2025-07-17T07:05:38.3461190Z 
2025-07-17T07:05:38.3461240Z Returns:
2025-07-17T07:05:38.3461420Z     Returns a new "batched" function. It takes the same inputs as
2025-07-17T07:05:38.3461740Z     ``func``, except each input has an extra dimension at the index
2025-07-17T07:05:38.3462030Z     specified by ``in_dims``. It takes returns the same outputs as
2025-07-17T07:05:38.3462330Z     ``func``, except each output has an extra dimension at the index
2025-07-17T07:05:38.3462610Z     specified by ``out_dims``.
2025-07-17T07:05:38.3462720Z 
2025-07-17T07:05:38.3462770Z .. warning:
2025-07-17T07:05:38.3462960Z     :func:`vmap` works best with functional-style code. Please do not
2025-07-17T07:05:38.3463260Z     perform any side-effects in ``func``, with the exception of
2025-07-17T07:05:38.3463580Z     in-place PyTorch operations. Examples of side-effects include mutating
2025-07-17T07:05:38.3463920Z     Python data structures and assigning values to variables not captured
2025-07-17T07:05:38.3464160Z     in ``func``.
2025-07-17T07:05:38.3464240Z 
2025-07-17T07:05:38.3464440Z One example of using :func:`vmap` is to compute batched dot products. PyTorch
2025-07-17T07:05:38.3464840Z doesn't provide a batched ``torch.dot`` API; instead of unsuccessfully
2025-07-17T07:05:38.3465170Z rummaging through docs, use :func:`vmap` to construct a new function.
2025-07-17T07:05:38.3465370Z 
2025-07-17T07:05:38.3465460Z     >>> torch.dot  # [D], [D] -> []
2025-07-17T07:05:38.3465710Z     >>> batched_dot = torch.func.vmap(torch.dot)  # [N, D], [N, D] -> [N]
2025-07-17T07:05:38.3465970Z     >>> x, y = torch.randn(2, 5), torch.randn(2, 5)
2025-07-17T07:05:38.3466160Z     >>> batched_dot(x, y)
2025-07-17T07:05:38.3466260Z 
2025-07-17T07:05:38.3466410Z :func:`vmap` can be helpful in hiding batch dimensions, leading to a simpler
2025-07-17T07:05:38.3466670Z model authoring experience.
2025-07-17T07:05:38.3466780Z 
2025-07-17T07:05:38.3466840Z     >>> batch_size, feature_size = 3, 5
2025-07-17T07:05:38.3467070Z     >>> weights = torch.randn(feature_size, requires_grad=True)
2025-07-17T07:05:38.3467290Z     >>>
2025-07-17T07:05:38.3467400Z     >>> def model(feature_vec):
2025-07-17T07:05:38.3467600Z     >>> # Very simple linear model with activation
2025-07-17T07:05:38.3467820Z     >>>     return feature_vec.dot(weights).relu()
2025-07-17T07:05:38.3468000Z     >>>
2025-07-17T07:05:38.3468150Z     >>> examples = torch.randn(batch_size, feature_size)
2025-07-17T07:05:38.3468370Z     >>> result = torch.vmap(model)(examples)
2025-07-17T07:05:38.3468500Z 
2025-07-17T07:05:38.3468660Z :func:`vmap` can also help vectorize computations that were previously difficult
2025-07-17T07:05:38.3469010Z or impossible to batch. One example is higher-order gradient computation.
2025-07-17T07:05:38.3469350Z The PyTorch autograd engine computes vjps (vector-Jacobian products).
2025-07-17T07:05:38.3469700Z Computing a full Jacobian matrix for some function f: R^N -> R^N usually
2025-07-17T07:05:38.3470060Z requires N calls to ``autograd.grad``, one per Jacobian row. Using :func:`vmap`,
2025-07-17T07:05:38.3470450Z we can vectorize the whole computation, computing the Jacobian in a single
2025-07-17T07:05:38.3470720Z call to ``autograd.grad``.
2025-07-17T07:05:38.3470840Z 
2025-07-17T07:05:38.3470880Z     >>> # Setup
2025-07-17T07:05:38.3471010Z     >>> N = 5
2025-07-17T07:05:38.3471140Z     >>> f = lambda x: x**2
2025-07-17T07:05:38.3471310Z     >>> x = torch.randn(N, requires_grad=True)
2025-07-17T07:05:38.3471500Z     >>> y = f(x)
2025-07-17T07:05:38.3471640Z     >>> I_N = torch.eye(N)
2025-07-17T07:05:38.3471780Z     >>>
2025-07-17T07:05:38.3471900Z     >>> # Sequential approach
2025-07-17T07:05:38.3472150Z     >>> jacobian_rows = [torch.autograd.grad(y, x, v, retain_graph=True)[0]
2025-07-17T07:05:38.3472420Z     >>>                  for v in I_N.unbind()]
2025-07-17T07:05:38.3472630Z     >>> jacobian = torch.stack(jacobian_rows)
2025-07-17T07:05:38.3472820Z     >>>
2025-07-17T07:05:38.3472950Z     >>> # vectorized gradient computation
2025-07-17T07:05:38.3473140Z     >>> def get_vjp(v):
2025-07-17T07:05:38.3473310Z     >>>     return torch.autograd.grad(y, x, v)
2025-07-17T07:05:38.3473520Z     >>> jacobian = torch.vmap(get_vjp)(I_N)
2025-07-17T07:05:38.3473660Z 
2025-07-17T07:05:38.3473850Z :func:`vmap` can also be nested, producing an output with multiple batched dimensions
2025-07-17T07:05:38.3474090Z 
2025-07-17T07:05:38.3474140Z     >>> torch.dot  # [D], [D] -> []
2025-07-17T07:05:38.3474350Z     >>> batched_dot = torch.vmap(
2025-07-17T07:05:38.3474530Z     ...     torch.vmap(torch.dot)
2025-07-17T07:05:38.3474710Z     ... )  # [N1, N0, D], [N1, N0, D] -> [N1, N0]
2025-07-17T07:05:38.3474930Z     >>> x, y = torch.randn(2, 3, 5), torch.randn(2, 3, 5)
2025-07-17T07:05:38.3475150Z     >>> batched_dot(x, y)  # tensor of size [2, 3]
2025-07-17T07:05:38.3475290Z 
2025-07-17T07:05:38.3475440Z If the inputs are not batched along the first dimension, ``in_dims`` specifies
2025-07-17T07:05:38.3475740Z the dimension that each inputs are batched along as
2025-07-17T07:05:38.3475900Z 
2025-07-17T07:05:38.3475960Z     >>> torch.dot  # [N], [N] -> []
2025-07-17T07:05:38.3476280Z     >>> batched_dot = torch.vmap(torch.dot, in_dims=1)  # [N, D], [N, D] -> [D]
2025-07-17T07:05:38.3476630Z     >>> x, y = torch.randn(2, 5), torch.randn(2, 5)
2025-07-17T07:05:38.3476820Z     >>> batched_dot(
2025-07-17T07:05:38.3476950Z     ...     x, y
2025-07-17T07:05:38.3477150Z     ... )  # output is [5] instead of [2] if batched along the 0th dimension
2025-07-17T07:05:38.3477340Z 
2025-07-17T07:05:38.3477490Z If there are multiple inputs each of which is batched along different dimensions,
2025-07-17T07:05:38.3477840Z ``in_dims`` must be a tuple with the batch dimension for each input as
2025-07-17T07:05:38.3478030Z 
2025-07-17T07:05:38.3478090Z     >>> torch.dot  # [D], [D] -> []
2025-07-17T07:05:38.3478350Z     >>> batched_dot = torch.vmap(torch.dot, in_dims=(0, None))  # [N, D], [D] -> [N]
2025-07-17T07:05:38.3478630Z     >>> x, y = torch.randn(2, 5), torch.randn(5)
2025-07-17T07:05:38.3478820Z     >>> batched_dot(
2025-07-17T07:05:38.3478950Z     ...     x, y
2025-07-17T07:05:38.3479140Z     ... )  # second arg doesn't have a batch dim because in_dim[1] was None
2025-07-17T07:05:38.3479330Z 
2025-07-17T07:05:38.3479470Z If the input is a Python struct, ``in_dims`` must be a tuple containing a struct
2025-07-17T07:05:38.3479740Z matching the shape of the input:
2025-07-17T07:05:38.3479860Z 
2025-07-17T07:05:38.3479940Z     >>> f = lambda dict: torch.dot(dict["x"], dict["y"])
2025-07-17T07:05:38.3480160Z     >>> x, y = torch.randn(2, 5), torch.randn(5)
2025-07-17T07:05:38.3480350Z     >>> input = {"x": x, "y": y}
2025-07-17T07:05:38.3480570Z     >>> batched_dot = torch.vmap(f, in_dims=({"x": 0, "y": None},))
2025-07-17T07:05:38.3480790Z     >>> batched_dot(input)
2025-07-17T07:05:38.3480890Z 
2025-07-17T07:05:38.3481070Z By default, the output is batched along the first dimension. However, it can be batched
2025-07-17T07:05:38.3481390Z along any dimension by using ``out_dims``
2025-07-17T07:05:38.3481530Z 
2025-07-17T07:05:38.3481580Z     >>> f = lambda x: x**2
2025-07-17T07:05:38.3481740Z     >>> x = torch.randn(2, 5)
2025-07-17T07:05:38.3481920Z     >>> batched_pow = torch.vmap(f, out_dims=1)
2025-07-17T07:05:38.3482120Z     >>> batched_pow(x)  # [5, 2]
2025-07-17T07:05:38.3482230Z 
2025-07-17T07:05:38.3482410Z For any function that uses kwargs, the returned function will not batch the kwargs but will
2025-07-17T07:05:38.3482700Z accept kwargs
2025-07-17T07:05:38.3482780Z 
2025-07-17T07:05:38.3482830Z     >>> x = torch.randn([2, 5])
2025-07-17T07:05:38.3482990Z     >>> def fn(x, scale=4.):
2025-07-17T07:05:38.3483150Z     >>>   return x * scale
2025-07-17T07:05:38.3483290Z     >>>
2025-07-17T07:05:38.3483410Z     >>> batched_pow = torch.vmap(fn)
2025-07-17T07:05:38.3483620Z     >>> assert torch.allclose(batched_pow(x), x * 4)
2025-07-17T07:05:38.3483900Z     >>> batched_pow(x, scale=x)  # scale is not batched, output has shape [2, 2, 5]
2025-07-17T07:05:38.3484110Z 
2025-07-17T07:05:38.3484150Z .. note::
2025-07-17T07:05:38.3484350Z     vmap does not provide general autobatching or handle variable-length
2025-07-17T07:05:38.3484620Z     sequences out of the box.
2025-07-17T07:05:38.3484730Z 
2025-07-17T07:05:38.3484890Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.3485190Z 
2025-07-17T07:05:38.3485550Z msg = Cannot scrape callname=grad in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/apis.py line=306.
2025-07-17T07:05:38.3486150Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.3486510Z ``grad`` operator helps computing gradients of ``func`` with respect to the
2025-07-17T07:05:38.3486840Z     input(s) specified by ``argnums``. This operator can be nested to
2025-07-17T07:05:38.3487090Z     compute higher-order gradients.
2025-07-17T07:05:38.3487220Z 
2025-07-17T07:05:38.3487260Z     Args:
2025-07-17T07:05:38.3487460Z         func (Callable): A Python function that takes one or more arguments.
2025-07-17T07:05:38.3487870Z             Must return a single-element Tensor. If specified ``has_aux`` equals ``True``,
2025-07-17T07:05:38.3488320Z             function can return a tuple of single-element Tensor and other auxiliary objects:
2025-07-17T07:05:38.3488590Z             ``(output, aux)``.
2025-07-17T07:05:38.3488970Z         argnums (int or Tuple[int]): Specifies arguments to compute gradients with respect to.
2025-07-17T07:05:38.3489340Z             ``argnums`` can be single integer or tuple of integers. Default: 0.
2025-07-17T07:05:38.3489670Z         has_aux (bool): Flag indicating that ``func`` returns a tensor and other
2025-07-17T07:05:38.3489980Z             auxiliary objects: ``(output, aux)``. Default: False.
2025-07-17T07:05:38.3490160Z 
2025-07-17T07:05:38.3490200Z     Returns:
2025-07-17T07:05:38.3490470Z         Function to compute gradients with respect to its inputs. By default, the output of
2025-07-17T07:05:38.3490860Z         the function is the gradient tensor(s) with respect to the first argument.
2025-07-17T07:05:38.3491260Z         If specified ``has_aux`` equals ``True``, tuple of gradients and output auxiliary objects
2025-07-17T07:05:38.3491650Z         is returned. If ``argnums`` is a tuple of integers, a tuple of output gradients with
2025-07-17T07:05:38.3491970Z         respect to each ``argnums`` value is returned.
2025-07-17T07:05:38.3492120Z 
2025-07-17T07:05:38.3492180Z     Example of using ``grad``:
2025-07-17T07:05:38.3492300Z 
2025-07-17T07:05:38.3492360Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:38.3492530Z         >>> from torch.func import grad
2025-07-17T07:05:38.3492710Z         >>> x = torch.randn([])
2025-07-17T07:05:38.3492900Z         >>> cos_x = grad(lambda x: torch.sin(x))(x)
2025-07-17T07:05:38.3499560Z         >>> assert torch.allclose(cos_x, x.cos())
2025-07-17T07:05:38.3499830Z         >>>
2025-07-17T07:05:38.3499970Z         >>> # Second-order gradients
2025-07-17T07:05:38.3500210Z         >>> neg_sin_x = grad(grad(lambda x: torch.sin(x)))(x)
2025-07-17T07:05:38.3500480Z         >>> assert torch.allclose(neg_sin_x, -x.sin())
2025-07-17T07:05:38.3500640Z 
2025-07-17T07:05:38.3500800Z     When composed with ``vmap``, ``grad`` can be used to compute per-sample-gradients:
2025-07-17T07:05:38.3501040Z 
2025-07-17T07:05:38.3501090Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:38.3501280Z         >>> from torch.func import grad, vmap
2025-07-17T07:05:38.3501490Z         >>> batch_size, feature_size = 3, 5
2025-07-17T07:05:38.3501670Z         >>>
2025-07-17T07:05:38.3501810Z         >>> def model(weights, feature_vec):
2025-07-17T07:05:38.3502030Z         >>> # Very simple linear model with activation
2025-07-17T07:05:38.3502250Z         >>>     assert feature_vec.dim() == 1
2025-07-17T07:05:38.3502520Z         >>>     return feature_vec.dot(weights).relu()
2025-07-17T07:05:38.3502710Z         >>>
2025-07-17T07:05:38.3502860Z         >>> def compute_loss(weights, example, target):
2025-07-17T07:05:38.3503080Z         >>>     y = model(weights, example)
2025-07-17T07:05:38.3503290Z         >>>     return ((y - target) ** 2).mean()  # MSELoss
2025-07-17T07:05:38.3503480Z         >>>
2025-07-17T07:05:38.3503820Z         >>> weights = torch.randn(feature_size, requires_grad=True)
2025-07-17T07:05:38.3504100Z         >>> examples = torch.randn(batch_size, feature_size)
2025-07-17T07:05:38.3504330Z         >>> targets = torch.randn(batch_size)
2025-07-17T07:05:38.3504590Z         >>> inputs = (weights, examples, targets)
2025-07-17T07:05:38.3504880Z         >>> grad_weight_per_example = vmap(grad(compute_loss), in_dims=(None, 0, 0))(
2025-07-17T07:05:38.3505190Z         ...     *inputs
2025-07-17T07:05:38.3505320Z         ... )
2025-07-17T07:05:38.3505400Z 
2025-07-17T07:05:38.3505550Z     Example of using ``grad`` with ``has_aux`` and ``argnums``:
2025-07-17T07:05:38.3505730Z 
2025-07-17T07:05:38.3505790Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:38.3506070Z         >>> from torch.func import grad
2025-07-17T07:05:38.3506250Z         >>> def my_loss_func(y, y_pred):
2025-07-17T07:05:38.3506590Z         >>>    loss_per_sample = (0.5 * y_pred - y) ** 2
2025-07-17T07:05:38.3506880Z         >>>    loss = loss_per_sample.mean()
2025-07-17T07:05:38.3507090Z         >>>    return loss, (y_pred, loss_per_sample)
2025-07-17T07:05:38.3507280Z         >>>
2025-07-17T07:05:38.3507440Z         >>> fn = grad(my_loss_func, argnums=(0, 1), has_aux=True)
2025-07-17T07:05:38.3507680Z         >>> y_true = torch.rand(4)
2025-07-17T07:05:38.3507880Z         >>> y_preds = torch.rand(4, requires_grad=True)
2025-07-17T07:05:38.3508090Z         >>> out = fn(y_true, y_preds)
2025-07-17T07:05:38.3508370Z         >>> # > output is ((grads w.r.t y_true, grads w.r.t y_preds), (y_pred, loss_per_sample))
2025-07-17T07:05:38.3508600Z 
2025-07-17T07:05:38.3508660Z     .. note::
2025-07-17T07:05:38.3508850Z         Using PyTorch ``torch.no_grad`` together with ``grad``.
2025-07-17T07:05:38.3509030Z 
2025-07-17T07:05:38.3509160Z         Case 1: Using ``torch.no_grad`` inside a function:
2025-07-17T07:05:38.3509320Z 
2025-07-17T07:05:38.3509380Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:38.3509640Z             >>> def f(x):
2025-07-17T07:05:38.3509790Z             >>>     with torch.no_grad():
2025-07-17T07:05:38.3509980Z             >>>         c = x ** 2
2025-07-17T07:05:38.3510140Z             >>>     return x - c
2025-07-17T07:05:38.3510250Z 
2025-07-17T07:05:38.3510380Z         In this case, ``grad(f)(x)`` will respect the inner ``torch.no_grad``.
2025-07-17T07:05:38.3510570Z 
2025-07-17T07:05:38.3510680Z         Case 2: Using ``grad`` inside ``torch.no_grad`` context manager:
2025-07-17T07:05:38.3510860Z 
2025-07-17T07:05:38.3510910Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:38.3511080Z             >>> with torch.no_grad():
2025-07-17T07:05:38.3511260Z             >>>     grad(f)(x)
2025-07-17T07:05:38.3511360Z 
2025-07-17T07:05:38.3511500Z         In this case, ``grad`` will respect the inner ``torch.no_grad``, but not the
2025-07-17T07:05:38.3511830Z         outer one. This is because ``grad`` is a "function transform": its result
2025-07-17T07:05:38.3512160Z         should not depend on the result of a context manager outside of ``f``.
2025-07-17T07:05:38.3512360Z 
2025-07-17T07:05:38.3512410Z     
2025-07-17T07:05:38.3512620Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.3512830Z 
2025-07-17T07:05:38.3513240Z msg = Cannot scrape callname=print_assert_equal in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=286.
2025-07-17T07:05:38.3513850Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.3514070Z 
2025-07-17T07:05:38.3514200Z Test if two objects are equal, and print an error message if test fails.
2025-07-17T07:05:38.3514400Z 
2025-07-17T07:05:38.3514480Z The test is performed with ``actual == desired``.
2025-07-17T07:05:38.3514630Z 
2025-07-17T07:05:38.3514680Z Parameters
2025-07-17T07:05:38.3514790Z ----------
2025-07-17T07:05:38.3514910Z test_string : str
2025-07-17T07:05:38.3515060Z     The message supplied to AssertionError.
2025-07-17T07:05:38.3515280Z actual : object
2025-07-17T07:05:38.3515450Z     The object to test for equality against `desired`.
2025-07-17T07:05:38.3515650Z desired : object
2025-07-17T07:05:38.3515790Z     The expected result.
2025-07-17T07:05:38.3515930Z 
2025-07-17T07:05:38.3515980Z Examples
2025-07-17T07:05:38.3516090Z --------
2025-07-17T07:05:38.3516210Z >>> np.testing.print_assert_equal(
2025-07-17T07:05:38.3516400Z ...     "Test XYZ of func xyz", [0, 1], [0, 1]
2025-07-17T07:05:38.3516580Z ... )  # doctest: +SKIP
2025-07-17T07:05:38.3516740Z >>> np.testing.print_assert_equal(
2025-07-17T07:05:38.3516920Z ...     "Test XYZ of func xyz", [0, 1], [0, 2]
2025-07-17T07:05:38.3517100Z ... )  # doctest: +SKIP
2025-07-17T07:05:38.3517260Z Traceback (most recent call last):
2025-07-17T07:05:38.3517420Z ...
2025-07-17T07:05:38.3517550Z AssertionError: Test XYZ of func xyz failed
2025-07-17T07:05:38.3517730Z ACTUAL:
2025-07-17T07:05:38.3517840Z [0, 1]
2025-07-17T07:05:38.3518010Z DESIRED:
2025-07-17T07:05:38.3518170Z [0, 2]
2025-07-17T07:05:38.3518240Z 
2025-07-17T07:05:38.3518240Z 
2025-07-17T07:05:38.3518400Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.3518630Z 
2025-07-17T07:05:38.3519020Z msg = Cannot scrape callname=assert_almost_equal in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=331.
2025-07-17T07:05:38.3519630Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.3519850Z 
2025-07-17T07:05:38.3519970Z Raises an AssertionError if two items are not equal up to desired
2025-07-17T07:05:38.3520210Z precision.
2025-07-17T07:05:38.3520280Z 
2025-07-17T07:05:38.3520380Z .. note:: It is recommended to use one of `assert_allclose`,
2025-07-17T07:05:38.3520660Z           `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
2025-07-17T07:05:38.3520950Z           instead of this function for more consistent floating point
2025-07-17T07:05:38.3521190Z           comparisons.
2025-07-17T07:05:38.3521280Z 
2025-07-17T07:05:38.3521410Z The test verifies that the elements of `actual` and `desired` satisfy.
2025-07-17T07:05:38.3521610Z 
2025-07-17T07:05:38.3521700Z     ``abs(desired-actual) < float64(1.5 * 10**(-decimal))``
2025-07-17T07:05:38.3521870Z 
2025-07-17T07:05:38.3522000Z That is a looser test than originally documented, but agrees with what the
2025-07-17T07:05:38.3522340Z actual implementation in `assert_array_almost_equal` did up to rounding
2025-07-17T07:05:38.3522690Z vagaries. An exception is raised at conflicting values. For ndarrays this
2025-07-17T07:05:38.3522960Z delegates to assert_array_almost_equal
2025-07-17T07:05:38.3523090Z 
2025-07-17T07:05:38.3523140Z Parameters
2025-07-17T07:05:38.3523250Z ----------
2025-07-17T07:05:38.3523360Z actual : array_like
2025-07-17T07:05:38.3523500Z     The object to check.
2025-07-17T07:05:38.3523640Z desired : array_like
2025-07-17T07:05:38.3523780Z     The expected object.
2025-07-17T07:05:38.3523940Z decimal : int, optional
2025-07-17T07:05:38.3524090Z     Desired precision, default is 7.
2025-07-17T07:05:38.3524270Z err_msg : str, optional
2025-07-17T07:05:38.3524450Z     The error message to be printed in case of failure.
2025-07-17T07:05:38.3524660Z verbose : bool, optional
2025-07-17T07:05:38.3524880Z     If True, the conflicting values are appended to the error message.
2025-07-17T07:05:38.3525070Z 
2025-07-17T07:05:38.3525110Z Raises
2025-07-17T07:05:38.3525210Z ------
2025-07-17T07:05:38.3525320Z AssertionError
2025-07-17T07:05:38.3525510Z   If actual and desired are not equal up to specified precision.
2025-07-17T07:05:38.3525690Z 
2025-07-17T07:05:38.3525730Z See Also
2025-07-17T07:05:38.3525840Z --------
2025-07-17T07:05:38.3526040Z assert_allclose: Compare two array_like objects for equality with desired
2025-07-17T07:05:38.3526330Z                  relative and/or absolute precision.
2025-07-17T07:05:38.3526590Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-07-17T07:05:38.3526830Z 
2025-07-17T07:05:38.3526880Z Examples
2025-07-17T07:05:38.3526980Z --------
2025-07-17T07:05:38.3527140Z >>> from torch._numpy.testing import assert_almost_equal
2025-07-17T07:05:38.3527380Z >>> assert_almost_equal(2.3333333333333, 2.33333334)
2025-07-17T07:05:38.3527660Z >>> assert_almost_equal(2.3333333333333, 2.33333334, decimal=10)
2025-07-17T07:05:38.3527890Z Traceback (most recent call last):
2025-07-17T07:05:38.3528050Z     ...
2025-07-17T07:05:38.3528160Z AssertionError:
2025-07-17T07:05:38.3528310Z Arrays are not almost equal to 10 decimals
2025-07-17T07:05:38.3528500Z  ACTUAL: 2.3333333333333
2025-07-17T07:05:38.3528630Z  DESIRED: 2.33333334
2025-07-17T07:05:38.3528720Z 
2025-07-17T07:05:38.3528770Z >>> assert_almost_equal(
2025-07-17T07:05:38.3528990Z ...     np.array([1.0, 2.3333333333333]), np.array([1.0, 2.33333334]), decimal=9
2025-07-17T07:05:38.3529220Z ... )
2025-07-17T07:05:38.3529440Z Traceback (most recent call last):
2025-07-17T07:05:38.3529670Z     ...
2025-07-17T07:05:38.3529780Z AssertionError:
2025-07-17T07:05:38.3529920Z Arrays are not almost equal to 9 decimals
2025-07-17T07:05:38.3530100Z <BLANKLINE>
2025-07-17T07:05:38.3530230Z Mismatched elements: 1 / 2 (50%)
2025-07-17T07:05:38.3530410Z Max absolute difference: 6.666699636781459e-09
2025-07-17T07:05:38.3530630Z Max relative difference: 2.8571569790287484e-09
2025-07-17T07:05:38.3530850Z  x: torch.ndarray([1.0000, 2.3333], dtype=float64)
2025-07-17T07:05:38.3531070Z  y: torch.ndarray([1.0000, 2.3333], dtype=float64)
2025-07-17T07:05:38.3531220Z 
2025-07-17T07:05:38.3531220Z 
2025-07-17T07:05:38.3531370Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.3531580Z 
2025-07-17T07:05:38.3531980Z msg = Cannot scrape callname=assert_approx_equal in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=457.
2025-07-17T07:05:38.3532600Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.3532820Z 
2025-07-17T07:05:38.3532960Z Raises an AssertionError if two items are not equal up to significant
2025-07-17T07:05:38.3533200Z digits.
2025-07-17T07:05:38.3533260Z 
2025-07-17T07:05:38.3533370Z .. note:: It is recommended to use one of `assert_allclose`,
2025-07-17T07:05:38.3533640Z           `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
2025-07-17T07:05:38.3533940Z           instead of this function for more consistent floating point
2025-07-17T07:05:38.3534180Z           comparisons.
2025-07-17T07:05:38.3534270Z 
2025-07-17T07:05:38.3534380Z Given two numbers, check that they are approximately equal.
2025-07-17T07:05:38.3534690Z Approximately equal is defined as the number of significant digits
2025-07-17T07:05:38.3534920Z that agree.
2025-07-17T07:05:38.3534990Z 
2025-07-17T07:05:38.3535040Z Parameters
2025-07-17T07:05:38.3535150Z ----------
2025-07-17T07:05:38.3535260Z actual : scalar
2025-07-17T07:05:38.3535390Z     The object to check.
2025-07-17T07:05:38.3535530Z desired : scalar
2025-07-17T07:05:38.3535660Z     The expected object.
2025-07-17T07:05:38.3535810Z significant : int, optional
2025-07-17T07:05:38.3535980Z     Desired precision, default is 7.
2025-07-17T07:05:38.3536150Z err_msg : str, optional
2025-07-17T07:05:38.3536330Z     The error message to be printed in case of failure.
2025-07-17T07:05:38.3536540Z verbose : bool, optional
2025-07-17T07:05:38.3536760Z     If True, the conflicting values are appended to the error message.
2025-07-17T07:05:38.3536950Z 
2025-07-17T07:05:38.3536990Z Raises
2025-07-17T07:05:38.3537100Z ------
2025-07-17T07:05:38.3537210Z AssertionError
2025-07-17T07:05:38.3537400Z   If actual and desired are not equal up to specified precision.
2025-07-17T07:05:38.3537580Z 
2025-07-17T07:05:38.3537630Z See Also
2025-07-17T07:05:38.3537740Z --------
2025-07-17T07:05:38.3537940Z assert_allclose: Compare two array_like objects for equality with desired
2025-07-17T07:05:38.3538220Z                  relative and/or absolute precision.
2025-07-17T07:05:38.3538530Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-07-17T07:05:38.3538720Z 
2025-07-17T07:05:38.3538770Z Examples
2025-07-17T07:05:38.3538870Z --------
2025-07-17T07:05:38.3539030Z >>> np.testing.assert_approx_equal(
2025-07-17T07:05:38.3539220Z ...     0.12345677777777e-20, 0.1234567e-20
2025-07-17T07:05:38.3539400Z ... )  # doctest: +SKIP
2025-07-17T07:05:38.3539560Z >>> np.testing.assert_approx_equal(
2025-07-17T07:05:38.3539740Z ...     0.12345670e-20,
2025-07-17T07:05:38.3539890Z ...     0.12345671e-20,  # doctest: +SKIP
2025-07-17T07:05:38.3540060Z ...     significant=8,
2025-07-17T07:05:38.3540190Z ... )
2025-07-17T07:05:38.3540320Z >>> np.testing.assert_approx_equal(
2025-07-17T07:05:38.3540490Z ...     0.12345670e-20,
2025-07-17T07:05:38.3540630Z ...     0.12345672e-20,  # doctest: +SKIP
2025-07-17T07:05:38.3540800Z ...     significant=8,
2025-07-17T07:05:38.3540930Z ... )
2025-07-17T07:05:38.3541110Z Traceback (most recent call last):
2025-07-17T07:05:38.3541330Z     ...
2025-07-17T07:05:38.3541440Z AssertionError:
2025-07-17T07:05:38.3541590Z Items are not equal to 8 significant digits:
2025-07-17T07:05:38.3541780Z  ACTUAL: 1.234567e-21
2025-07-17T07:05:38.3541920Z  DESIRED: 1.2345672e-21
2025-07-17T07:05:38.3542010Z 
2025-07-17T07:05:38.3542110Z the evaluated condition that raises the exception is
2025-07-17T07:05:38.3542270Z 
2025-07-17T07:05:38.3542400Z >>> abs(0.12345670e-20 / 1e-21 - 0.12345672e-20 / 1e-21) >= 10 ** -(8 - 1)
2025-07-17T07:05:38.3542620Z True
2025-07-17T07:05:38.3542680Z 
2025-07-17T07:05:38.3542690Z 
2025-07-17T07:05:38.3542830Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.5150740Z 
2025-07-17T07:05:38.5151380Z msg = Cannot scrape callname=assert_array_equal in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=744.
2025-07-17T07:05:38.5152080Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.5152350Z 
2025-07-17T07:05:38.5152490Z Raises an AssertionError if two array_like objects are not equal.
2025-07-17T07:05:38.5152730Z 
2025-07-17T07:05:38.5152860Z Given two array_like objects, check that the shape is equal and all
2025-07-17T07:05:38.5153230Z elements of these objects are equal (but see the Notes for the special
2025-07-17T07:05:38.5153560Z handling of a scalar). An exception is raised at shape mismatch or
2025-07-17T07:05:38.5153900Z conflicting values. In contrast to the standard usage in numpy, NaNs
2025-07-17T07:05:38.5154250Z are compared like numbers, no assertion is raised if both objects have
2025-07-17T07:05:38.5154520Z NaNs in the same positions.
2025-07-17T07:05:38.5154630Z 
2025-07-17T07:05:38.5154780Z The usual caution for verifying equality with floating point numbers is
2025-07-17T07:05:38.5155030Z advised.
2025-07-17T07:05:38.5155100Z 
2025-07-17T07:05:38.5155150Z Parameters
2025-07-17T07:05:38.5155280Z ----------
2025-07-17T07:05:38.5155400Z x : array_like
2025-07-17T07:05:38.5155530Z     The actual object to check.
2025-07-17T07:05:38.5155700Z y : array_like
2025-07-17T07:05:38.5155840Z     The desired, expected object.
2025-07-17T07:05:38.5156020Z err_msg : str, optional
2025-07-17T07:05:38.5156210Z     The error message to be printed in case of failure.
2025-07-17T07:05:38.5156430Z verbose : bool, optional
2025-07-17T07:05:38.5156670Z     If True, the conflicting values are appended to the error message.
2025-07-17T07:05:38.5156910Z strict : bool, optional
2025-07-17T07:05:38.5157130Z     If True, raise an AssertionError when either the shape or the data
2025-07-17T07:05:38.5157430Z     type of the array_like objects does not match. The special
2025-07-17T07:05:38.5157740Z     handling for scalars mentioned in the Notes section is disabled.
2025-07-17T07:05:38.5157940Z 
2025-07-17T07:05:38.5157980Z Raises
2025-07-17T07:05:38.5158090Z ------
2025-07-17T07:05:38.5158210Z AssertionError
2025-07-17T07:05:38.5158640Z     If actual and desired objects are not equal.
2025-07-17T07:05:38.5158800Z 
2025-07-17T07:05:38.5158850Z See Also
2025-07-17T07:05:38.5158960Z --------
2025-07-17T07:05:38.5159180Z assert_allclose: Compare two array_like objects for equality with desired
2025-07-17T07:05:38.5163340Z                  relative and/or absolute precision.
2025-07-17T07:05:38.5163620Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-07-17T07:05:38.5163830Z 
2025-07-17T07:05:38.5163940Z Notes
2025-07-17T07:05:38.5164080Z -----
2025-07-17T07:05:38.5164270Z When one of `x` and `y` is a scalar and the other is array_like, the
2025-07-17T07:05:38.5164620Z function checks that each element of the array_like object is equal to
2025-07-17T07:05:38.5164970Z the scalar. This behaviour can be disabled with the `strict` parameter.
2025-07-17T07:05:38.5165180Z 
2025-07-17T07:05:38.5165230Z Examples
2025-07-17T07:05:38.5165390Z --------
2025-07-17T07:05:38.5165750Z The first assert does not raise an exception:
2025-07-17T07:05:38.5172350Z 
2025-07-17T07:05:38.5172430Z >>> np.testing.assert_array_equal(
2025-07-17T07:05:38.5172670Z ...     [1.0, 2.33333, np.nan], [np.exp(0), 2.33333, np.nan]
2025-07-17T07:05:38.5172870Z ... )
2025-07-17T07:05:38.5172940Z 
2025-07-17T07:05:38.5173090Z Use `assert_allclose` or one of the nulp (number of floating point values)
2025-07-17T07:05:38.5173360Z functions for these cases instead:
2025-07-17T07:05:38.5173480Z 
2025-07-17T07:05:38.5173540Z >>> np.testing.assert_allclose(
2025-07-17T07:05:38.5173780Z ...     [1.0, np.pi, np.nan], [1, np.sqrt(np.pi) ** 2, np.nan], rtol=1e-10, atol=0
2025-07-17T07:05:38.5174020Z ... )
2025-07-17T07:05:38.5174080Z 
2025-07-17T07:05:38.5174210Z As mentioned in the Notes section, `assert_array_equal` has special
2025-07-17T07:05:38.5174530Z handling for scalars. Here the test checks that each value in `x` is 3:
2025-07-17T07:05:38.5174730Z 
2025-07-17T07:05:38.5174790Z >>> x = np.full((2, 5), fill_value=3)
2025-07-17T07:05:38.5174990Z >>> np.testing.assert_array_equal(x, 3)
2025-07-17T07:05:38.5175130Z 
2025-07-17T07:05:38.5175260Z Use `strict` to raise an AssertionError when comparing a scalar with an
2025-07-17T07:05:38.5175500Z array:
2025-07-17T07:05:38.5175560Z 
2025-07-17T07:05:38.5175650Z >>> np.testing.assert_array_equal(x, 3, strict=True)
2025-07-17T07:05:38.5175870Z Traceback (most recent call last):
2025-07-17T07:05:38.5176040Z     ...
2025-07-17T07:05:38.5176150Z AssertionError:
2025-07-17T07:05:38.5176290Z Arrays are not equal
2025-07-17T07:05:38.5176420Z <BLANKLINE>
2025-07-17T07:05:38.5176550Z (shapes (2, 5), () mismatch)
2025-07-17T07:05:38.5176710Z  x: torch.ndarray([[3, 3, 3, 3, 3],
2025-07-17T07:05:38.5176880Z         [3, 3, 3, 3, 3]])
2025-07-17T07:05:38.5177020Z  y: torch.ndarray(3)
2025-07-17T07:05:38.5177110Z 
2025-07-17T07:05:38.5177240Z The `strict` parameter also ensures that the array data types match:
2025-07-17T07:05:38.5177430Z 
2025-07-17T07:05:38.5177490Z >>> x = np.array([2, 2, 2])
2025-07-17T07:05:38.5177670Z >>> y = np.array([2.0, 2.0, 2.0], dtype=np.float32)
2025-07-17T07:05:38.5177900Z >>> np.testing.assert_array_equal(x, y, strict=True)
2025-07-17T07:05:38.5178120Z Traceback (most recent call last):
2025-07-17T07:05:38.5178280Z     ...
2025-07-17T07:05:38.5178390Z AssertionError:
2025-07-17T07:05:38.5178520Z Arrays are not equal
2025-07-17T07:05:38.5178650Z <BLANKLINE>
2025-07-17T07:05:38.5178800Z (dtypes dtype("int64"), dtype("float32") mismatch)
2025-07-17T07:05:38.5179010Z  x: torch.ndarray([2, 2, 2])
2025-07-17T07:05:38.5179170Z  y: torch.ndarray([2., 2., 2.])
2025-07-17T07:05:38.5179280Z 
2025-07-17T07:05:38.5179430Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.5179650Z 
2025-07-17T07:05:38.5180070Z msg = Cannot scrape callname=assert_array_almost_equal in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=851.
2025-07-17T07:05:38.5180700Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.5180970Z 
2025-07-17T07:05:38.5181110Z Raises an AssertionError if two objects are not equal up to desired
2025-07-17T07:05:38.5181350Z precision.
2025-07-17T07:05:38.5181420Z 
2025-07-17T07:05:38.5181600Z .. note:: It is recommended to use one of `assert_allclose`,
2025-07-17T07:05:38.5181880Z           `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
2025-07-17T07:05:38.5182170Z           instead of this function for more consistent floating point
2025-07-17T07:05:38.5182400Z           comparisons.
2025-07-17T07:05:38.5182490Z 
2025-07-17T07:05:38.5182640Z The test verifies identical shapes and that the elements of ``actual`` and
2025-07-17T07:05:38.5182900Z ``desired`` satisfy.
2025-07-17T07:05:38.5182990Z 
2025-07-17T07:05:38.5183070Z     ``abs(desired-actual) < 1.5 * 10**(-decimal)``
2025-07-17T07:05:38.5183210Z 
2025-07-17T07:05:38.5183450Z That is a looser test than originally documented, but agrees with what the
2025-07-17T07:05:38.5183860Z actual implementation did up to rounding vagaries. An exception is raised
2025-07-17T07:05:38.5184240Z at shape mismatch or conflicting values. In contrast to the standard usage
2025-07-17T07:05:38.5184580Z in numpy, NaNs are compared like numbers, no assertion is raised if both
2025-07-17T07:05:38.5184840Z objects have NaNs in the same positions.
2025-07-17T07:05:38.5184970Z 
2025-07-17T07:05:38.5185020Z Parameters
2025-07-17T07:05:38.5185130Z ----------
2025-07-17T07:05:38.5185240Z x : array_like
2025-07-17T07:05:38.5185380Z     The actual object to check.
2025-07-17T07:05:38.5185530Z y : array_like
2025-07-17T07:05:38.5185670Z     The desired, expected object.
2025-07-17T07:05:38.5185840Z decimal : int, optional
2025-07-17T07:05:38.5185990Z     Desired precision, default is 6.
2025-07-17T07:05:38.5186170Z err_msg : str, optional
2025-07-17T07:05:38.5186350Z   The error message to be printed in case of failure.
2025-07-17T07:05:38.5186570Z verbose : bool, optional
2025-07-17T07:05:38.5186790Z     If True, the conflicting values are appended to the error message.
2025-07-17T07:05:38.5186980Z 
2025-07-17T07:05:38.5187030Z Raises
2025-07-17T07:05:38.5187130Z ------
2025-07-17T07:05:38.5187230Z AssertionError
2025-07-17T07:05:38.5187430Z     If actual and desired are not equal up to specified precision.
2025-07-17T07:05:38.5187620Z 
2025-07-17T07:05:38.5187660Z See Also
2025-07-17T07:05:38.5187770Z --------
2025-07-17T07:05:38.5187980Z assert_allclose: Compare two array_like objects for equality with desired
2025-07-17T07:05:38.5188260Z                  relative and/or absolute precision.
2025-07-17T07:05:38.5188530Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-07-17T07:05:38.5188720Z 
2025-07-17T07:05:38.5188770Z Examples
2025-07-17T07:05:38.5188880Z --------
2025-07-17T07:05:38.5189010Z the first assert does not raise an exception
2025-07-17T07:05:38.5189150Z 
2025-07-17T07:05:38.5189300Z >>> np.testing.assert_array_almost_equal([1.0, 2.333, np.nan], [1.0, 2.333, np.nan])
2025-07-17T07:05:38.5189530Z 
2025-07-17T07:05:38.5189590Z >>> np.testing.assert_array_almost_equal(
2025-07-17T07:05:38.5189820Z ...     [1.0, 2.33333, np.nan], [1.0, 2.33339, np.nan], decimal=5
2025-07-17T07:05:38.5190020Z ... )
2025-07-17T07:05:38.5190140Z Traceback (most recent call last):
2025-07-17T07:05:38.5190310Z     ...
2025-07-17T07:05:38.5190350Z AssertionError:
2025-07-17T07:05:38.5190420Z Arrays are not almost equal to 5 decimals
2025-07-17T07:05:38.5190470Z <BLANKLINE>
2025-07-17T07:05:38.5190530Z Mismatched elements: 1 / 3 (33.3%)
2025-07-17T07:05:38.5190600Z Max absolute difference: 5.999999999994898e-05
2025-07-17T07:05:38.5190680Z Max relative difference: 2.5713661239633743e-05
2025-07-17T07:05:38.5190780Z  x: torch.ndarray([1.0000, 2.3333,    nan], dtype=float64)
2025-07-17T07:05:38.5190870Z  y: torch.ndarray([1.0000, 2.3334,    nan], dtype=float64)
2025-07-17T07:05:38.5190870Z 
2025-07-17T07:05:38.5190940Z >>> np.testing.assert_array_almost_equal(
2025-07-17T07:05:38.5191020Z ...     [1.0, 2.33333, np.nan], [1.0, 2.33333, 5], decimal=5
2025-07-17T07:05:38.5191090Z ... )
2025-07-17T07:05:38.5191160Z Traceback (most recent call last):
2025-07-17T07:05:38.5191200Z     ...
2025-07-17T07:05:38.5191250Z AssertionError:
2025-07-17T07:05:38.5191320Z Arrays are not almost equal to 5 decimals
2025-07-17T07:05:38.5191390Z <BLANKLINE>
2025-07-17T07:05:38.5191450Z x and y nan location mismatch:
2025-07-17T07:05:38.5191540Z  x: torch.ndarray([1.0000, 2.3333,    nan], dtype=float64)
2025-07-17T07:05:38.5191640Z  y: torch.ndarray([1.0000, 2.3333, 5.0000], dtype=float64)
2025-07-17T07:05:38.5191640Z 
2025-07-17T07:05:38.5191640Z 
2025-07-17T07:05:38.5191790Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.5191790Z 
2025-07-17T07:05:38.5192210Z msg = Cannot scrape callname=clear_and_catch_warnings in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=1848.
2025-07-17T07:05:38.5192430Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.5192630Z Context manager that resets warning registry for catching warnings
2025-07-17T07:05:38.5192640Z 
2025-07-17T07:05:38.5192780Z     Warnings can be slippery, because, whenever a warning is triggered, Python
2025-07-17T07:05:38.5192920Z     adds a ``__warningregistry__`` member to the *calling* module.  This makes
2025-07-17T07:05:38.5193060Z     it impossible to retrigger the warning in this module, whatever you put in
2025-07-17T07:05:38.5193210Z     the warnings filters.  This context manager accepts a sequence of `modules`
2025-07-17T07:05:38.5193290Z     as a keyword argument to its constructor and:
2025-07-17T07:05:38.5193290Z 
2025-07-17T07:05:38.5193430Z     * stores and removes any ``__warningregistry__`` entries in given `modules`
2025-07-17T07:05:38.5193480Z       on entry;
2025-07-17T07:05:38.5193590Z     * resets ``__warningregistry__`` to its previous state on exit.
2025-07-17T07:05:38.5193590Z 
2025-07-17T07:05:38.5193730Z     This makes it possible to trigger any warning afresh inside the context
2025-07-17T07:05:38.5193850Z     manager without disturbing the state of warnings outside.
2025-07-17T07:05:38.5193850Z 
2025-07-17T07:05:38.5193990Z     For compatibility with Python 3.0, please consider all arguments to be
2025-07-17T07:05:38.5194040Z     keyword-only.
2025-07-17T07:05:38.5194040Z 
2025-07-17T07:05:38.5194080Z     Parameters
2025-07-17T07:05:38.5194130Z     ----------
2025-07-17T07:05:38.5194180Z     record : bool, optional
2025-07-17T07:05:38.5194290Z         Specifies whether warnings should be captured by a custom
2025-07-17T07:05:38.5194430Z         implementation of ``warnings.showwarning()`` and be appended to a list
2025-07-17T07:05:38.5194560Z         returned by the context manager. Otherwise None is returned by the
2025-07-17T07:05:38.5194700Z         context manager. The objects appended to the list are arguments whose
2025-07-17T07:05:38.5194800Z         attributes mirror the arguments to ``showwarning()``.
2025-07-17T07:05:38.5194860Z     modules : sequence, optional
2025-07-17T07:05:38.5194990Z         Sequence of modules for which to reset warnings registry on entry and
2025-07-17T07:05:38.5195110Z         restore on exit. To work correctly, all 'ignore' filters should
2025-07-17T07:05:38.5195170Z         filter by one of these modules.
2025-07-17T07:05:38.5195180Z 
2025-07-17T07:05:38.5195230Z     Examples
2025-07-17T07:05:38.5195270Z     --------
2025-07-17T07:05:38.5195320Z     >>> import warnings
2025-07-17T07:05:38.5195430Z     >>> with np.testing.clear_and_catch_warnings(  # doctest: +SKIP
2025-07-17T07:05:38.5195500Z     ...     modules=[np.core.fromnumeric]
2025-07-17T07:05:38.5195540Z     ... ):
2025-07-17T07:05:38.5195610Z     ...     warnings.simplefilter("always")
2025-07-17T07:05:38.5195750Z     ...     warnings.filterwarnings("ignore", module="np.core.fromnumeric")
2025-07-17T07:05:38.5195850Z     ...     # do something that raises a warning but ignore those in
2025-07-17T07:05:38.5195940Z     ...     # np.core.fromnumeric
2025-07-17T07:05:38.5195980Z     
2025-07-17T07:05:38.5196130Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.5296730Z 
2025-07-17T07:05:38.5297330Z msg = Cannot scrape callname=calculate_gain in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py line=142.
2025-07-17T07:05:38.5297500Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.5297640Z Return the recommended gain value for the given nonlinearity function.
2025-07-17T07:05:38.5297640Z 
2025-07-17T07:05:38.5297710Z     The values are as follows:
2025-07-17T07:05:38.5297710Z 
2025-07-17T07:05:38.5297790Z     ================= ====================================================
2025-07-17T07:05:38.5297850Z     nonlinearity      gain
2025-07-17T07:05:38.5298060Z     ================= ====================================================
2025-07-17T07:05:38.5298190Z     Linear / Identity :math:`1`
2025-07-17T07:05:38.5298250Z     Conv{1,2,3}D      :math:`1`
2025-07-17T07:05:38.5298300Z     Sigmoid           :math:`1`
2025-07-17T07:05:38.5298370Z     Tanh              :math:`\frac{5}{3}`
2025-07-17T07:05:38.5298430Z     ReLU              :math:`\sqrt{2}`
2025-07-17T07:05:38.5298560Z     Leaky Relu        :math:`\sqrt{\frac{2}{1 + \text{negative\_slope}^2}}`
2025-07-17T07:05:38.5298620Z     SELU              :math:`\frac{3}{4}`
2025-07-17T07:05:38.5298700Z     ================= ====================================================
2025-07-17T07:05:38.5298700Z 
2025-07-17T07:05:38.5298750Z     .. warning::
2025-07-17T07:05:38.5298880Z         In order to implement `Self-Normalizing Neural Networks`_ ,
2025-07-17T07:05:38.5299030Z         you should use ``nonlinearity='linear'`` instead of ``nonlinearity='selu'``.
2025-07-17T07:05:38.5299140Z         This gives the initial weights a variance of ``1 / N``,
2025-07-17T07:05:38.5299280Z         which is necessary to induce a stable fixed point in the forward pass.
2025-07-17T07:05:38.5299430Z         In contrast, the default gain for ``SELU`` sacrifices the normalization
2025-07-17T07:05:38.5299580Z         effect for more stable gradient flow in rectangular layers.
2025-07-17T07:05:38.5299590Z 
2025-07-17T07:05:38.5299630Z     Args:
2025-07-17T07:05:38.5299760Z         nonlinearity: the non-linear function (`nn.functional` name)
2025-07-17T07:05:38.5299870Z         param: optional parameter for the non-linear function
2025-07-17T07:05:38.5299870Z 
2025-07-17T07:05:38.5299920Z     Examples:
2025-07-17T07:05:38.5299990Z         >>> gain = nn.init.calculate_gain(
2025-07-17T07:05:38.5300050Z         ...     "leaky_relu", 0.2
2025-07-17T07:05:38.5300130Z         ... )  # leaky_relu with negative_slope=0.2
2025-07-17T07:05:38.5300130Z 
2025-07-17T07:05:38.5300440Z     .. _Self-Normalizing Neural Networks: https://papers.nips.cc/paper/2017/hash/5d44ee6f2c3f71b73125876103c8f6c4-Abstract.html
2025-07-17T07:05:38.5300480Z     
2025-07-17T07:05:38.5300640Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.5300640Z 
2025-07-17T07:05:38.5301100Z msg = Cannot scrape callname=DistributedDataParallel.join in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py line=1766.
2025-07-17T07:05:38.5301260Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.5301260Z 
2025-07-17T07:05:38.5301400Z Context manager for training with uneven inputs across processes in DDP.
2025-07-17T07:05:38.5301410Z 
2025-07-17T07:05:38.5301540Z This context manager will keep track of already-joined DDP processes,
2025-07-17T07:05:38.5301660Z and "shadow" the forward and backward passes by inserting collective
2025-07-17T07:05:38.5301800Z communication operations to match with the ones created by non-joined
2025-07-17T07:05:38.5301940Z DDP processes. This will ensure each collective call has a corresponding
2025-07-17T07:05:38.5302110Z call by already-joined DDP processes, preventing hangs or errors that
2025-07-17T07:05:38.5302240Z would otherwise happen when training with uneven inputs across
2025-07-17T07:05:38.5302380Z processes. Alternatively, if the flag ``throw_on_early_termination`` is
2025-07-17T07:05:38.5302530Z specified to be ``True``, all trainers will throw an error once one rank
2025-07-17T07:05:38.5302650Z runs out of inputs, allowing these errors to be caught and handled
2025-07-17T07:05:38.5302720Z according to application logic.
2025-07-17T07:05:38.5302720Z 
2025-07-17T07:05:38.5302850Z Once all DDP processes have joined, the context manager will broadcast
2025-07-17T07:05:38.5302990Z the model corresponding to the last joined process to all processes to
2025-07-17T07:05:38.5303070Z ensure the model is the same across all processes
2025-07-17T07:05:38.5303130Z (which is guaranteed by DDP).
2025-07-17T07:05:38.5303130Z 
2025-07-17T07:05:38.5303320Z To use this to enable training with uneven inputs across processes,
2025-07-17T07:05:38.5303520Z simply wrap this context manager around your training loop. No further
2025-07-17T07:05:38.5303620Z modifications to the model or data loading is required.
2025-07-17T07:05:38.5303630Z 
2025-07-17T07:05:38.5303680Z .. warning::
2025-07-17T07:05:38.5303800Z     If the model or training loop this context manager is wrapped around
2025-07-17T07:05:38.5303910Z     has additional distributed collective operations, such as
2025-07-17T07:05:38.5304020Z     ``SyncBatchNorm`` in the model's forward pass, then the flag
2025-07-17T07:05:38.5304150Z     ``throw_on_early_termination`` must be enabled. This is because this
2025-07-17T07:05:38.5304270Z     context manager is not aware of non-DDP collective communication.
2025-07-17T07:05:38.5304380Z     This flag will cause all ranks to throw when any one rank
2025-07-17T07:05:38.5304500Z     exhausts inputs, allowing these errors to be caught and recovered
2025-07-17T07:05:38.5304560Z     from across all ranks.
2025-07-17T07:05:38.5304560Z 
2025-07-17T07:05:38.5304600Z Args:
2025-07-17T07:05:38.5304720Z     divide_by_initial_world_size (bool): If ``True``, will divide
2025-07-17T07:05:38.5304840Z         gradients by the initial ``world_size`` DDP training was launched
2025-07-17T07:05:38.5304940Z         with. If ``False``, will compute the effective world size
2025-07-17T07:05:38.5305050Z         (number of ranks that have not depleted their inputs yet) and
2025-07-17T07:05:38.5305140Z         divide gradients by that during allreduce. Set
2025-07-17T07:05:38.5305250Z         ``divide_by_initial_world_size=True`` to ensure every input
2025-07-17T07:05:38.5305380Z         sample including the uneven inputs have equal weight in terms of
2025-07-17T07:05:38.5305480Z         how much they contribute to the global gradient. This is
2025-07-17T07:05:38.5305580Z         achieved by always dividing the gradient by the initial
2025-07-17T07:05:38.5305690Z         ``world_size`` even when we encounter uneven inputs. If you set
2025-07-17T07:05:38.5305800Z         this to ``False``, we divide the gradient by the remaining
2025-07-17T07:05:38.5305920Z         number of nodes. This ensures parity with training on a smaller
2025-07-17T07:05:38.5306030Z         ``world_size`` although it also means the uneven inputs would
2025-07-17T07:05:38.5306150Z         contribute more towards the global gradient. Typically, you
2025-07-17T07:05:38.5306260Z         would want to set this to ``True`` for cases where the last few
2025-07-17T07:05:38.5306380Z         inputs of your training job are uneven. In extreme cases, where
2025-07-17T07:05:38.5306490Z         there is a large discrepancy in the number of inputs, setting
2025-07-17T07:05:38.5306570Z         this to ``False`` might provide better results.
2025-07-17T07:05:38.5306700Z     enable (bool): Whether to enable uneven input detection or not. Pass
2025-07-17T07:05:38.5306800Z         in ``enable=False`` to disable in cases where you know that
2025-07-17T07:05:38.5306950Z         inputs are even across participating processes. Default is
2025-07-17T07:05:38.5307000Z         ``True``.
2025-07-17T07:05:38.5307110Z     throw_on_early_termination (bool): Whether to throw an error
2025-07-17T07:05:38.5307220Z         or continue training when at least one rank has exhausted
2025-07-17T07:05:38.5307360Z         inputs. If ``True``, will throw upon the first rank reaching end
2025-07-17T07:05:38.5307470Z         of data. If ``False``, will continue training with a smaller
2025-07-17T07:05:38.5307580Z         effective world size until all ranks are joined. Note that if
2025-07-17T07:05:38.5307670Z         this flag is specified, then the flag
2025-07-17T07:05:38.5307780Z         ``divide_by_initial_world_size`` would be ignored. Default
2025-07-17T07:05:38.5307830Z         is ``False``.
2025-07-17T07:05:38.5307840Z 
2025-07-17T07:05:38.5307840Z 
2025-07-17T07:05:38.5307880Z Example::
2025-07-17T07:05:38.5307890Z 
2025-07-17T07:05:38.5308020Z     >>> # xdoctest: +SKIP("Distributed")
2025-07-17T07:05:38.5308120Z     >>> import torch
2025-07-17T07:05:38.5308190Z     >>> import torch.distributed as dist
2025-07-17T07:05:38.5308230Z     >>> import os
2025-07-17T07:05:38.5308310Z     >>> import torch.multiprocessing as mp
2025-07-17T07:05:38.5308370Z     >>> import torch.nn as nn
2025-07-17T07:05:38.5308440Z     >>> # On each spawned worker
2025-07-17T07:05:38.5308490Z     >>> def worker(rank):
2025-07-17T07:05:38.5308600Z     >>>     dist.init_process_group("nccl", rank=rank, world_size=2)
2025-07-17T07:05:38.5308660Z     >>>     torch.cuda.set_device(rank)
2025-07-17T07:05:38.5308750Z     >>>     model = nn.Linear(1, 1, bias=False).to(rank)
2025-07-17T07:05:38.5308860Z     >>>     model = torch.nn.parallel.DistributedDataParallel(
2025-07-17T07:05:38.5308950Z     >>>         model, device_ids=[rank], output_device=rank
2025-07-17T07:05:38.5309000Z     >>>     )
2025-07-17T07:05:38.5309070Z     >>>     # Rank 1 gets one more input than rank 0.
2025-07-17T07:05:38.5309200Z     >>>     inputs = [torch.tensor([1]).float() for _ in range(10 + rank)]
2025-07-17T07:05:38.5309260Z     >>>     with model.join():
2025-07-17T07:05:38.5309320Z     >>>         for _ in range(5):
2025-07-17T07:05:38.5309370Z     >>>             for inp in inputs:
2025-07-17T07:05:38.5309450Z     >>>                 loss = model(inp).sum()
2025-07-17T07:05:38.5309500Z     >>>                 loss.backward()
2025-07-17T07:05:38.5309620Z     >>>     # Without the join() API, the below synchronization will hang
2025-07-17T07:05:38.5309710Z     >>>     # blocking for rank 1's allreduce to complete.
2025-07-17T07:05:38.5309780Z     >>>     torch.cuda.synchronize(device=rank)
2025-07-17T07:05:38.5309790Z 
2025-07-17T07:05:38.5309940Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.5309940Z 
2025-07-17T07:05:38.5310430Z msg = Cannot scrape callname=DistributedDataParallel._register_fused_optim in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py line=2057.
2025-07-17T07:05:38.5310590Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.5310590Z 
2025-07-17T07:05:38.5310780Z Register an optimizer in DDP to optimize parameter immediately after its gradient reduction.
2025-07-17T07:05:38.5310780Z 
2025-07-17T07:05:38.5310900Z Registers an optimizer with DDP such that the optimization for a
2025-07-17T07:05:38.5311030Z parameter will run immediately when that parameter's gradient is
2025-07-17T07:05:38.5311140Z finished with reduction, instead of waiting for all parameters'
2025-07-17T07:05:38.5311270Z gradients to finish reduction. This can result in a training speedup
2025-07-17T07:05:38.5311400Z depending on your workload since the optimizer can run while gradient
2025-07-17T07:05:38.5311540Z reduction for other parameters are still ongoing. In addition, this has
2025-07-17T07:05:38.5311680Z the potential to reduce peak memory consumption during training, as it
2025-07-17T07:05:38.5311830Z only needs to load the per-parameter optimizer states of a single
2025-07-17T07:05:38.5311960Z parameter at a time, instead of loading all per-parameter optimizer
2025-07-17T07:05:38.5312010Z states at once.
2025-07-17T07:05:38.5312010Z 
2025-07-17T07:05:38.5312070Z Args:
2025-07-17T07:05:38.5312190Z     optim (Type): a ``torch.optim.Optimizer`` class to be registered
2025-07-17T07:05:38.5312250Z     as a fused optimizer.
2025-07-17T07:05:38.5312340Z     *args (Sequence[Any]): Arguments to forward to `optim`.
2025-07-17T07:05:38.5312470Z     optim_params (Optional[Iterable[torch.Tensor]]): Set of parameters
2025-07-17T07:05:38.5312610Z     to optimize, similar to `params` argument of traditional `torch.optim`
2025-07-17T07:05:38.5312730Z     Optimizers. If this is omitted, all DDP model parameters will be
2025-07-17T07:05:38.5312780Z     optimized.
2025-07-17T07:05:38.5312900Z     **kwargs: (Dict[str, Any]): Keyword arguments to forward to `optim`.
2025-07-17T07:05:38.5312960Z 
2025-07-17T07:05:38.5313070Z .. warning ::
2025-07-17T07:05:38.5313210Z     _register_fused_optim should only be called once on a DDP instance,
2025-07-17T07:05:38.5313330Z     and registering multiple fused optimizers for the same DDP model
2025-07-17T07:05:38.5313410Z     is not currently supported. Please ping
2025-07-17T07:05:38.5313550Z     https://github.com/pytorch/pytorch/issues/71595 if this is necessary
2025-07-17T07:05:38.5313600Z     for your use case.
2025-07-17T07:05:38.5313600Z 
2025-07-17T07:05:38.5313650Z .. warning ::
2025-07-17T07:05:38.5313760Z     _register_fused_optim and register_comm_hook currently do not
2025-07-17T07:05:38.5313890Z     compose together, meaning that custom DDP communication hooks are
2025-07-17T07:05:38.5313990Z     not supported with overlapped optimizers. Please ping
2025-07-17T07:05:38.5314120Z     https://github.com/pytorch/pytorch/issues/71595 if this is necessary
2025-07-17T07:05:38.5314170Z     for your use case.
2025-07-17T07:05:38.5314180Z 
2025-07-17T07:05:38.5314220Z .. warning ::
2025-07-17T07:05:38.5314360Z     Gradient accumulation and DDP `no_sync` are currently not supported
2025-07-17T07:05:38.5314430Z     with overlapped optimizer. Please ping
2025-07-17T07:05:38.5314560Z     https://github.com/pytorch/pytorch/issues/71595 if this is necessary
2025-07-17T07:05:38.5314610Z     for your use case.
2025-07-17T07:05:38.5314620Z 
2025-07-17T07:05:38.5314660Z Example::
2025-07-17T07:05:38.5314660Z 
2025-07-17T07:05:38.5314740Z     >>> # xdoctest: +SKIP("No rendezvous handler")
2025-07-17T07:05:38.5314920Z     >>> torch.distributed.init_process_group(backend='nccl', world_size=4, init_method='...')
2025-07-17T07:05:38.5315050Z     >>> net = torch.nn.parallel.DistributedDataParallel(model, pg)
2025-07-17T07:05:38.5315100Z     >>> lr = 1e-2
2025-07-17T07:05:38.5315150Z     >>> betas = (0.9, 0.99)
2025-07-17T07:05:38.5315200Z     >>> eps = 1e-6
2025-07-17T07:05:38.5315330Z     >>> net._register_fused_optim(torch.optim.Adam, lr, betas=betas, eps=eps)
2025-07-17T07:05:38.5315400Z     >>> # Example with subset of parameters
2025-07-17T07:05:38.5315480Z     >>> params_to_opt = [list(net.parameters())[0]]
2025-07-17T07:05:38.5315540Z     >>> net._register_fused_optim(
2025-07-17T07:05:38.5315680Z     ...   torch.optim.Adam, lr, optim_params=params_to_opt,  betas=betas, eps=eps
2025-07-17T07:05:38.5315730Z     ... )
2025-07-17T07:05:38.5315730Z 
2025-07-17T07:05:38.5315880Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.5388860Z 
2025-07-17T07:05:38.5389410Z msg = Cannot scrape callname=register_parametrization in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/parametrize.py line=424.
2025-07-17T07:05:38.5389610Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.5389700Z Register a parametrization to a tensor in a module.
2025-07-17T07:05:38.5389700Z 
2025-07-17T07:05:38.5389880Z     Assume that ``tensor_name="weight"`` for simplicity. When accessing ``module.weight``,
2025-07-17T07:05:38.5390110Z     the module will return the parametrized version ``parametrization(module.weight)``.
2025-07-17T07:05:38.5390270Z     If the original tensor requires a gradient, the backward pass will differentiate
2025-07-17T07:05:38.5390500Z     through :attr:`parametrization`, and the optimizer will update the tensor accordingly.
2025-07-17T07:05:38.5390500Z 
2025-07-17T07:05:38.5390690Z     The first time that a module registers a parametrization, this function will add an attribute
2025-07-17T07:05:38.5390850Z     ``parametrizations`` to the module of type :class:`~ParametrizationList`.
2025-07-17T07:05:38.5390850Z 
2025-07-17T07:05:38.5391000Z     The list of parametrizations on the tensor ``weight`` will be accessible under
2025-07-17T07:05:38.5391080Z     ``module.parametrizations.weight``.
2025-07-17T07:05:38.5391090Z 
2025-07-17T07:05:38.5391170Z     The original tensor will be accessible under
2025-07-17T07:05:38.5391340Z     ``module.parametrizations.weight.original``.
2025-07-17T07:05:38.5391400Z 
2025-07-17T07:05:38.5391570Z     Parametrizations may be concatenated by registering several parametrizations
2025-07-17T07:05:38.5391630Z     on the same attribute.
2025-07-17T07:05:38.5391630Z 
2025-07-17T07:05:38.5391780Z     The training mode of a registered parametrization is updated on registration
2025-07-17T07:05:38.5391860Z     to match the training mode of the host module
2025-07-17T07:05:38.5391870Z 
2025-07-17T07:05:38.5392050Z     Parametrized parameters and buffers have an inbuilt caching system that can be activated
2025-07-17T07:05:38.5392130Z     using the context manager :func:`cached`.
2025-07-17T07:05:38.5392130Z 
2025-07-17T07:05:38.5392280Z     A :attr:`parametrization` may optionally implement a method with signature
2025-07-17T07:05:38.5392280Z 
2025-07-17T07:05:38.5392340Z     .. code-block:: python
2025-07-17T07:05:38.5392340Z 
2025-07-17T07:05:38.5392480Z         def right_inverse(self, X: Tensor) -> Union[Tensor, Sequence[Tensor]]
2025-07-17T07:05:38.5392480Z 
2025-07-17T07:05:38.5392640Z     This method is called on the unparametrized tensor when the first parametrization
2025-07-17T07:05:38.5392770Z     is registered to compute the initial value of the original tensor.
2025-07-17T07:05:38.5392960Z     If this method is not implemented, the original tensor will be just the unparametrized tensor.
2025-07-17T07:05:38.5392960Z 
2025-07-17T07:05:38.5393150Z     If all the parametrizations registered on a tensor implement `right_inverse` it is possible
2025-07-17T07:05:38.5393320Z     to initialize a parametrized tensor by assigning to it, as shown in the example below.
2025-07-17T07:05:38.5393320Z 
2025-07-17T07:05:38.5393470Z     It is possible for the first parametrization to depend on several inputs.
2025-07-17T07:05:38.5393620Z     This may be implemented returning a tuple of tensors from ``right_inverse``
2025-07-17T07:05:38.5393760Z     (see the example implementation of a ``RankOne`` parametrization below).
2025-07-17T07:05:38.5393770Z 
2025-07-17T07:05:38.5393970Z     In this case, the unconstrained tensors are also located under ``module.parametrizations.weight``
2025-07-17T07:05:38.5394050Z     with names ``original0``, ``original1``,...
2025-07-17T07:05:38.5394050Z 
2025-07-17T07:05:38.5394100Z     .. note::
2025-07-17T07:05:38.5394100Z 
2025-07-17T07:05:38.5394260Z         If unsafe=False (default) both the forward and right_inverse methods will be called
2025-07-17T07:05:38.5394350Z         once to perform a number of consistency checks.
2025-07-17T07:05:38.5394510Z         If unsafe=True, then right_inverse will be called if the tensor is not parametrized,
2025-07-17T07:05:38.5394580Z         and nothing will be called otherwise.
2025-07-17T07:05:38.5394590Z 
2025-07-17T07:05:38.5394630Z     .. note::
2025-07-17T07:05:38.5394630Z 
2025-07-17T07:05:38.5394760Z         In most situations, ``right_inverse`` will be a function such that
2025-07-17T07:05:38.5394830Z         ``forward(right_inverse(X)) == X`` (see
2025-07-17T07:05:38.5395040Z         `right inverse <https://en.wikipedia.org/wiki/Inverse_function#Right_inverses>`_).
2025-07-17T07:05:38.5395190Z         Sometimes, when the parametrization is not surjective, it may be reasonable
2025-07-17T07:05:38.5395240Z         to relax this.
2025-07-17T07:05:38.5395260Z 
2025-07-17T07:05:38.5395310Z     .. warning::
2025-07-17T07:05:38.5395310Z 
2025-07-17T07:05:38.5395480Z         If a parametrization depends on several inputs, :func:`~register_parametrization`
2025-07-17T07:05:38.5395630Z         will register a number of new parameters. If such parametrization is registered
2025-07-17T07:05:38.5395790Z         after the optimizer is created, these new parameters will need to be added manually
2025-07-17T07:05:38.5395910Z         to the optimizer. See :meth:`torch.Optimizer.add_param_group`.
2025-07-17T07:05:38.5395920Z 
2025-07-17T07:05:38.5395960Z     Args:
2025-07-17T07:05:38.5396150Z         module (nn.Module): module on which to register the parametrization
2025-07-17T07:05:38.5396330Z         tensor_name (str): name of the parameter or buffer on which to register
2025-07-17T07:05:38.5396390Z             the parametrization
2025-07-17T07:05:38.5396510Z         parametrization (nn.Module): the parametrization to register
2025-07-17T07:05:38.5396560Z     Keyword args:
2025-07-17T07:05:38.5396690Z         unsafe (bool): a boolean flag that denotes whether the parametrization
2025-07-17T07:05:38.5396820Z             may change the dtype and shape of the tensor. Default: `False`
2025-07-17T07:05:38.5396980Z             Warning: the parametrization is not checked for consistency upon registration.
2025-07-17T07:05:38.5397050Z             Enable this flag at your own risk.
2025-07-17T07:05:38.5397050Z 
2025-07-17T07:05:38.5397090Z     Raises:
2025-07-17T07:05:38.5397270Z         ValueError: if the module does not have a parameter or a buffer named :attr:`tensor_name`
2025-07-17T07:05:38.5397270Z 
2025-07-17T07:05:38.5397320Z     Examples:
2025-07-17T07:05:38.5397410Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK)
2025-07-17T07:05:38.5397460Z         >>> import torch
2025-07-17T07:05:38.5397520Z         >>> import torch.nn as nn
2025-07-17T07:05:38.5397600Z         >>> import torch.nn.utils.parametrize as P
2025-07-17T07:05:38.5397650Z         >>>
2025-07-17T07:05:38.5397710Z         >>> class Symmetric(nn.Module):
2025-07-17T07:05:38.5397760Z         >>>     def forward(self, X):
2025-07-17T07:05:38.5397870Z         >>>         return X.triu() + X.triu(1).T  # Return a symmetric matrix
2025-07-17T07:05:38.5397910Z         >>>
2025-07-17T07:05:38.5397980Z         >>>     def right_inverse(self, A):
2025-07-17T07:05:38.5398030Z         >>>         return A.triu()
2025-07-17T07:05:38.5398080Z         >>>
2025-07-17T07:05:38.5398130Z         >>> m = nn.Linear(5, 5)
2025-07-17T07:05:38.5398230Z         >>> P.register_parametrization(m, "weight", Symmetric())
2025-07-17T07:05:38.5398370Z         >>> print(torch.allclose(m.weight, m.weight.T))  # m.weight is now symmetric
2025-07-17T07:05:38.5398420Z         True
2025-07-17T07:05:38.5398480Z         >>> A = torch.rand(5, 5)
2025-07-17T07:05:38.5398540Z         >>> A = A + A.T  # A is now symmetric
2025-07-17T07:05:38.5398660Z         >>> m.weight = A  # Initialize the weight to be the symmetric matrix A
2025-07-17T07:05:38.5398730Z         >>> print(torch.allclose(m.weight, A))
2025-07-17T07:05:38.5398780Z         True
2025-07-17T07:05:38.5398780Z 
2025-07-17T07:05:38.5398840Z         >>> class RankOne(nn.Module):
2025-07-17T07:05:38.5398900Z         >>>     def forward(self, x, y):
2025-07-17T07:05:38.5398980Z         >>> # Form a rank 1 matrix multiplying two vectors
2025-07-17T07:05:38.5399060Z         >>>         return x.unsqueeze(-1) @ y.unsqueeze(-2)
2025-07-17T07:05:38.5399100Z         >>>
2025-07-17T07:05:38.5399170Z         >>>     def right_inverse(self, Z):
2025-07-17T07:05:38.5399240Z         >>> # Project Z onto the rank 1 matrices
2025-07-17T07:05:38.5399340Z         >>>         U, S, Vh = torch.linalg.svd(Z, full_matrices=False)
2025-07-17T07:05:38.5399430Z         >>> # Return rescaled singular vectors
2025-07-17T07:05:38.5399510Z         >>>         s0_sqrt = S[0].sqrt().unsqueeze(-1)
2025-07-17T07:05:38.5399600Z         >>>         return U[..., :, 0] * s0_sqrt, Vh[..., 0, :] * s0_sqrt
2025-07-17T07:05:38.5399680Z         >>>
2025-07-17T07:05:38.5399770Z         >>> linear_rank_one = P.register_parametrization(
2025-07-17T07:05:38.5399840Z         ...     nn.Linear(4, 4), "weight", RankOne()
2025-07-17T07:05:38.5399890Z         ... )
2025-07-17T07:05:38.5400010Z         >>> print(torch.linalg.matrix_rank(linear_rank_one.weight).item())
2025-07-17T07:05:38.5400060Z         1
2025-07-17T07:05:38.5400060Z 
2025-07-17T07:05:38.5400100Z     
2025-07-17T07:05:38.5400250Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.5400250Z 
2025-07-17T07:05:38.5400740Z msg = Cannot scrape callname=convert_conv2d_weight_memory_format in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/memory_format.py line=14.
2025-07-17T07:05:38.5400950Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.5401080Z Convert ``memory_format`` of ``nn.Conv2d.weight`` to ``memory_format``.
2025-07-17T07:05:38.5401090Z 
2025-07-17T07:05:38.5401250Z     The conversion recursively applies to nested ``nn.Module``, including ``module``.
2025-07-17T07:05:38.5401410Z     Note that it only changes the memory_format, but not the semantics of each dimensions.
2025-07-17T07:05:38.5401570Z     This function is used to facilitate the computation to adopt NHWC kernels, which
2025-07-17T07:05:38.5401750Z     provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0
2025-07-17T07:05:38.5401750Z 
2025-07-17T07:05:38.5401850Z     .. note::
2025-07-17T07:05:38.5402000Z         Calling ``model.to(memory_format=torch.channels_last)`` is more aggressive
2025-07-17T07:05:38.5402160Z         than the utility function ``convert_conv2d_weight_memory_format``. Any
2025-07-17T07:05:38.5402290Z         layer with 4d weight will be affected by ``model.to``, which does not
2025-07-17T07:05:38.5402440Z         necessarily benefit from conversion to specified ``memory_format``.
2025-07-17T07:05:38.5402580Z         One place we are confident in is that NHWC(channels_last) conversion for
2025-07-17T07:05:38.5402730Z         convolution in cuDNN, as it is beneficial to run convolution in NHWC,
2025-07-17T07:05:38.5407480Z         even in cases where we have to apply permutation to input tensors.
2025-07-17T07:05:38.5407480Z 
2025-07-17T07:05:38.5407640Z         Hence our strategy here is to convert only the weight of convolution to
2025-07-17T07:05:38.5407720Z         channels_last. This ensures that;
2025-07-17T07:05:38.5407850Z         1. Fast convolution kernels will be used, the benefit of which could
2025-07-17T07:05:38.5408000Z         outweigh overhead of permutation (if input is not in the same format).
2025-07-17T07:05:38.5408140Z         2. No unnecessary permutations are applied on layers that do not benefit
2025-07-17T07:05:38.5408210Z         from memory_format conversion.
2025-07-17T07:05:38.5408210Z 
2025-07-17T07:05:38.5408340Z         The optimal case is that, layers between convolution layers are channels
2025-07-17T07:05:38.5408480Z         last compatible. Input tensor would be permuted to channels last when it
2025-07-17T07:05:38.5408620Z         encounters the first convolution layer and stay in that memory format.
2025-07-17T07:05:38.5408760Z         Hence following convolutions will not need to permute its input tensor.
2025-07-17T07:05:38.5408760Z 
2025-07-17T07:05:38.5408900Z         In case where a channels last incompatible layer is between convolution
2025-07-17T07:05:38.5409040Z         layers, we need to permute the input tensor back to contiguous format
2025-07-17T07:05:38.5409170Z         for that layer. The input tensor will go through the remaining layers in
2025-07-17T07:05:38.5409360Z         contiguous format and be permuted to channels last when it encounters
2025-07-17T07:05:38.5409500Z         another convolution layer. There's no point in propagating that
2025-07-17T07:05:38.5409630Z         permutation to an earlier layer, as most layers are quite agnostic to
2025-07-17T07:05:38.5409720Z         ``memory_format``.
2025-07-17T07:05:38.5409730Z 
2025-07-17T07:05:38.5409870Z         This claim might change when PyTorch supports fusion of permutation, as
2025-07-17T07:05:38.5410000Z         there might have been a better spot to fuse the permutation other than
2025-07-17T07:05:38.5410060Z         immediately before a convolution.
2025-07-17T07:05:38.5410070Z 
2025-07-17T07:05:38.5410110Z     Args:
2025-07-17T07:05:38.5410240Z         module (nn.Module): ``nn.Conv2d`` & ``nn.ConvTranspose2d`` or container
2025-07-17T07:05:38.5410300Z                             ``nn.Module``
2025-07-17T07:05:38.5410390Z         memory_format: user specified ``memory_format``,
2025-07-17T07:05:38.5410780Z             e.g. ``torch.channels_last`` or ``torch.contiguous_format``
2025-07-17T07:05:38.5411030Z 
2025-07-17T07:05:38.5411080Z     Returns:
2025-07-17T07:05:38.5411160Z         The original module with updated ``nn.Conv2d``
2025-07-17T07:05:38.5411160Z 
2025-07-17T07:05:38.5411210Z     Example:
2025-07-17T07:05:38.5411290Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-07-17T07:05:38.5411390Z         >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG)
2025-07-17T07:05:38.5411450Z         >>> input = torch.randint(
2025-07-17T07:05:38.5411540Z         ...     1, 10, (2, 8, 4, 4), dtype=torch.float16, device="cuda"
2025-07-17T07:05:38.5411580Z         ... )
2025-07-17T07:05:38.5411640Z         >>> model = nn.Sequential(
2025-07-17T07:05:38.5411710Z         >>>     nn.Conv2d(8, 4, 3)).cuda().half()
2025-07-17T07:05:38.5411770Z         >>> # This is identical to:
2025-07-17T07:05:38.5411920Z         >>> # nn.utils.convert_conv2d_weight_memory_format(model, torch.channels_last)
2025-07-17T07:05:38.5412030Z         >>> model = nn.utils.convert_conv2d_weight_memory_format(
2025-07-17T07:05:38.5412090Z         ...     model, torch.channels_last
2025-07-17T07:05:38.5412130Z         ... )
2025-07-17T07:05:38.5412190Z         >>> out = model(input)
2025-07-17T07:05:38.5412230Z     
2025-07-17T07:05:38.5412380Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.5668710Z 
2025-07-17T07:05:38.5669400Z msg = Cannot scrape callname=convert_conv3d_weight_memory_format in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/memory_format.py line=93.
2025-07-17T07:05:38.5669610Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.5669750Z Convert ``memory_format`` of ``nn.Conv3d.weight`` to ``memory_format``
2025-07-17T07:05:38.5669920Z     The conversion recursively applies to nested ``nn.Module``, including ``module``.
2025-07-17T07:05:38.5670100Z     Note that it only changes the memory_format, but not the semantics of each dimensions.
2025-07-17T07:05:38.5670270Z     This function is used to facilitate the computation to adopt NHWC kernels, which
2025-07-17T07:05:38.5670460Z     provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0
2025-07-17T07:05:38.5670460Z 
2025-07-17T07:05:38.5670520Z     .. note::
2025-07-17T07:05:38.5670680Z         Calling ``model.to(memory_format=torch.channels_last_3d)`` is more aggressive
2025-07-17T07:05:38.5670820Z         than the utility function ``convert_conv3d_weight_memory_format``. Any
2025-07-17T07:05:38.5670950Z         layer with 4d weight will be affected by ``model.to``, which does not
2025-07-17T07:05:38.5671100Z         necessarily benefit from conversion to specified ``memory_format``.
2025-07-17T07:05:38.5671240Z         One place we are confident in is that NDHWC(channels_last_3d) conversion for
2025-07-17T07:05:38.5671380Z         convolution in cuDNN, as it is beneficial to run convolution in NDHWC,
2025-07-17T07:05:38.5671590Z         even in cases where we have to apply permutation to input tensors.
2025-07-17T07:05:38.5671590Z 
2025-07-17T07:05:38.5671740Z         Hence our strategy here is to convert only the weight of convolution to
2025-07-17T07:05:38.5671890Z         channels_last_3d. This ensures that;
2025-07-17T07:05:38.5672030Z         1. Fast convolution kernels will be used, the benefit of which could
2025-07-17T07:05:38.5672170Z         outweigh overhead of permutation (if input is not in the same format).
2025-07-17T07:05:38.5672320Z         2. No unnecessary permutations are applied on layers that do not benefit
2025-07-17T07:05:38.5672380Z         from memory_format conversion.
2025-07-17T07:05:38.5672380Z 
2025-07-17T07:05:38.5672520Z         The optimal case is that, layers between convolution layers are channels
2025-07-17T07:05:38.5672670Z         last compatible. Input tensor would be permuted to channels last when it
2025-07-17T07:05:38.5672950Z         encounters the first convolution layer and stay in that memory format.
2025-07-17T07:05:38.5673190Z         Hence following convolutions will not need to permute its input tensor.
2025-07-17T07:05:38.5673190Z 
2025-07-17T07:05:38.5673320Z         In case where a channels last incompatible layer is between convolution
2025-07-17T07:05:38.5673460Z         layers, we need to permute the input tensor back to contiguous format
2025-07-17T07:05:38.5673600Z         for that layer. The input tensor will go through the remaining layers in
2025-07-17T07:05:38.5673730Z         contiguous format and be permuted to channels last when it encounters
2025-07-17T07:05:38.5673860Z         another convolution layer. There's no point in propagating that
2025-07-17T07:05:38.5673990Z         permutation to an earlier layer, as most layers are quite agnostic to
2025-07-17T07:05:38.5674040Z         ``memory_format``.
2025-07-17T07:05:38.5674050Z 
2025-07-17T07:05:38.5674190Z         This claim might change when PyTorch supports fusion of permutation, as
2025-07-17T07:05:38.5674320Z         there might have been a better spot to fuse the permutation other than
2025-07-17T07:05:38.5674400Z         immediately before a convolution.
2025-07-17T07:05:38.5674400Z 
2025-07-17T07:05:38.5674440Z     Args:
2025-07-17T07:05:38.5674580Z         module (nn.Module): ``nn.Conv3d`` & ``nn.ConvTranspose3d`` or container
2025-07-17T07:05:38.5674630Z                             ``nn.Module``
2025-07-17T07:05:38.5674730Z         memory_format: user specified ``memory_format``,
2025-07-17T07:05:38.5674840Z             e.g. ``torch.channels_last`` or ``torch.contiguous_format``
2025-07-17T07:05:38.5674840Z 
2025-07-17T07:05:38.5674890Z     Returns:
2025-07-17T07:05:38.5674970Z         The original module with updated ``nn.Conv3d``
2025-07-17T07:05:38.5674980Z 
2025-07-17T07:05:38.5675020Z     Example:
2025-07-17T07:05:38.5675100Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-07-17T07:05:38.5675200Z         >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG)
2025-07-17T07:05:38.5675260Z         >>> input = torch.randint(
2025-07-17T07:05:38.5675360Z         ...     1, 10, (2, 8, 4, 4, 4), dtype=torch.float16, device="cuda"
2025-07-17T07:05:38.5675410Z         ... )
2025-07-17T07:05:38.5675460Z         >>> model = nn.Sequential(
2025-07-17T07:05:38.5675530Z         >>>     nn.Conv3d(8, 4, 3)).cuda().half()
2025-07-17T07:05:38.5675590Z         >>> # This is identical to:
2025-07-17T07:05:38.5675750Z         >>> # nn.utils.convert_conv3d_weight_memory_format(model, torch.channels_last_3d)
2025-07-17T07:05:38.5675850Z         >>> model = nn.utils.convert_conv3d_weight_memory_format(
2025-07-17T07:05:38.5675920Z         ...     model, torch.channels_last_3d
2025-07-17T07:05:38.5675960Z         ... )
2025-07-17T07:05:38.5676010Z         >>> out = model(input)
2025-07-17T07:05:38.5676050Z     
2025-07-17T07:05:38.5676210Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.5676210Z 
2025-07-17T07:05:38.5676640Z msg = Cannot scrape callname=ln_structured in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py line=979.
2025-07-17T07:05:38.5676800Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.5677010Z Prune tensor by removing channels with the lowest L\ ``n``-norm along the specified dimension.
2025-07-17T07:05:38.5677010Z 
2025-07-17T07:05:38.5677150Z     Prunes tensor corresponding to parameter called ``name`` in ``module``
2025-07-17T07:05:38.5677280Z     by removing the specified ``amount`` of (currently unpruned) channels
2025-07-17T07:05:38.5677390Z     along the specified ``dim`` with the lowest L\ ``n``-norm.
2025-07-17T07:05:38.5677510Z     Modifies module in place (and also return the modified module)
2025-07-17T07:05:38.5677550Z     by:
2025-07-17T07:05:38.5677550Z 
2025-07-17T07:05:38.5677750Z     1) adding a named buffer called ``name+'_mask'`` corresponding to the
2025-07-17T07:05:38.5677950Z        binary mask applied to the parameter ``name`` by the pruning method.
2025-07-17T07:05:38.5678080Z     2) replacing the parameter ``name`` by its pruned version, while the
2025-07-17T07:05:38.5678200Z        original (unpruned) parameter is stored in a new parameter named
2025-07-17T07:05:38.5678250Z        ``name+'_orig'``.
2025-07-17T07:05:38.5678260Z 
2025-07-17T07:05:38.5678300Z     Args:
2025-07-17T07:05:38.5678410Z         module (nn.Module): module containing the tensor to prune
2025-07-17T07:05:38.5678520Z         name (str): parameter name within ``module`` on which pruning
2025-07-17T07:05:38.5678570Z                 will act.
2025-07-17T07:05:38.5678670Z         amount (int or float): quantity of parameters to prune.
2025-07-17T07:05:38.5678780Z             If ``float``, should be between 0.0 and 1.0 and represent the
2025-07-17T07:05:38.5678900Z             fraction of parameters to prune. If ``int``, it represents the
2025-07-17T07:05:38.5678980Z             absolute number of parameters to prune.
2025-07-17T07:05:38.5679110Z         n (int, float, inf, -inf, 'fro', 'nuc'): See documentation of valid
2025-07-17T07:05:38.5679210Z             entries for argument ``p`` in :func:`torch.norm`.
2025-07-17T07:05:38.5679330Z         dim (int): index of the dim along which we define channels to prune.
2025-07-17T07:05:38.5679470Z         importance_scores (torch.Tensor): tensor of importance scores (of same
2025-07-17T07:05:38.5679590Z             shape as module parameter) used to compute mask for pruning.
2025-07-17T07:05:38.5679730Z             The values in this tensor indicate the importance of the corresponding
2025-07-17T07:05:38.5679800Z             elements in the parameter being pruned.
2025-07-17T07:05:38.5679950Z             If unspecified or None, the module parameter will be used in its place.
2025-07-17T07:05:38.5679950Z 
2025-07-17T07:05:38.5679990Z     Returns:
2025-07-17T07:05:38.5680130Z         module (nn.Module): modified (i.e. pruned) version of the input module
2025-07-17T07:05:38.5680130Z 
2025-07-17T07:05:38.5680170Z     Examples:
2025-07-17T07:05:38.5680250Z         >>> from torch.nn.utils import prune
2025-07-17T07:05:38.5680310Z         >>> m = prune.ln_structured(
2025-07-17T07:05:38.5680420Z         ...     nn.Conv2d(5, 3, 2), "weight", amount=0.3, dim=1, n=float("-inf")
2025-07-17T07:05:38.5680460Z         ... )
2025-07-17T07:05:38.5680510Z     
2025-07-17T07:05:38.5680660Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.5680660Z 
2025-07-17T07:05:38.5681050Z msg = Cannot scrape callname=global_unstructured in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py line=1026.
2025-07-17T07:05:38.5681210Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.5681210Z 
2025-07-17T07:05:38.5681460Z Globally prunes tensors corresponding to all parameters in ``parameters`` by applying the specified ``pruning_method``.
2025-07-17T07:05:38.5681470Z 
2025-07-17T07:05:38.5681550Z Modifies modules in place by:
2025-07-17T07:05:38.5681560Z 
2025-07-17T07:05:38.5681690Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the
2025-07-17T07:05:38.5681820Z    binary mask applied to the parameter ``name`` by the pruning method.
2025-07-17T07:05:38.5681980Z 2) replacing the parameter ``name`` by its pruned version, while the
2025-07-17T07:05:38.5682100Z    original (unpruned) parameter is stored in a new parameter named
2025-07-17T07:05:38.5682150Z    ``name+'_orig'``.
2025-07-17T07:05:38.5682160Z 
2025-07-17T07:05:38.5682200Z Args:
2025-07-17T07:05:38.5682320Z     parameters (Iterable of (module, name) tuples): parameters of
2025-07-17T07:05:38.5682440Z         the model to prune in a global fashion, i.e. by aggregating all
2025-07-17T07:05:38.5682560Z         weights prior to deciding which ones to prune. module must be of
2025-07-17T07:05:38.5682710Z         type :class:`nn.Module`, and name must be a string.
2025-07-17T07:05:38.5682900Z     pruning_method (function): a valid pruning function from this module,
2025-07-17T07:05:38.5683010Z         or a custom one implemented by the user that satisfies the
2025-07-17T07:05:38.5683150Z         implementation guidelines and has ``PRUNING_TYPE='unstructured'``.
2025-07-17T07:05:38.5683290Z     importance_scores (dict): a dictionary mapping (module, name) tuples to
2025-07-17T07:05:38.5683420Z         the corresponding parameter's importance scores tensor. The tensor
2025-07-17T07:05:38.5683550Z         should be the same shape as the parameter, and is used for computing
2025-07-17T07:05:38.5683600Z         mask for pruning.
2025-07-17T07:05:38.5683730Z         If unspecified or None, the parameter will be used in place of its
2025-07-17T07:05:38.5683780Z         importance scores.
2025-07-17T07:05:38.5683850Z     kwargs: other keyword arguments such as:
2025-07-17T07:05:38.5683970Z         amount (int or float): quantity of parameters to prune across the
2025-07-17T07:05:38.5684020Z         specified parameters.
2025-07-17T07:05:38.5684140Z         If ``float``, should be between 0.0 and 1.0 and represent the
2025-07-17T07:05:38.5684250Z         fraction of parameters to prune. If ``int``, it represents the
2025-07-17T07:05:38.5684330Z         absolute number of parameters to prune.
2025-07-17T07:05:38.5684330Z 
2025-07-17T07:05:38.5684370Z Raises:
2025-07-17T07:05:38.5684470Z     TypeError: if ``PRUNING_TYPE != 'unstructured'``
2025-07-17T07:05:38.5684470Z 
2025-07-17T07:05:38.5684510Z Note:
2025-07-17T07:05:38.5684640Z     Since global structured pruning doesn't make much sense unless the
2025-07-17T07:05:38.5684760Z     norm is normalized by the size of the parameter, we now limit the
2025-07-17T07:05:38.5684850Z     scope of global pruning to unstructured methods.
2025-07-17T07:05:38.5684850Z 
2025-07-17T07:05:38.5684900Z Examples:
2025-07-17T07:05:38.5684970Z     >>> from torch.nn.utils import prune
2025-07-17T07:05:38.5685040Z     >>> from collections import OrderedDict
2025-07-17T07:05:38.5685100Z     >>> net = nn.Sequential(
2025-07-17T07:05:38.5685150Z     ...     OrderedDict(
2025-07-17T07:05:38.5685190Z     ...         [
2025-07-17T07:05:38.5685260Z     ...             ("first", nn.Linear(10, 4)),
2025-07-17T07:05:38.5685320Z     ...             ("second", nn.Linear(4, 1)),
2025-07-17T07:05:38.5685370Z     ...         ]
2025-07-17T07:05:38.5685410Z     ...     )
2025-07-17T07:05:38.5685460Z     ... )
2025-07-17T07:05:38.5685520Z     >>> parameters_to_prune = (
2025-07-17T07:05:38.5685580Z     ...     (net.first, "weight"),
2025-07-17T07:05:38.5685640Z     ...     (net.second, "weight"),
2025-07-17T07:05:38.5685680Z     ... )
2025-07-17T07:05:38.5685740Z     >>> prune.global_unstructured(
2025-07-17T07:05:38.5685800Z     ...     parameters_to_prune,
2025-07-17T07:05:38.5685870Z     ...     pruning_method=prune.L1Unstructured,
2025-07-17T07:05:38.5685920Z     ...     amount=10,
2025-07-17T07:05:38.5685960Z     ... )
2025-07-17T07:05:38.5686100Z     >>> print(sum(torch.nn.utils.parameters_to_vector(net.buffers()) == 0))
2025-07-17T07:05:38.5686170Z     tensor(10)
2025-07-17T07:05:38.5686180Z 
2025-07-17T07:05:38.5686180Z 
2025-07-17T07:05:38.5686330Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.6007630Z 
2025-07-17T07:05:38.6008230Z msg = Cannot scrape callname=custom_from_mask in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py line=1149.
2025-07-17T07:05:38.6008450Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.6008700Z Prune tensor corresponding to parameter called ``name`` in ``module`` by applying the pre-computed mask in ``mask``.
2025-07-17T07:05:38.6008700Z 
2025-07-17T07:05:38.6008840Z     Modifies module in place (and also return the modified module) by:
2025-07-17T07:05:38.6008840Z 
2025-07-17T07:05:38.6009170Z     1) adding a named buffer called ``name+'_mask'`` corresponding to the
2025-07-17T07:05:38.6009400Z        binary mask applied to the parameter ``name`` by the pruning method.
2025-07-17T07:05:38.6009540Z     2) replacing the parameter ``name`` by its pruned version, while the
2025-07-17T07:05:38.6009670Z        original (unpruned) parameter is stored in a new parameter named
2025-07-17T07:05:38.6009730Z        ``name+'_orig'``.
2025-07-17T07:05:38.6009730Z 
2025-07-17T07:05:38.6009770Z     Args:
2025-07-17T07:05:38.6009890Z         module (nn.Module): module containing the tensor to prune
2025-07-17T07:05:38.6010010Z         name (str): parameter name within ``module`` on which pruning
2025-07-17T07:05:38.6010060Z             will act.
2025-07-17T07:05:38.6010170Z         mask (Tensor): binary mask to be applied to the parameter.
2025-07-17T07:05:38.6010170Z 
2025-07-17T07:05:38.6010220Z     Returns:
2025-07-17T07:05:38.6010360Z         module (nn.Module): modified (i.e. pruned) version of the input module
2025-07-17T07:05:38.6010360Z 
2025-07-17T07:05:38.6010410Z     Examples:
2025-07-17T07:05:38.6010490Z         >>> from torch.nn.utils import prune
2025-07-17T07:05:38.6010550Z         >>> m = prune.custom_from_mask(
2025-07-17T07:05:38.6010670Z         ...     nn.Linear(5, 3), name="bias", mask=torch.tensor([0, 1, 0])
2025-07-17T07:05:38.6010710Z         ... )
2025-07-17T07:05:38.6010780Z         >>> print(m.bias_mask)
2025-07-17T07:05:38.6010830Z         tensor([0., 1., 0.])
2025-07-17T07:05:38.6010830Z 
2025-07-17T07:05:38.6010870Z     
2025-07-17T07:05:38.6011030Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.6011030Z 
2025-07-17T07:05:38.6011440Z msg = Cannot scrape callname=pad_packed_sequence in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/rnn.py line=342.
2025-07-17T07:05:38.6011600Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.6011680Z Pad a packed batch of variable length sequences.
2025-07-17T07:05:38.6011680Z 
2025-07-17T07:05:38.6011790Z     It is an inverse operation to :func:`pack_padded_sequence`.
2025-07-17T07:05:38.6011800Z 
2025-07-17T07:05:38.6011970Z     The returned Tensor's data will be of size ``T x B x *`` (if :attr:`batch_first` is ``False``)
2025-07-17T07:05:38.6012120Z     or ``B x T x *`` (if :attr:`batch_first` is ``True``) , where ``T`` is the length of the longest
2025-07-17T07:05:38.6012190Z     sequence and ``B`` is the batch size.
2025-07-17T07:05:38.6012190Z 
2025-07-17T07:05:38.6012240Z     Example:
2025-07-17T07:05:38.6012380Z         >>> from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
2025-07-17T07:05:38.6012480Z         >>> seq = torch.tensor([[1, 2, 0], [3, 0, 0], [4, 5, 6]])
2025-07-17T07:05:38.6012530Z         >>> lens = [2, 1, 3]
2025-07-17T07:05:38.6012600Z         >>> packed = pack_padded_sequence(
2025-07-17T07:05:38.6012690Z         ...     seq, lens, batch_first=True, enforce_sorted=False
2025-07-17T07:05:38.6012730Z         ... )
2025-07-17T07:05:38.6012780Z         >>> packed
2025-07-17T07:05:38.6012960Z         PackedSequence(data=tensor([4, 1, 3, 5, 2, 6]), batch_sizes=tensor([3, 2, 1]),
2025-07-17T07:05:38.6013100Z                        sorted_indices=tensor([2, 0, 1]), unsorted_indices=tensor([1, 2, 0]))
2025-07-17T07:05:38.6013290Z         >>> seq_unpacked, lens_unpacked = pad_packed_sequence(packed, batch_first=True)
2025-07-17T07:05:38.6013340Z         >>> seq_unpacked
2025-07-17T07:05:38.6013390Z         tensor([[1, 2, 0],
2025-07-17T07:05:38.6013440Z                 [3, 0, 0],
2025-07-17T07:05:38.6013480Z                 [4, 5, 6]])
2025-07-17T07:05:38.6013530Z         >>> lens_unpacked
2025-07-17T07:05:38.6013580Z         tensor([2, 1, 3])
2025-07-17T07:05:38.6013580Z 
2025-07-17T07:05:38.6013640Z     .. note::
2025-07-17T07:05:38.6013730Z         :attr:`total_length` is useful to implement the
2025-07-17T07:05:38.6013860Z         ``pack sequence -> recurrent network -> unpack sequence`` pattern in a
2025-07-17T07:05:38.6014090Z         :class:`~torch.nn.Module` wrapped in :class:`~torch.nn.DataParallel`.
2025-07-17T07:05:38.6014290Z         See :ref:`this FAQ section <pack-rnn-unpack-with-data-parallelism>` for
2025-07-17T07:05:38.6014350Z         details.
2025-07-17T07:05:38.6014350Z 
2025-07-17T07:05:38.6014390Z     Args:
2025-07-17T07:05:38.6014470Z         sequence (PackedSequence): batch to pad
2025-07-17T07:05:38.6014610Z         batch_first (bool, optional): if ``True``, the output will be in ``B x T x *``
2025-07-17T07:05:38.6014680Z             format, ``T x B x *`` otherwise.
2025-07-17T07:05:38.6014800Z         padding_value (float, optional): values for padded elements.
2025-07-17T07:05:38.6014940Z         total_length (int, optional): if not ``None``, the output will be padded to
2025-07-17T07:05:38.6015090Z             have length :attr:`total_length`. This method will throw :class:`ValueError`
2025-07-17T07:05:38.6015200Z             if :attr:`total_length` is less than the max sequence length in
2025-07-17T07:05:38.6015260Z             :attr:`sequence`.
2025-07-17T07:05:38.6015260Z 
2025-07-17T07:05:38.6015310Z     Returns:
2025-07-17T07:05:38.6015430Z         Tuple of Tensor containing the padded sequence, and a Tensor
2025-07-17T07:05:38.6015550Z         containing the list of lengths of each sequence in the batch.
2025-07-17T07:05:38.6015690Z         Batch elements will be re-ordered as they were ordered originally when
2025-07-17T07:05:38.6015820Z         the batch was passed to ``pack_padded_sequence`` or ``pack_sequence``.
2025-07-17T07:05:38.6015860Z     
2025-07-17T07:05:38.6016010Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.6016010Z 
2025-07-17T07:05:38.6016390Z msg = Cannot scrape callname=Unflatten in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/flatten.py line=60.
2025-07-17T07:05:38.6016540Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.6016550Z 
2025-07-17T07:05:38.6016740Z Unflattens a tensor dim expanding it to a desired shape. For use with :class:`~nn.Sequential`.
2025-07-17T07:05:38.6016740Z 
2025-07-17T07:05:38.6016910Z * :attr:`dim` specifies the dimension of the input tensor to be unflattened, and it can
2025-07-17T07:05:38.6017050Z   be either `int` or `str` when `Tensor` or `NamedTensor` is used, respectively.
2025-07-17T07:05:38.6017050Z 
2025-07-17T07:05:38.6017240Z * :attr:`unflattened_size` is the new shape of the unflattened dimension of the tensor and it can be
2025-07-17T07:05:38.6017390Z   a `tuple` of ints or a `list` of ints or `torch.Size` for `Tensor` input;  a `NamedShape`
2025-07-17T07:05:38.6017490Z   (tuple of `(name, size)` tuples) for `NamedTensor` input.
2025-07-17T07:05:38.6017490Z 
2025-07-17T07:05:38.6017540Z Shape:
2025-07-17T07:05:38.6017670Z     - Input: :math:`(*, S_{\text{dim}}, *)`, where :math:`S_{\text{dim}}` is the size at
2025-07-17T07:05:38.6017830Z       dimension :attr:`dim` and :math:`*` means any number of dimensions including none.
2025-07-17T07:05:38.6017990Z     - Output: :math:`(*, U_1, ..., U_n, *)`, where :math:`U` = :attr:`unflattened_size` and
2025-07-17T07:05:38.6018080Z       :math:`\prod_{i=1}^n U_i = S_{\text{dim}}`.
2025-07-17T07:05:38.6018080Z 
2025-07-17T07:05:38.6018140Z Args:
2025-07-17T07:05:38.6018240Z     dim (Union[int, str]): Dimension to be unflattened
2025-07-17T07:05:38.6018450Z     unflattened_size (Union[torch.Size, Tuple, List, NamedShape]): New shape of the unflattened dimension
2025-07-17T07:05:38.6018450Z 
2025-07-17T07:05:38.6018500Z Examples:
2025-07-17T07:05:38.6018560Z     >>> input = torch.randn(2, 50)
2025-07-17T07:05:38.6018610Z     >>> # With tuple of ints
2025-07-17T07:05:38.6018670Z     >>> m = nn.Sequential(
2025-07-17T07:05:38.6018720Z     >>>     nn.Linear(50, 50),
2025-07-17T07:05:38.6018780Z     >>>     nn.Unflatten(1, (2, 5, 5))
2025-07-17T07:05:38.6018820Z     >>> )
2025-07-17T07:05:38.6018870Z     >>> output = m(input)
2025-07-17T07:05:38.6018980Z     >>> output.size()
2025-07-17T07:05:38.6019090Z     torch.Size([2, 2, 5, 5])
2025-07-17T07:05:38.6019140Z     >>> # With torch.Size
2025-07-17T07:05:38.6019190Z     >>> m = nn.Sequential(
2025-07-17T07:05:38.6019250Z     >>>     nn.Linear(50, 50),
2025-07-17T07:05:38.6019320Z     >>>     nn.Unflatten(1, torch.Size([2, 5, 5]))
2025-07-17T07:05:38.6019370Z     >>> )
2025-07-17T07:05:38.6019420Z     >>> output = m(input)
2025-07-17T07:05:38.6019470Z     >>> output.size()
2025-07-17T07:05:38.6019520Z     torch.Size([2, 2, 5, 5])
2025-07-17T07:05:38.6019580Z     >>> # With namedshape (tuple of tuples)
2025-07-17T07:05:38.6019670Z     >>> input = torch.randn(2, 50, names=("N", "features"))
2025-07-17T07:05:38.6019790Z     >>> unflatten = nn.Unflatten("features", (("C", 2), ("H", 5), ("W", 5)))
2025-07-17T07:05:38.6019860Z     >>> output = unflatten(input)
2025-07-17T07:05:38.6019900Z     >>> output.size()
2025-07-17T07:05:38.6019960Z     torch.Size([2, 2, 5, 5])
2025-07-17T07:05:38.6019960Z 
2025-07-17T07:05:38.6020110Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.6020110Z 
2025-07-17T07:05:38.6020510Z msg = Cannot scrape callname=SyncBatchNorm in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py line=601.
2025-07-17T07:05:38.6020670Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.6020770Z Applies Batch Normalization over a N-Dimensional input.
2025-07-17T07:05:38.6020780Z 
2025-07-17T07:05:38.6020980Z     The N-D input is a mini-batch of [N-2]D inputs with additional channel dimension) as described in the paper
2025-07-17T07:05:38.6021120Z     `Batch Normalization: Accelerating Deep Network Training by Reducing
2025-07-17T07:05:38.6021250Z     Internal Covariate Shift <https://arxiv.org/abs/1502.03167>`__ .
2025-07-17T07:05:38.6021250Z 
2025-07-17T07:05:38.6021310Z     .. math::
2025-07-17T07:05:38.6021310Z 
2025-07-17T07:05:38.6021440Z         y = \frac{x - \mathrm{E}[x]}{ \sqrt{\mathrm{Var}[x] + \epsilon}} * \gamma + \beta
2025-07-17T07:05:38.6021450Z 
2025-07-17T07:05:38.6021590Z     The mean and standard-deviation are calculated per-dimension over all
2025-07-17T07:05:38.6021730Z     mini-batches of the same process groups. :math:`\gamma` and :math:`\beta`
2025-07-17T07:05:38.6021880Z     are learnable parameter vectors of size `C` (where `C` is the input size).
2025-07-17T07:05:38.6021980Z     By default, the elements of :math:`\gamma` are sampled from
2025-07-17T07:05:38.6022110Z     :math:`\mathcal{U}(0, 1)` and the elements of :math:`\beta` are set to 0.
2025-07-17T07:05:38.6022260Z     The standard-deviation is calculated via the biased estimator, equivalent to
2025-07-17T07:05:38.6022330Z     `torch.var(input, unbiased=False)`.
2025-07-17T07:05:38.6022330Z 
2025-07-17T07:05:38.6022470Z     Also by default, during training this layer keeps running estimates of its
2025-07-17T07:05:38.6022600Z     computed mean and variance, which are then used for normalization during
2025-07-17T07:05:38.6022800Z     evaluation. The running estimates are kept with a default :attr:`momentum`
2025-07-17T07:05:38.6022850Z     of 0.1.
2025-07-17T07:05:38.6022850Z 
2025-07-17T07:05:38.6022990Z     If :attr:`track_running_stats` is set to ``False``, this layer then does not
2025-07-17T07:05:38.6023150Z     keep running estimates, and batch statistics are instead used during
2025-07-17T07:05:38.6023210Z     evaluation time as well.
2025-07-17T07:05:38.6023210Z 
2025-07-17T07:05:38.6023260Z     .. note::
2025-07-17T07:05:38.6023390Z         This :attr:`momentum` argument is different from one used in optimizer
2025-07-17T07:05:38.6023520Z         classes and the conventional notion of momentum. Mathematically, the
2025-07-17T07:05:38.6023600Z         update rule for running statistics here is
2025-07-17T07:05:38.6023770Z         :math:`\hat{x}_\text{new} = (1 - \text{momentum}) \times \hat{x} + \text{momentum} \times x_t`,
2025-07-17T07:05:38.6023970Z         where :math:`\hat{x}` is the estimated statistic and :math:`x_t` is the
2025-07-17T07:05:38.6024070Z         new observed value.
2025-07-17T07:05:38.6024080Z 
2025-07-17T07:05:38.6024260Z     Because the Batch Normalization is done for each channel in the ``C`` dimension, computing
2025-07-17T07:05:38.6024410Z     statistics on ``(N, +)`` slices, it's common terminology to call this Volumetric Batch
2025-07-17T07:05:38.6024510Z     Normalization or Spatio-temporal Batch Normalization.
2025-07-17T07:05:38.6024510Z 
2025-07-17T07:05:38.6024590Z     Currently :class:`SyncBatchNorm` only supports
2025-07-17T07:05:38.6024770Z     :class:`~torch.nn.DistributedDataParallel` (DDP) with single GPU per process. Use
2025-07-17T07:05:38.6024900Z     :meth:`torch.nn.SyncBatchNorm.convert_sync_batchnorm()` to convert
2025-07-17T07:05:38.6025020Z     :attr:`BatchNorm*D` layer to :class:`SyncBatchNorm` before wrapping
2025-07-17T07:05:38.6025070Z     Network with DDP.
2025-07-17T07:05:38.6025070Z 
2025-07-17T07:05:38.6025120Z     Args:
2025-07-17T07:05:38.6025220Z         num_features: :math:`C` from an expected input of size
2025-07-17T07:05:38.6025270Z             :math:`(N, C, +)`
2025-07-17T07:05:38.6025390Z         eps: a value added to the denominator for numerical stability.
2025-07-17T07:05:38.6025450Z             Default: ``1e-5``
2025-07-17T07:05:38.6025570Z         momentum: the value used for the running_mean and running_var
2025-07-17T07:05:38.6025690Z             computation. Can be set to ``None`` for cumulative moving average
2025-07-17T07:05:38.6025760Z             (i.e. simple average). Default: 0.1
2025-07-17T07:05:38.6025890Z         affine: a boolean value that when set to ``True``, this module has
2025-07-17T07:05:38.6025980Z             learnable affine parameters. Default: ``True``
2025-07-17T07:05:38.6026110Z         track_running_stats: a boolean value that when set to ``True``, this
2025-07-17T07:05:38.6026250Z             module tracks the running mean and variance, and when set to ``False``,
2025-07-17T07:05:38.6026400Z             this module does not track such statistics, and initializes statistics
2025-07-17T07:05:38.6026520Z             buffers :attr:`running_mean` and :attr:`running_var` as ``None``.
2025-07-17T07:05:38.6026660Z             When these buffers are ``None``, this module always uses batch statistics.
2025-07-17T07:05:38.6026750Z             in both training and eval modes. Default: ``True``
2025-07-17T07:05:38.6026900Z         process_group: synchronization of stats happen within each process group
2025-07-17T07:05:38.6027030Z             individually. Default behavior is synchronization across the whole
2025-07-17T07:05:38.6027080Z             world
2025-07-17T07:05:38.6027080Z 
2025-07-17T07:05:38.6027120Z     Shape:
2025-07-17T07:05:38.6027180Z         - Input: :math:`(N, C, +)`
2025-07-17T07:05:38.6027270Z         - Output: :math:`(N, C, +)` (same shape as input)
2025-07-17T07:05:38.6027270Z 
2025-07-17T07:05:38.6027320Z     .. note::
2025-07-17T07:05:38.6027470Z         Synchronization of batchnorm statistics occurs only while training, i.e.
2025-07-17T07:05:38.6027630Z         synchronization is disabled when ``model.eval()`` is set or if
2025-07-17T07:05:38.6027720Z         ``self.training`` is otherwise ``False``.
2025-07-17T07:05:38.6027720Z 
2025-07-17T07:05:38.6027820Z     Examples::
2025-07-17T07:05:38.6027850Z 
2025-07-17T07:05:38.6027910Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:38.6027970Z         >>> # With Learnable Parameters
2025-07-17T07:05:38.6028030Z         >>> m = nn.SyncBatchNorm(100)
2025-07-17T07:05:38.6028100Z         >>> # creating process group (optional)
2025-07-17T07:05:38.6028190Z         >>> # ranks is a list of int identifying rank ids.
2025-07-17T07:05:38.6028240Z         >>> ranks = list(range(8))
2025-07-17T07:05:38.6028300Z         >>> r1, r2 = ranks[:4], ranks[4:]
2025-07-17T07:05:38.6028390Z         >>> # Note: every rank calls into new_group for every
2025-07-17T07:05:38.6028490Z         >>> # process group created, even if that rank is not
2025-07-17T07:05:38.6028640Z         >>> # part of the group.
2025-07-17T07:05:38.6028850Z         >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]]
2025-07-17T07:05:38.6028980Z         >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1]
2025-07-17T07:05:38.6029040Z         >>> # Without Learnable Parameters
2025-07-17T07:05:38.6029170Z         >>> m = nn.BatchNorm3d(100, affine=False, process_group=process_group)
2025-07-17T07:05:38.6029240Z         >>> input = torch.randn(20, 100, 35, 45, 10)
2025-07-17T07:05:38.6029300Z         >>> output = m(input)
2025-07-17T07:05:38.6029300Z 
2025-07-17T07:05:38.6029370Z         >>> # network is nn.BatchNorm layer
2025-07-17T07:05:38.6029530Z         >>> sync_bn_network = nn.SyncBatchNorm.convert_sync_batchnorm(network, process_group)
2025-07-17T07:05:38.6029630Z         >>> # only single gpu per process is currently supported
2025-07-17T07:05:38.6029770Z         >>> ddp_sync_bn_network = torch.nn.parallel.DistributedDataParallel(
2025-07-17T07:05:38.6029840Z         >>>                         sync_bn_network,
2025-07-17T07:05:38.6029930Z         >>>                         device_ids=[args.local_rank],
2025-07-17T07:05:38.6030010Z         >>>                         output_device=args.local_rank)
2025-07-17T07:05:38.6030050Z     
2025-07-17T07:05:38.6030200Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.6159680Z 
2025-07-17T07:05:38.6160280Z msg = Cannot scrape callname=SyncBatchNorm.convert_sync_batchnorm in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py line=825.
2025-07-17T07:05:38.6160470Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.6160670Z Converts all :attr:`BatchNorm*D` layers in the model to :class:`torch.nn.SyncBatchNorm` layers.
2025-07-17T07:05:38.6160670Z 
2025-07-17T07:05:38.6160720Z         Args:
2025-07-17T07:05:38.6160870Z             module (nn.Module): module containing one or more :attr:`BatchNorm*D` layers
2025-07-17T07:05:38.6161010Z             process_group (optional): process group to scope synchronization,
2025-07-17T07:05:38.6161080Z                 default is the whole world
2025-07-17T07:05:38.6161080Z 
2025-07-17T07:05:38.6161130Z         Returns:
2025-07-17T07:05:38.6161290Z             The original :attr:`module` with the converted :class:`torch.nn.SyncBatchNorm`
2025-07-17T07:05:38.6161420Z             layers. If the original :attr:`module` is a :attr:`BatchNorm*D` layer,
2025-07-17T07:05:38.6161550Z             a new :class:`torch.nn.SyncBatchNorm` layer object will be returned
2025-07-17T07:05:38.6161610Z             instead.
2025-07-17T07:05:38.6161610Z 
2025-07-17T07:05:38.6161660Z         Example::
2025-07-17T07:05:38.6161660Z 
2025-07-17T07:05:38.6161740Z             >>> # Network with nn.BatchNorm layer
2025-07-17T07:05:38.6161830Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-07-17T07:05:38.6161900Z             >>> module = torch.nn.Sequential(
2025-07-17T07:05:38.6162030Z             >>>            torch.nn.Linear(20, 100),
2025-07-17T07:05:38.6162110Z             >>>            torch.nn.BatchNorm1d(100),
2025-07-17T07:05:38.6162160Z             >>>          ).cuda()
2025-07-17T07:05:38.6162280Z             >>> # creating process group (optional)
2025-07-17T07:05:38.6162370Z             >>> # ranks is a list of int identifying rank ids.
2025-07-17T07:05:38.6162430Z             >>> ranks = list(range(8))
2025-07-17T07:05:38.6162500Z             >>> r1, r2 = ranks[:4], ranks[4:]
2025-07-17T07:05:38.6162590Z             >>> # Note: every rank calls into new_group for every
2025-07-17T07:05:38.6162690Z             >>> # process group created, even if that rank is not
2025-07-17T07:05:38.6162750Z             >>> # part of the group.
2025-07-17T07:05:38.6162820Z             >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:38.6163070Z             >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]]
2025-07-17T07:05:38.6163270Z             >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1]
2025-07-17T07:05:38.6163460Z             >>> sync_bn_module = torch.nn.SyncBatchNorm.convert_sync_batchnorm(module, process_group)
2025-07-17T07:05:38.6163460Z 
2025-07-17T07:05:38.6163510Z         
2025-07-17T07:05:38.6163660Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.6163660Z 
2025-07-17T07:05:38.6164050Z msg = Cannot scrape callname=MaxUnpool2d in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py line=406.
2025-07-17T07:05:38.6164200Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.6164290Z Computes a partial inverse of :class:`MaxPool2d`.
2025-07-17T07:05:38.6164290Z 
2025-07-17T07:05:38.6164450Z     :class:`MaxPool2d` is not fully invertible, since the non-maximal values are lost.
2025-07-17T07:05:38.6164450Z 
2025-07-17T07:05:38.6164590Z     :class:`MaxUnpool2d` takes in as input the output of :class:`MaxPool2d`
2025-07-17T07:05:38.6164730Z     including the indices of the maximal values and computes a partial inverse
2025-07-17T07:05:38.6164820Z     in which all non-maximal values are set to zero.
2025-07-17T07:05:38.6164820Z 
2025-07-17T07:05:38.6164860Z     Note:
2025-07-17T07:05:38.6165050Z         This operation may behave nondeterministically when the input indices has repeat values.
2025-07-17T07:05:38.6165280Z         See https://github.com/pytorch/pytorch/issues/80827 and :doc:`/notes/randomness` for more information.
2025-07-17T07:05:38.6165280Z 
2025-07-17T07:05:38.6165420Z     .. note:: :class:`MaxPool2d` can map several input sizes to the same output
2025-07-17T07:05:38.6165530Z               sizes. Hence, the inversion process can get ambiguous.
2025-07-17T07:05:38.6165640Z               To accommodate this, you can provide the needed output size
2025-07-17T07:05:38.6165770Z               as an additional argument :attr:`output_size` in the forward call.
2025-07-17T07:05:38.6165840Z               See the Inputs and Example below.
2025-07-17T07:05:38.6165840Z 
2025-07-17T07:05:38.6165890Z     Args:
2025-07-17T07:05:38.6166000Z         kernel_size (int or tuple): Size of the max pooling window.
2025-07-17T07:05:38.6166100Z         stride (int or tuple): Stride of the max pooling window.
2025-07-17T07:05:38.6166190Z             It is set to :attr:`kernel_size` by default.
2025-07-17T07:05:38.6166300Z         padding (int or tuple): Padding that was added to the input
2025-07-17T07:05:38.6166300Z 
2025-07-17T07:05:38.6166340Z     Inputs:
2025-07-17T07:05:38.6166410Z         - `input`: the input Tensor to invert
2025-07-17T07:05:38.6166540Z         - `indices`: the indices given out by :class:`~torch.nn.MaxPool2d`
2025-07-17T07:05:38.6166630Z         - `output_size` (optional): the targeted output size
2025-07-17T07:05:38.6166630Z 
2025-07-17T07:05:38.6166670Z     Shape:
2025-07-17T07:05:38.6166790Z         - Input: :math:`(N, C, H_{in}, W_{in})` or :math:`(C, H_{in}, W_{in})`.
2025-07-17T07:05:38.6166950Z         - Output: :math:`(N, C, H_{out}, W_{out})` or :math:`(C, H_{out}, W_{out})`, where
2025-07-17T07:05:38.6166960Z 
2025-07-17T07:05:38.6167010Z           .. math::
2025-07-17T07:05:38.6167190Z             H_{out} = (H_{in} - 1) \times \text{stride[0]} - 2 \times \text{padding[0]} + \text{kernel\_size[0]}
2025-07-17T07:05:38.6167200Z 
2025-07-17T07:05:38.6167250Z           .. math::
2025-07-17T07:05:38.6167400Z             W_{out} = (W_{in} - 1) \times \text{stride[1]} - 2 \times \text{padding[1]} + \text{kernel\_size[1]}
2025-07-17T07:05:38.6167400Z 
2025-07-17T07:05:38.6167510Z           or as given by :attr:`output_size` in the call operator
2025-07-17T07:05:38.6167510Z 
2025-07-17T07:05:38.6167550Z     Example::
2025-07-17T07:05:38.6167560Z 
2025-07-17T07:05:38.6167660Z         >>> pool = nn.MaxPool2d(2, stride=2, return_indices=True)
2025-07-17T07:05:38.6167780Z         >>> unpool = nn.MaxUnpool2d(2, stride=2)
2025-07-17T07:05:38.6167920Z         >>> input = torch.tensor([[[[ 1.,  2.,  3.,  4.],
2025-07-17T07:05:38.6167990Z                                     [ 5.,  6.,  7.,  8.],
2025-07-17T07:05:38.6168060Z                                     [ 9., 10., 11., 12.],
2025-07-17T07:05:38.6168130Z                                     [13., 14., 15., 16.]]]])
2025-07-17T07:05:38.6168190Z         >>> output, indices = pool(input)
2025-07-17T07:05:38.6168250Z         >>> unpool(output, indices)
2025-07-17T07:05:38.6168310Z         tensor([[[[  0.,   0.,   0.,   0.],
2025-07-17T07:05:38.6168360Z                   [  0.,   6.,   0.,   8.],
2025-07-17T07:05:38.6168410Z                   [  0.,   0.,   0.,   0.],
2025-07-17T07:05:38.6168470Z                   [  0.,  14.,   0.,  16.]]]])
2025-07-17T07:05:38.6168600Z         >>> # Now using output_size to resolve an ambiguous size for the inverse
2025-07-17T07:05:38.6168680Z         >>> input = torch.tensor([[[[ 1.,  2.,  3.,  4.,  5.],
2025-07-17T07:05:38.6168750Z                                     [ 6.,  7.,  8.,  9., 10.],
2025-07-17T07:05:38.6168820Z                                     [11., 12., 13., 14., 15.],
2025-07-17T07:05:38.6168900Z                                     [16., 17., 18., 19., 20.]]]])
2025-07-17T07:05:38.6168960Z         >>> output, indices = pool(input)
2025-07-17T07:05:38.6169060Z         >>> # This call will not work without specifying output_size
2025-07-17T07:05:38.6169160Z         >>> unpool(output, indices, output_size=input.size())
2025-07-17T07:05:38.6169220Z         tensor([[[[ 0.,  0.,  0.,  0.,  0.],
2025-07-17T07:05:38.6169280Z                   [ 0.,  7.,  0.,  9.,  0.],
2025-07-17T07:05:38.6169330Z                   [ 0.,  0.,  0.,  0.,  0.],
2025-07-17T07:05:38.6169390Z                   [ 0., 17.,  0., 19.,  0.]]]])
2025-07-17T07:05:38.6169390Z 
2025-07-17T07:05:38.6169390Z 
2025-07-17T07:05:38.6169430Z     
2025-07-17T07:05:38.6169580Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.6169590Z 
2025-07-17T07:05:38.6170020Z msg = Cannot scrape callname=TripletMarginWithDistanceLoss in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py line=1718.
2025-07-17T07:05:38.6170180Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.6170300Z Creates a criterion that measures the triplet loss given input
2025-07-17T07:05:38.6170420Z     tensors :math:`a`, :math:`p`, and :math:`n` (representing anchor,
2025-07-17T07:05:38.6170550Z     positive, and negative examples, respectively), and a nonnegative,
2025-07-17T07:05:38.6170700Z     real-valued function ("distance function") used to compute the relationship
2025-07-17T07:05:38.6170830Z     between the anchor and positive example ("positive distance") and the
2025-07-17T07:05:38.6170920Z     anchor and negative example ("negative distance").
2025-07-17T07:05:38.6170930Z 
2025-07-17T07:05:38.6171050Z     The unreduced loss (i.e., with :attr:`reduction` set to ``'none'``)
2025-07-17T07:05:38.6171130Z     can be described as:
2025-07-17T07:05:38.6171130Z 
2025-07-17T07:05:38.6171180Z     .. math::
2025-07-17T07:05:38.6171270Z         \ell(a, p, n) = L = \{l_1,\dots,l_N\}^\top, \quad
2025-07-17T07:05:38.6171360Z         l_i = \max \{d(a_i, p_i) - d(a_i, n_i) + {\rm margin}, 0\}
2025-07-17T07:05:38.6171420Z 
2025-07-17T07:05:38.6171570Z     where :math:`N` is the batch size; :math:`d` is a nonnegative, real-valued function
2025-07-17T07:05:38.6171750Z     quantifying the closeness of two tensors, referred to as the :attr:`distance_function`;
2025-07-17T07:05:38.6171980Z     and :math:`margin` is a nonnegative margin representing the minimum difference
2025-07-17T07:05:38.6177390Z     between the positive and negative distances that is required for the loss to
2025-07-17T07:05:38.6177550Z     be 0.  The input tensors have :math:`N` elements each and can be of any shape
2025-07-17T07:05:38.6177620Z     that the distance function can handle.
2025-07-17T07:05:38.6177730Z 
2025-07-17T07:05:38.6177860Z     If :attr:`reduction` is not ``'none'``
2025-07-17T07:05:38.6177920Z     (default ``'mean'``), then:
2025-07-17T07:05:38.6177920Z 
2025-07-17T07:05:38.6177970Z     .. math::
2025-07-17T07:05:38.6178010Z         \ell(x, y) =
2025-07-17T07:05:38.6178070Z         \begin{cases}
2025-07-17T07:05:38.6178190Z             \operatorname{mean}(L), &  \text{if reduction} = \text{`mean';}\\
2025-07-17T07:05:38.6178310Z             \operatorname{sum}(L),  &  \text{if reduction} = \text{`sum'.}
2025-07-17T07:05:38.6178350Z         \end{cases}
2025-07-17T07:05:38.6178350Z 
2025-07-17T07:05:38.6178500Z     See also :class:`~torch.nn.TripletMarginLoss`, which computes the triplet
2025-07-17T07:05:38.6178650Z     loss for input tensors using the :math:`l_p` distance as the distance function.
2025-07-17T07:05:38.6178650Z 
2025-07-17T07:05:38.6178700Z     Args:
2025-07-17T07:05:38.6178860Z         distance_function (Callable, optional): A nonnegative, real-valued function that
2025-07-17T07:05:38.6178980Z             quantifies the closeness of two tensors. If not specified,
2025-07-17T07:05:38.6179080Z             `nn.PairwiseDistance` will be used.  Default: ``None``
2025-07-17T07:05:38.6179250Z         margin (float, optional): A nonnegative margin representing the minimum difference
2025-07-17T07:05:38.6179410Z             between the positive and negative distances required for the loss to be 0. Larger
2025-07-17T07:05:38.6179580Z             margins penalize cases where the negative examples are not distant enough from the
2025-07-17T07:05:38.6179680Z             anchors, relative to the positives. Default: :math:`1`.
2025-07-17T07:05:38.6179850Z         swap (bool, optional): Whether to use the distance swap described in the paper
2025-07-17T07:05:38.6180010Z             `Learning shallow convolutional feature descriptors with triplet losses` by
2025-07-17T07:05:38.6180150Z             V. Balntas, E. Riba et al. If True, and if the positive example is closer to the
2025-07-17T07:05:38.6180310Z             negative example than the anchor is, swaps the positive example and the anchor in
2025-07-17T07:05:38.6180400Z             the loss computation. Default: ``False``.
2025-07-17T07:05:38.6180570Z         reduction (str, optional): Specifies the (optional) reduction to apply to the output:
2025-07-17T07:05:38.6180680Z             ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied,
2025-07-17T07:05:38.6180800Z             ``'mean'``: the sum of the output will be divided by the number of
2025-07-17T07:05:38.6180940Z             elements in the output, ``'sum'``: the output will be summed. Default: ``'mean'``
2025-07-17T07:05:38.6180940Z 
2025-07-17T07:05:38.6180940Z 
2025-07-17T07:05:38.6180990Z     Shape:
2025-07-17T07:05:38.6181140Z         - Input: :math:`(N, *)` where :math:`*` represents any number of additional dimensions
2025-07-17T07:05:38.6181220Z           as supported by the distance function.
2025-07-17T07:05:38.6181370Z         - Output: A Tensor of shape :math:`(N)` if :attr:`reduction` is ``'none'``, or a scalar
2025-07-17T07:05:38.6181470Z           otherwise.
2025-07-17T07:05:38.6181480Z 
2025-07-17T07:05:38.6181520Z     Examples:
2025-07-17T07:05:38.6181520Z 
2025-07-17T07:05:38.6181590Z     >>> # Initialize embeddings
2025-07-17T07:05:38.6181670Z     >>> embedding = nn.Embedding(1000, 128)
2025-07-17T07:05:38.6181750Z     >>> anchor_ids = torch.randint(0, 1000, (1,))
2025-07-17T07:05:38.6181820Z     >>> positive_ids = torch.randint(0, 1000, (1,))
2025-07-17T07:05:38.6181900Z     >>> negative_ids = torch.randint(0, 1000, (1,))
2025-07-17T07:05:38.6181960Z     >>> anchor = embedding(anchor_ids)
2025-07-17T07:05:38.6182030Z     >>> positive = embedding(positive_ids)
2025-07-17T07:05:38.6182090Z     >>> negative = embedding(negative_ids)
2025-07-17T07:05:38.6182130Z     >>>
2025-07-17T07:05:38.6182190Z     >>> # Built-in Distance Function
2025-07-17T07:05:38.6182240Z     >>> triplet_loss = \
2025-07-17T07:05:38.6182480Z     >>>     nn.TripletMarginWithDistanceLoss(distance_function=nn.PairwiseDistance())
2025-07-17T07:05:38.6182660Z     >>> output = triplet_loss(anchor, positive, negative)
2025-07-17T07:05:38.6182720Z     >>> output.backward()
2025-07-17T07:05:38.6182760Z     >>>
2025-07-17T07:05:38.6182820Z     >>> # Custom Distance Function
2025-07-17T07:05:38.6182880Z     >>> def l_infinity(x1, x2):
2025-07-17T07:05:38.6182980Z     >>>     return torch.max(torch.abs(x1 - x2), dim=1).values
2025-07-17T07:05:38.6183020Z     >>>
2025-07-17T07:05:38.6183130Z     >>> # xdoctest: +SKIP("FIXME: Would call backwards a second time")
2025-07-17T07:05:38.6183180Z     >>> triplet_loss = (
2025-07-17T07:05:38.6183350Z     >>>     nn.TripletMarginWithDistanceLoss(distance_function=l_infinity, margin=1.5))
2025-07-17T07:05:38.6183440Z     >>> output = triplet_loss(anchor, positive, negative)
2025-07-17T07:05:38.6183500Z     >>> output.backward()
2025-07-17T07:05:38.6183540Z     >>>
2025-07-17T07:05:38.6183610Z     >>> # Custom Distance Function (Lambda)
2025-07-17T07:05:38.6183660Z     >>> triplet_loss = (
2025-07-17T07:05:38.6183740Z     >>>     nn.TripletMarginWithDistanceLoss(
2025-07-17T07:05:38.6183880Z     >>>         distance_function=lambda x, y: 1.0 - F.cosine_similarity(x, y)))
2025-07-17T07:05:38.6183970Z     >>> output = triplet_loss(anchor, positive, negative)
2025-07-17T07:05:38.6184030Z     >>> output.backward()
2025-07-17T07:05:38.6184030Z 
2025-07-17T07:05:38.6184080Z     Reference:
2025-07-17T07:05:38.6184260Z         V. Balntas, et al.: Learning shallow convolutional feature descriptors with triplet losses:
2025-07-17T07:05:38.6184390Z         https://bmva-archive.org.uk/bmvc/2016/papers/paper119/index.html
2025-07-17T07:05:38.6184440Z     
2025-07-17T07:05:38.6184590Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 17))
2025-07-17T07:05:38.7511890Z 
2025-07-17T07:05:38.7512470Z msg = Cannot scrape callname=CTCLoss in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py line=1852.
2025-07-17T07:05:38.7513120Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.7513450Z The Connectionist Temporal Classification loss.
2025-07-17T07:05:38.7513610Z 
2025-07-17T07:05:38.7513850Z     Calculates loss between a continuous (unsegmented) time series and a target sequence. CTCLoss sums over the
2025-07-17T07:05:38.7514370Z     probability of possible alignments of input to target, producing a loss value which is differentiable
2025-07-17T07:05:38.7514860Z     with respect to each input node. The alignment of input to target is assumed to be "many-to-one", which
2025-07-17T07:05:38.7515320Z     limits the length of the target sequence such that it must be :math:`\leq` the input length.
2025-07-17T07:05:38.7515570Z 
2025-07-17T07:05:38.7515620Z     Args:
2025-07-17T07:05:38.7515800Z         blank (int, optional): blank label. Default :math:`0`.
2025-07-17T07:05:38.7516110Z         reduction (str, optional): Specifies the reduction to apply to the output:
2025-07-17T07:05:38.7516660Z             ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied,
2025-07-17T07:05:38.7516970Z             ``'mean'``: the output losses will be divided by the target lengths and
2025-07-17T07:05:38.7517440Z             then the mean over the batch is taken, ``'sum'``: the output losses will be summed.
2025-07-17T07:05:38.7517710Z             Default: ``'mean'``
2025-07-17T07:05:38.7517890Z         zero_infinity (bool, optional):
2025-07-17T07:05:38.7518140Z             Whether to zero infinite losses and the associated gradients.
2025-07-17T07:05:38.7518390Z             Default: ``False``
2025-07-17T07:05:38.7518610Z             Infinite losses mainly occur when the inputs are too short
2025-07-17T07:05:38.7518850Z             to be aligned to the targets.
2025-07-17T07:05:38.7518980Z 
2025-07-17T07:05:38.7519030Z     Shape:
2025-07-17T07:05:38.7519460Z         - Log_probs: Tensor of size :math:`(T, N, C)` or :math:`(T, C)`,
2025-07-17T07:05:38.7519870Z           where :math:`T = \text{input length}`,
2025-07-17T07:05:38.7520080Z           :math:`N = \text{batch size}`, and
2025-07-17T07:05:38.7520300Z           :math:`C = \text{number of classes (including blank)}`.
2025-07-17T07:05:38.7520600Z           The logarithmized probabilities of the outputs (e.g. obtained with
2025-07-17T07:05:38.7520880Z           :func:`torch.nn.functional.log_softmax`).
2025-07-17T07:05:38.7521110Z         - Targets: Tensor of size :math:`(N, S)` or
2025-07-17T07:05:38.7521350Z           :math:`(\operatorname{sum}(\text{target\_lengths}))`,
2025-07-17T07:05:38.7521590Z           where :math:`N = \text{batch size}` and
2025-07-17T07:05:38.7521830Z           :math:`S = \text{max target length, if shape is } (N, S)`.
2025-07-17T07:05:38.7522110Z           It represents the target sequences. Each element in the target
2025-07-17T07:05:38.7522440Z           sequence is a class index. And the target index cannot be blank (default=0).
2025-07-17T07:05:38.7522740Z           In the :math:`(N, S)` form, targets are padded to the
2025-07-17T07:05:38.7522990Z           length of the longest sequence, and stacked.
2025-07-17T07:05:38.7523260Z           In the :math:`(\operatorname{sum}(\text{target\_lengths}))` form,
2025-07-17T07:05:38.7523530Z           the targets are assumed to be un-padded and
2025-07-17T07:05:38.7523740Z           concatenated within 1 dimension.
2025-07-17T07:05:38.7524000Z         - Input_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`,
2025-07-17T07:05:38.7524320Z           where :math:`N = \text{batch size}`. It represents the lengths of the
2025-07-17T07:05:38.7524640Z           inputs (must each be :math:`\leq T`). And the lengths are specified
2025-07-17T07:05:38.7524970Z           for each sequence to achieve masking under the assumption that sequences
2025-07-17T07:05:38.7525240Z           are padded to equal lengths.
2025-07-17T07:05:38.7525500Z         - Target_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`,
2025-07-17T07:05:38.7525830Z           where :math:`N = \text{batch size}`. It represents lengths of the targets.
2025-07-17T07:05:38.7526170Z           Lengths are specified for each sequence to achieve masking under the
2025-07-17T07:05:38.7526510Z           assumption that sequences are padded to equal lengths. If target shape is
2025-07-17T07:05:38.7526840Z           :math:`(N,S)`, target_lengths are effectively the stop index
2025-07-17T07:05:38.7527170Z           :math:`s_n` for each target sequence, such that ``target_n = targets[n,0:s_n]`` for
2025-07-17T07:05:38.7527500Z           each target in a batch. Lengths must each be :math:`\leq S`
2025-07-17T07:05:38.7527810Z           If the targets are given as a 1d tensor that is the concatenation of individual
2025-07-17T07:05:38.7528170Z           targets, the target_lengths must add up to the total length of the tensor.
2025-07-17T07:05:38.7528510Z         - Output: scalar if :attr:`reduction` is ``'mean'`` (default) or
2025-07-17T07:05:38.7528890Z           ``'sum'``. If :attr:`reduction` is ``'none'``, then :math:`(N)` if input is batched or
2025-07-17T07:05:38.7529230Z           :math:`()` if input is unbatched, where :math:`N = \text{batch size}`.
2025-07-17T07:05:38.7529410Z 
2025-07-17T07:05:38.7529460Z     Examples:
2025-07-17T07:05:38.7529560Z 
2025-07-17T07:05:38.7529630Z         >>> # Target are to be padded
2025-07-17T07:05:38.7529820Z         >>> T = 50  # Input sequence length
2025-07-17T07:05:38.7530030Z         >>> C = 20  # Number of classes (including blank)
2025-07-17T07:05:38.7530230Z         >>> N = 16  # Batch size
2025-07-17T07:05:38.7530490Z         >>> S = 30  # Target sequence length of longest target in batch (padding length)
2025-07-17T07:05:38.7530800Z         >>> S_min = 10  # Minimum target length, for demonstration purposes
2025-07-17T07:05:38.7531020Z         >>>
2025-07-17T07:05:38.7531210Z         >>> # Initialize random batch of input vectors, for *size = (T,N,C)
2025-07-17T07:05:38.7531590Z         >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_()
2025-07-17T07:05:38.7531900Z         >>>
2025-07-17T07:05:38.7532090Z         >>> # Initialize random batch of targets (0 = blank, 1:C = classes)
2025-07-17T07:05:38.7532400Z         >>> target = torch.randint(low=1, high=C, size=(N, S), dtype=torch.long)
2025-07-17T07:05:38.7532640Z         >>>
2025-07-17T07:05:38.7532840Z         >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long)
2025-07-17T07:05:38.7533100Z         >>> target_lengths = torch.randint(
2025-07-17T07:05:38.7533290Z         ...     low=S_min,
2025-07-17T07:05:38.7533440Z         ...     high=S,
2025-07-17T07:05:38.7533580Z         ...     size=(N,),
2025-07-17T07:05:38.7533730Z         ...     dtype=torch.long,
2025-07-17T07:05:38.7533890Z         ... )
2025-07-17T07:05:38.7534010Z         >>> ctc_loss = nn.CTCLoss()
2025-07-17T07:05:38.7534240Z         >>> loss = ctc_loss(input, target, input_lengths, target_lengths)
2025-07-17T07:05:38.7534480Z         >>> loss.backward()
2025-07-17T07:05:38.7534630Z         >>>
2025-07-17T07:05:38.7534730Z         >>>
2025-07-17T07:05:38.7534860Z         >>> # Target are to be un-padded
2025-07-17T07:05:38.7535050Z         >>> T = 50  # Input sequence length
2025-07-17T07:05:38.7535260Z         >>> C = 20  # Number of classes (including blank)
2025-07-17T07:05:38.7535460Z         >>> N = 16  # Batch size
2025-07-17T07:05:38.7535610Z         >>>
2025-07-17T07:05:38.7535800Z         >>> # Initialize random batch of input vectors, for *size = (T,N,C)
2025-07-17T07:05:38.7536120Z         >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_()
2025-07-17T07:05:38.7536440Z         >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long)
2025-07-17T07:05:38.7536680Z         >>>
2025-07-17T07:05:38.7536860Z         >>> # Initialize random batch of targets (0 = blank, 1:C = classes)
2025-07-17T07:05:38.7537190Z         >>> target_lengths = torch.randint(low=1, high=T, size=(N,), dtype=torch.long)
2025-07-17T07:05:38.7537470Z         >>> target = torch.randint(
2025-07-17T07:05:38.7537640Z         ...     low=1,
2025-07-17T07:05:38.7537780Z         ...     high=C,
2025-07-17T07:05:38.7537930Z         ...     size=(sum(target_lengths),),
2025-07-17T07:05:38.7538120Z         ...     dtype=torch.long,
2025-07-17T07:05:38.7538280Z         ... )
2025-07-17T07:05:38.7538410Z         >>> ctc_loss = nn.CTCLoss()
2025-07-17T07:05:38.7538640Z         >>> loss = ctc_loss(input, target, input_lengths, target_lengths)
2025-07-17T07:05:38.7538880Z         >>> loss.backward()
2025-07-17T07:05:38.7539020Z         >>>
2025-07-17T07:05:38.7539130Z         >>>
2025-07-17T07:05:38.7539300Z         >>> # Target are to be un-padded and unbatched (effectively N=1)
2025-07-17T07:05:38.7539540Z         >>> T = 50  # Input sequence length
2025-07-17T07:05:38.7539760Z         >>> C = 20  # Number of classes (including blank)
2025-07-17T07:05:38.7539940Z         >>>
2025-07-17T07:05:38.7540140Z         >>> # Initialize random batch of input vectors, for *size = (T,C)
2025-07-17T07:05:38.7540490Z         >>> # xdoctest: +SKIP("FIXME: error in doctest")
2025-07-17T07:05:38.7540770Z         >>> input = torch.randn(T, C).log_softmax(1).detach().requires_grad_()
2025-07-17T07:05:38.7541050Z         >>> input_lengths = torch.tensor(T, dtype=torch.long)
2025-07-17T07:05:38.7541330Z         >>>
2025-07-17T07:05:38.7541510Z         >>> # Initialize random batch of targets (0 = blank, 1:C = classes)
2025-07-17T07:05:38.7541840Z         >>> target_lengths = torch.randint(low=1, high=T, size=(), dtype=torch.long)
2025-07-17T07:05:38.7542110Z         >>> target = torch.randint(
2025-07-17T07:05:38.7542270Z         ...     low=1,
2025-07-17T07:05:38.7542410Z         ...     high=C,
2025-07-17T07:05:38.7542550Z         ...     size=(target_lengths,),
2025-07-17T07:05:38.7542730Z         ...     dtype=torch.long,
2025-07-17T07:05:38.7542890Z         ... )
2025-07-17T07:05:38.7543020Z         >>> ctc_loss = nn.CTCLoss()
2025-07-17T07:05:38.7543350Z         >>> loss = ctc_loss(input, target, input_lengths, target_lengths)
2025-07-17T07:05:38.7543640Z         >>> loss.backward()
2025-07-17T07:05:38.7543740Z 
2025-07-17T07:05:38.7543790Z     Reference:
2025-07-17T07:05:38.7543980Z         A. Graves et al.: Connectionist Temporal Classification:
2025-07-17T07:05:38.7544290Z         Labelling Unsegmented Sequence Data with Recurrent Neural Networks:
2025-07-17T07:05:38.7544600Z         https://www.cs.toronto.edu/~graves/icml_2006.pdf
2025-07-17T07:05:38.7544760Z 
2025-07-17T07:05:38.7544810Z     Note:
2025-07-17T07:05:38.7545020Z         In order to use CuDNN, the following must be satisfied: :attr:`targets` must be
2025-07-17T07:05:38.7545390Z         in concatenated format, all :attr:`input_lengths` must be `T`.  :math:`blank=0`,
2025-07-17T07:05:38.7545750Z         :attr:`target_lengths` :math:`\leq 256`, the integer arguments must be of
2025-07-17T07:05:38.7546010Z         dtype :attr:`torch.int32`.
2025-07-17T07:05:38.7546130Z 
2025-07-17T07:05:38.7546290Z         The regular implementation uses the (more common in PyTorch) `torch.long` dtype.
2025-07-17T07:05:38.7546520Z 
2025-07-17T07:05:38.7546520Z 
2025-07-17T07:05:38.7546570Z     Note:
2025-07-17T07:05:38.7546790Z         In some circumstances when using the CUDA backend with CuDNN, this operator
2025-07-17T07:05:38.7547160Z         may select a nondeterministic algorithm to increase performance. If this is
2025-07-17T07:05:38.7547520Z         undesirable, you can try to make the operation deterministic (potentially at
2025-07-17T07:05:38.7547880Z         a performance cost) by setting ``torch.backends.cudnn.deterministic =
2025-07-17T07:05:38.7548130Z         True``.
2025-07-17T07:05:38.7548340Z         Please see the notes on :doc:`/notes/randomness` for background.
2025-07-17T07:05:38.7548560Z     
2025-07-17T07:05:38.7548780Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.7548990Z 
2025-07-17T07:05:38.7549420Z msg = Cannot scrape callname=Transformer.forward in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py line=186.
2025-07-17T07:05:38.7550050Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.7550360Z Take in and process masked source/target sequences.
2025-07-17T07:05:38.7550520Z 
2025-07-17T07:05:38.7550580Z         .. note::
2025-07-17T07:05:38.7550660Z 
2025-07-17T07:05:38.7550890Z             If a boolean tensor is provided for any of the [src/tgt/memory]_mask arguments, positions with a ``True`` value are
2025-07-17T07:05:38.7551270Z             not allowed to participate in the attention,
2025-07-17T07:05:38.7551550Z             which is the opposite of the definition for :attr:`attn_mask`
2025-07-17T07:05:38.7551850Z             in :func:`torch.nn.functional.scaled_dot_product_attention`.
2025-07-17T07:05:38.7552030Z 
2025-07-17T07:05:38.7552070Z         Args:
2025-07-17T07:05:38.7552240Z             src: the sequence to the encoder (required).
2025-07-17T07:05:38.7552500Z             tgt: the sequence to the decoder (required).
2025-07-17T07:05:38.7552760Z             src_mask: the additive mask for the src sequence (optional).
2025-07-17T07:05:38.7553050Z             tgt_mask: the additive mask for the tgt sequence (optional).
2025-07-17T07:05:38.7553380Z             memory_mask: the additive mask for the encoder output (optional).
2025-07-17T07:05:38.7553710Z             src_key_padding_mask: the Tensor mask for src keys per batch (optional).
2025-07-17T07:05:38.7554050Z             tgt_key_padding_mask: the Tensor mask for tgt keys per batch (optional).
2025-07-17T07:05:38.7554400Z             memory_key_padding_mask: the Tensor mask for memory keys per batch (optional).
2025-07-17T07:05:38.7554750Z             src_is_causal: If specified, applies a causal mask as ``src_mask``.
2025-07-17T07:05:38.7555030Z                 Default: ``None``; try to detect a causal mask.
2025-07-17T07:05:38.7555240Z                 Warning:
2025-07-17T07:05:38.7555500Z                 ``src_is_causal`` provides a hint that ``src_mask`` is
2025-07-17T07:05:38.7555890Z                 the causal mask. Providing incorrect hints can result in
2025-07-17T07:05:38.7556170Z                 incorrect execution, including forward and backward
2025-07-17T07:05:38.7556400Z                 compatibility.
2025-07-17T07:05:38.7556640Z             tgt_is_causal: If specified, applies a causal mask as ``tgt_mask``.
2025-07-17T07:05:38.7556920Z                 Default: ``None``; try to detect a causal mask.
2025-07-17T07:05:38.7557120Z                 Warning:
2025-07-17T07:05:38.7557320Z                 ``tgt_is_causal`` provides a hint that ``tgt_mask`` is
2025-07-17T07:05:38.7557600Z                 the causal mask. Providing incorrect hints can result in
2025-07-17T07:05:38.7557870Z                 incorrect execution, including forward and backward
2025-07-17T07:05:38.7558090Z                 compatibility.
2025-07-17T07:05:38.7558310Z             memory_is_causal: If specified, applies a causal mask as
2025-07-17T07:05:38.7558540Z                 ``memory_mask``.
2025-07-17T07:05:38.7558710Z                 Default: ``False``.
2025-07-17T07:05:38.7558880Z                 Warning:
2025-07-17T07:05:38.7559050Z                 ``memory_is_causal`` provides a hint that
2025-07-17T07:05:38.7559310Z                 ``memory_mask`` is the causal mask. Providing incorrect
2025-07-17T07:05:38.7559570Z                 hints can result in incorrect execution, including
2025-07-17T07:05:38.7559810Z                 forward and backward compatibility.
2025-07-17T07:05:38.7559950Z 
2025-07-17T07:05:38.7560000Z         Shape:
2025-07-17T07:05:38.7560230Z             - src: :math:`(S, E)` for unbatched input, :math:`(S, N, E)` if `batch_first=False` or
2025-07-17T07:05:38.7560510Z               `(N, S, E)` if `batch_first=True`.
2025-07-17T07:05:38.7560790Z             - tgt: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or
2025-07-17T07:05:38.7561070Z               `(N, T, E)` if `batch_first=True`.
2025-07-17T07:05:38.7561330Z             - src_mask: :math:`(S, S)` or :math:`(N\cdot\text{num\_heads}, S, S)`.
2025-07-17T07:05:38.7561630Z             - tgt_mask: :math:`(T, T)` or :math:`(N\cdot\text{num\_heads}, T, T)`.
2025-07-17T07:05:38.7561880Z             - memory_mask: :math:`(T, S)`.
2025-07-17T07:05:38.7562150Z             - src_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`.
2025-07-17T07:05:38.7562510Z             - tgt_key_padding_mask: :math:`(T)` for unbatched input otherwise :math:`(N, T)`.
2025-07-17T07:05:38.7562880Z             - memory_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`.
2025-07-17T07:05:38.7563090Z 
2025-07-17T07:05:38.7563280Z             Note: [src/tgt/memory]_mask ensures that position :math:`i` is allowed to attend the unmasked
2025-07-17T07:05:38.7563660Z             positions. If a BoolTensor is provided, positions with ``True``
2025-07-17T07:05:38.7564030Z             are not allowed to attend while ``False`` values will be unchanged. If a FloatTensor
2025-07-17T07:05:38.7564370Z             is provided, it will be added to the attention weight.
2025-07-17T07:05:38.7564720Z             [src/tgt/memory]_key_padding_mask provides specified elements in the key to be ignored by
2025-07-17T07:05:38.7565150Z             the attention. If a BoolTensor is provided, the positions with the
2025-07-17T07:05:38.7565530Z             value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged.
2025-07-17T07:05:38.7565780Z 
2025-07-17T07:05:38.7565940Z             - output: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or
2025-07-17T07:05:38.7566240Z               `(N, T, E)` if `batch_first=True`.
2025-07-17T07:05:38.7566380Z 
2025-07-17T07:05:38.7566520Z             Note: Due to the multi-head attention architecture in the transformer model,
2025-07-17T07:05:38.7566960Z             the output sequence length of a transformer is same as the input sequence
2025-07-17T07:05:38.7567310Z             (i.e. target) length of the decoder.
2025-07-17T07:05:38.7567450Z 
2025-07-17T07:05:38.7567650Z             where :math:`S` is the source sequence length, :math:`T` is the target sequence length, :math:`N` is the
2025-07-17T07:05:38.7567980Z             batch size, :math:`E` is the feature number
2025-07-17T07:05:38.7568130Z 
2025-07-17T07:05:38.7568170Z         Examples:
2025-07-17T07:05:38.7568310Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:38.7568490Z             >>> output = transformer_model(
2025-07-17T07:05:38.7568720Z             ...     src, tgt, src_mask=src_mask, tgt_mask=tgt_mask
2025-07-17T07:05:38.7568920Z             ... )
2025-07-17T07:05:38.7569040Z         
2025-07-17T07:05:38.7569270Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.7579250Z 
2025-07-17T07:05:38.7586150Z msg = Cannot scrape callname=EmbeddingBag in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/sparse.py line=272.
2025-07-17T07:05:38.7586880Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.7587310Z Compute sums or means of 'bags' of embeddings, without instantiating the intermediate embeddings.
2025-07-17T07:05:38.7587580Z 
2025-07-17T07:05:38.7587790Z     For bags of constant length, no :attr:`per_sample_weights`, no indices equal to :attr:`padding_idx`,
2025-07-17T07:05:38.7588120Z     and with 2D inputs, this class
2025-07-17T07:05:38.7588250Z 
2025-07-17T07:05:38.7588450Z         * with ``mode="sum"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.sum(dim=1)``,
2025-07-17T07:05:38.7588900Z         * with ``mode="mean"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.mean(dim=1)``,
2025-07-17T07:05:38.7589350Z         * with ``mode="max"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.max(dim=1)``.
2025-07-17T07:05:38.7589610Z 
2025-07-17T07:05:38.7589830Z     However, :class:`~torch.nn.EmbeddingBag` is much more time and memory efficient than using a chain of these
2025-07-17T07:05:38.7590150Z     operations.
2025-07-17T07:05:38.7590240Z 
2025-07-17T07:05:38.7590390Z     EmbeddingBag also supports per-sample weights as an argument to the forward
2025-07-17T07:05:38.7590750Z     pass. This scales the output of the Embedding before performing a weighted
2025-07-17T07:05:38.7591120Z     reduction as specified by ``mode``. If :attr:`per_sample_weights` is passed, the
2025-07-17T07:05:38.7591480Z     only supported ``mode`` is ``"sum"``, which computes a weighted sum according to
2025-07-17T07:05:38.7591750Z     :attr:`per_sample_weights`.
2025-07-17T07:05:38.7591870Z 
2025-07-17T07:05:38.7591920Z     Args:
2025-07-17T07:05:38.7592100Z         num_embeddings (int): size of the dictionary of embeddings
2025-07-17T07:05:38.7592380Z         embedding_dim (int): the size of each embedding vector
2025-07-17T07:05:38.7592890Z         max_norm (float, optional): If given, each embedding vector with norm larger than :attr:`max_norm`
2025-07-17T07:05:38.7593280Z                                     is renormalized to have norm :attr:`max_norm`.
2025-07-17T07:05:38.7593650Z         norm_type (float, optional): The p of the p-norm to compute for the :attr:`max_norm` option. Default ``2``.
2025-07-17T07:05:38.7594170Z         scale_grad_by_freq (bool, optional): if given, this will scale gradients by the inverse of frequency of
2025-07-17T07:05:38.7594530Z                                                 the words in the mini-batch. Default ``False``.
2025-07-17T07:05:38.7594820Z                                                 Note: this option is not supported when ``mode="max"``.
2025-07-17T07:05:38.7595150Z         mode (str, optional): ``"sum"``, ``"mean"`` or ``"max"``. Specifies the way to reduce the bag.
2025-07-17T07:05:38.7595500Z                                  ``"sum"`` computes the weighted sum, taking :attr:`per_sample_weights`
2025-07-17T07:05:38.7595950Z                                  into consideration. ``"mean"`` computes the average of the values
2025-07-17T07:05:38.7596340Z                                  in the bag, ``"max"`` computes the max value over each bag.
2025-07-17T07:05:38.7596580Z                                  Default: ``"mean"``
2025-07-17T07:05:38.7596920Z         sparse (bool, optional): if ``True``, gradient w.r.t. :attr:`weight` matrix will be a sparse tensor. See
2025-07-17T07:05:38.7597330Z                                  Notes for more details regarding sparse gradients. Note: this option is not
2025-07-17T07:05:38.7597630Z                                  supported when ``mode="max"``.
2025-07-17T07:05:38.7597990Z         include_last_offset (bool, optional): if ``True``, :attr:`offsets` has one additional element, where the last element
2025-07-17T07:05:38.7598420Z                                       is equivalent to the size of `indices`. This matches the CSR format.
2025-07-17T07:05:38.7598820Z         padding_idx (int, optional): If specified, the entries at :attr:`padding_idx` do not contribute to the
2025-07-17T07:05:38.7599250Z                                      gradient; therefore, the embedding vector at :attr:`padding_idx` is not updated
2025-07-17T07:05:38.7599630Z                                      during training, i.e. it remains as a fixed "pad". For a newly constructed
2025-07-17T07:05:38.7600010Z                                      EmbeddingBag, the embedding vector at :attr:`padding_idx` will default to all
2025-07-17T07:05:38.7600380Z                                      zeros, but can be updated to another value to be used as the padding vector.
2025-07-17T07:05:38.7600740Z                                      Note that the embedding vector at :attr:`padding_idx` is excluded from the
2025-07-17T07:05:38.7601020Z                                      reduction.
2025-07-17T07:05:38.7601150Z 
2025-07-17T07:05:38.7601200Z     Attributes:
2025-07-17T07:05:38.7601480Z         weight (Tensor): the learnable weights of the module of shape `(num_embeddings, embedding_dim)`
2025-07-17T07:05:38.7601820Z                          initialized from :math:`\mathcal{N}(0, 1)`.
2025-07-17T07:05:38.7601980Z 
2025-07-17T07:05:38.7602030Z     Examples::
2025-07-17T07:05:38.7602110Z 
2025-07-17T07:05:38.7602220Z         >>> # an EmbeddingBag module containing 10 tensors of size 3
2025-07-17T07:05:38.7602480Z         >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum')
2025-07-17T07:05:38.7602720Z         >>> # a batch of 2 samples of 4 indices each
2025-07-17T07:05:38.7602980Z         >>> input = torch.tensor([1, 2, 4, 5, 4, 3, 2, 9], dtype=torch.long)
2025-07-17T07:05:38.7603250Z         >>> offsets = torch.tensor([0, 4], dtype=torch.long)
2025-07-17T07:05:38.7603490Z         >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-07-17T07:05:38.7603710Z         >>> embedding_sum(input, offsets)
2025-07-17T07:05:38.7603900Z         tensor([[-0.8861, -5.4350, -0.0523],
2025-07-17T07:05:38.7604080Z                 [ 1.1306, -2.5798, -1.0044]])
2025-07-17T07:05:38.7604210Z 
2025-07-17T07:05:38.7604300Z         >>> # Example with padding_idx
2025-07-17T07:05:38.7604550Z         >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum', padding_idx=2)
2025-07-17T07:05:38.7604850Z         >>> input = torch.tensor([2, 2, 2, 2, 4, 3, 2, 9], dtype=torch.long)
2025-07-17T07:05:38.7605190Z         >>> offsets = torch.tensor([0, 4], dtype=torch.long)
2025-07-17T07:05:38.7605410Z         >>> embedding_sum(input, offsets)
2025-07-17T07:05:38.7605600Z         tensor([[ 0.0000,  0.0000,  0.0000],
2025-07-17T07:05:38.7605780Z                 [-0.7082,  3.2145, -2.6251]])
2025-07-17T07:05:38.7605910Z 
2025-07-17T07:05:38.7606010Z         >>> # An EmbeddingBag can be loaded from an Embedding like so
2025-07-17T07:05:38.7606270Z         >>> embedding = nn.Embedding(10, 3, padding_idx=2)
2025-07-17T07:05:38.7606520Z         >>> embedding_sum = nn.EmbeddingBag.from_pretrained(
2025-07-17T07:05:38.7606810Z                 embedding.weight,
2025-07-17T07:05:38.7607050Z                 padding_idx=embedding.padding_idx,
2025-07-17T07:05:38.7607250Z                 mode='sum')
2025-07-17T07:05:38.7607390Z     
2025-07-17T07:05:38.7607600Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.7607820Z 
2025-07-17T07:05:38.7608250Z msg = Cannot scrape callname=batch_isend_irecv in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=2706.
2025-07-17T07:05:38.7608880Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.7609100Z 
2025-07-17T07:05:38.7609250Z Send or Receive a batch of tensors asynchronously and return a list of requests.
2025-07-17T07:05:38.7609460Z 
2025-07-17T07:05:38.7609610Z Process each of the operations in ``p2p_op_list`` and return the corresponding
2025-07-17T07:05:38.7609940Z requests. NCCL, Gloo, and UCC backend are currently supported.
2025-07-17T07:05:38.7610120Z 
2025-07-17T07:05:38.7610160Z Args:
2025-07-17T07:05:38.7610360Z     p2p_op_list: A list of point-to-point operations(type of each operator is
2025-07-17T07:05:38.7610700Z         ``torch.distributed.P2POp``). The order of the isend/irecv in the list
2025-07-17T07:05:38.7611030Z         matters and it needs to match with corresponding isend/irecv on the
2025-07-17T07:05:38.7611270Z         remote end.
2025-07-17T07:05:38.7611350Z 
2025-07-17T07:05:38.7611400Z Returns:
2025-07-17T07:05:38.7611610Z     A list of distributed request objects returned by calling the corresponding
2025-07-17T07:05:38.7611870Z     op in the op_list.
2025-07-17T07:05:38.7611970Z 
2025-07-17T07:05:38.7612010Z Examples:
2025-07-17T07:05:38.7612140Z     >>> # xdoctest: +SKIP("no rank")
2025-07-17T07:05:38.7612370Z     >>> send_tensor = torch.arange(2, dtype=torch.float32) + 2 * rank
2025-07-17T07:05:38.7612640Z     >>> recv_tensor = torch.randn(2, dtype=torch.float32)
2025-07-17T07:05:38.7612930Z     >>> send_op = dist.P2POp(dist.isend, send_tensor, (rank + 1) % world_size)
2025-07-17T07:05:38.7613210Z     >>> recv_op = dist.P2POp(
2025-07-17T07:05:38.7613430Z     ...     dist.irecv, recv_tensor, (rank - 1 + world_size) % world_size
2025-07-17T07:05:38.7613650Z     ... )
2025-07-17T07:05:38.7613800Z     >>> reqs = batch_isend_irecv([send_op, recv_op])
2025-07-17T07:05:38.7613990Z     >>> for req in reqs:
2025-07-17T07:05:38.7614140Z     >>>     req.wait()
2025-07-17T07:05:38.7614270Z     >>> recv_tensor
2025-07-17T07:05:38.7614400Z     tensor([2, 3])     # Rank 0
2025-07-17T07:05:38.7614560Z     tensor([0, 1])     # Rank 1
2025-07-17T07:05:38.7614660Z 
2025-07-17T07:05:38.7614810Z .. note:: Note that when this API is used with the NCCL PG backend, users must set
2025-07-17T07:05:38.7615150Z     the current GPU device with `torch.cuda.set_device`, otherwise it will
2025-07-17T07:05:38.7615410Z     lead to unexpected hang issues.
2025-07-17T07:05:38.7615530Z 
2025-07-17T07:05:38.7615660Z     In addition, if this API is the first collective call in the ``group``
2025-07-17T07:05:38.7616020Z     passed to ``dist.P2POp``, all ranks of the ``group`` must participate in
2025-07-17T07:05:38.7616350Z     this API call; otherwise, the behavior is undefined. If this API call is
2025-07-17T07:05:38.7616680Z     not the first collective call in the ``group``, batched P2P operations
2025-07-17T07:05:38.7617050Z     involving only a subset of ranks of the ``group`` are allowed.
2025-07-17T07:05:38.7617230Z 
2025-07-17T07:05:38.7617380Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.7617590Z 
2025-07-17T07:05:38.7618030Z msg = Cannot scrape callname=all_reduce in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=2838.
2025-07-17T07:05:38.7618640Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.7618860Z 
2025-07-17T07:05:38.7619120Z Reduces the tensor data across all machines in a way that all get the final result.
2025-07-17T07:05:38.7619420Z 
2025-07-17T07:05:38.7619560Z After the call ``tensor`` is going to be bitwise identical in all processes.
2025-07-17T07:05:38.7619760Z 
2025-07-17T07:05:38.7619820Z Complex tensors are supported.
2025-07-17T07:05:38.7619940Z 
2025-07-17T07:05:38.7619980Z Args:
2025-07-17T07:05:38.7620170Z     tensor (Tensor): Input and output of the collective. The function
2025-07-17T07:05:38.7620410Z         operates in-place.
2025-07-17T07:05:38.7620580Z     op (optional): One of the values from
2025-07-17T07:05:38.7620770Z         ``torch.distributed.ReduceOp``
2025-07-17T07:05:38.7621020Z         enum.  Specifies an operation used for element-wise reductions.
2025-07-17T07:05:38.7621350Z     group (ProcessGroup, optional): The process group to work on. If None,
2025-07-17T07:05:38.7621630Z         the default process group will be used.
2025-07-17T07:05:38.7621880Z     async_op (bool, optional): Whether this op should be an async op
2025-07-17T07:05:38.7622070Z 
2025-07-17T07:05:38.7622110Z Returns:
2025-07-17T07:05:38.7622260Z     Async work handle, if async_op is set to True.
2025-07-17T07:05:38.7622490Z     None, if not async_op or if not part of the group
2025-07-17T07:05:38.7622640Z 
2025-07-17T07:05:38.7622690Z Examples:
2025-07-17T07:05:38.7622810Z     >>> # xdoctest: +SKIP("no rank")
2025-07-17T07:05:38.7623010Z     >>> # All tensors below are of torch.int64 type.
2025-07-17T07:05:38.7623220Z     >>> # We have 2 process groups, 2 ranks.
2025-07-17T07:05:38.7623420Z     >>> device = torch.device(f"cuda:{rank}")
2025-07-17T07:05:38.7623690Z     >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank
2025-07-17T07:05:38.7623930Z     >>> tensor
2025-07-17T07:05:38.7624070Z     tensor([1, 2], device='cuda:0') # Rank 0
2025-07-17T07:05:38.7624260Z     tensor([3, 4], device='cuda:1') # Rank 1
2025-07-17T07:05:38.7624470Z     >>> dist.all_reduce(tensor, op=ReduceOp.SUM)
2025-07-17T07:05:38.7624650Z     >>> tensor
2025-07-17T07:05:38.7624780Z     tensor([4, 6], device='cuda:0') # Rank 0
2025-07-17T07:05:38.7624980Z     tensor([4, 6], device='cuda:1') # Rank 1
2025-07-17T07:05:38.7625110Z 
2025-07-17T07:05:38.7625190Z     >>> # All tensors below are of torch.cfloat type.
2025-07-17T07:05:38.7625400Z     >>> # We have 2 process groups, 2 ranks.
2025-07-17T07:05:38.7625580Z     >>> tensor = torch.tensor(
2025-07-17T07:05:38.7625780Z     ...     [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device
2025-07-17T07:05:38.7625990Z     ... ) + 2 * rank * (1 + 1j)
2025-07-17T07:05:38.7626140Z     >>> tensor
2025-07-17T07:05:38.7626290Z     tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0
2025-07-17T07:05:38.7626520Z     tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1
2025-07-17T07:05:38.7626740Z     >>> dist.all_reduce(tensor, op=ReduceOp.SUM)
2025-07-17T07:05:38.7626920Z     >>> tensor
2025-07-17T07:05:38.7627070Z     tensor([4.+4.j, 6.+6.j], device='cuda:0') # Rank 0
2025-07-17T07:05:38.7627300Z     tensor([4.+4.j, 6.+6.j], device='cuda:1') # Rank 1
2025-07-17T07:05:38.7627440Z 
2025-07-17T07:05:38.7627440Z 
2025-07-17T07:05:38.7627610Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.7690400Z 
2025-07-17T07:05:38.7691100Z msg = Cannot scrape callname=gather_object in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=3198.
2025-07-17T07:05:38.7691880Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.7692120Z 
2025-07-17T07:05:38.7692260Z Gathers picklable objects from the whole group in a single process.
2025-07-17T07:05:38.7692470Z 
2025-07-17T07:05:38.7692620Z Similar to :func:`gather`, but Python objects can be passed in. Note that the
2025-07-17T07:05:38.7692920Z object must be picklable in order to be gathered.
2025-07-17T07:05:38.7693080Z 
2025-07-17T07:05:38.7693130Z Args:
2025-07-17T07:05:38.7693390Z     obj (Any): Input object. Must be picklable.
2025-07-17T07:05:38.7693740Z     object_gather_list (list[Any]): Output list. On the ``dst`` rank, it
2025-07-17T07:05:38.7694070Z         should be correctly sized as the size of the group for this
2025-07-17T07:05:38.7694380Z         collective and will contain the output. Must be ``None`` on non-dst
2025-07-17T07:05:38.7694640Z         ranks. (default is ``None``)
2025-07-17T07:05:38.7694950Z     dst (int, optional): Destination rank on global process group (regardless of ``group`` argument).
2025-07-17T07:05:38.7695330Z         (If both ``dst`` and ``group_dst`` are None, default is global rank 0)
2025-07-17T07:05:38.7695660Z     group: (ProcessGroup, optional): The process group to work on. If None,
2025-07-17T07:05:38.7695980Z         the default process group will be used. Default is ``None``.
2025-07-17T07:05:38.7696370Z     group_dst (int, optional): Destination rank on ``group``.  Invalid to specify both ``dst`` and ``group_dst``
2025-07-17T07:05:38.7696680Z 
2025-07-17T07:05:38.7696720Z Returns:
2025-07-17T07:05:38.7696910Z     None. On the ``dst`` rank, ``object_gather_list`` will contain the
2025-07-17T07:05:38.7697140Z     output of the collective.
2025-07-17T07:05:38.7697260Z 
2025-07-17T07:05:38.7697400Z .. note:: Note that this API differs slightly from the gather collective
2025-07-17T07:05:38.7697720Z     since it does not provide an async_op handle and thus will be a blocking
2025-07-17T07:05:38.7697960Z     call.
2025-07-17T07:05:38.7698030Z 
2025-07-17T07:05:38.7698160Z .. note:: For NCCL-based processed groups, internal tensor representations
2025-07-17T07:05:38.7698490Z     of objects must be moved to the GPU device before communication takes
2025-07-17T07:05:38.7698770Z     place. In this case, the device used is given by
2025-07-17T07:05:38.7699060Z     ``torch.cuda.current_device()`` and it is the user's responsibility to
2025-07-17T07:05:38.7699380Z     ensure that this is set so that each rank has an individual GPU, via
2025-07-17T07:05:38.7699630Z     ``torch.cuda.set_device()``.
2025-07-17T07:05:38.7699750Z 
2025-07-17T07:05:38.7699790Z .. warning::
2025-07-17T07:05:38.7700010Z     Object collectives have a number of serious performance and scalability
2025-07-17T07:05:38.7700320Z     limitations.  See :ref:`object_collectives` for details.
2025-07-17T07:05:38.7700500Z 
2025-07-17T07:05:38.7700540Z .. warning::
2025-07-17T07:05:38.7700740Z     :func:`gather_object` uses ``pickle`` module implicitly, which is
2025-07-17T07:05:38.7701060Z     known to be insecure. It is possible to construct malicious pickle data
2025-07-17T07:05:38.7701390Z     which will execute arbitrary code during unpickling. Only call this
2025-07-17T07:05:38.7701640Z     function with data you trust.
2025-07-17T07:05:38.7701760Z 
2025-07-17T07:05:38.7701800Z .. warning::
2025-07-17T07:05:38.7702010Z     Calling :func:`gather_object` with GPU tensors is not well supported
2025-07-17T07:05:38.7702350Z     and inefficient as it incurs GPU -> CPU transfer since tensors would be
2025-07-17T07:05:38.7702660Z     pickled. Please consider using :func:`gather` instead.
2025-07-17T07:05:38.7702830Z 
2025-07-17T07:05:38.7702940Z Example::
2025-07-17T07:05:38.7703100Z     >>> # xdoctest: +SKIP("need process group init")
2025-07-17T07:05:38.7703360Z     >>> # Note: Process group initialization omitted on each rank.
2025-07-17T07:05:38.7703620Z     >>> import torch.distributed as dist
2025-07-17T07:05:38.7703810Z     >>> # Assumes world_size of 3.
2025-07-17T07:05:38.7704030Z     >>> gather_objects = ["foo", 12, {1: 2}] # any picklable object
2025-07-17T07:05:38.7704280Z     >>> output = [None for _ in gather_objects]
2025-07-17T07:05:38.7704470Z     >>> dist.gather_object(
2025-07-17T07:05:38.7704640Z     ...     gather_objects[dist.get_rank()],
2025-07-17T07:05:38.7704850Z     ...     output if dist.get_rank() == 0 else None,
2025-07-17T07:05:38.7705040Z     ...     dst=0
2025-07-17T07:05:38.7705160Z     ... )
2025-07-17T07:05:38.7705270Z     >>> # On rank 0
2025-07-17T07:05:38.7705400Z     >>> output
2025-07-17T07:05:38.7705610Z     ['foo', 12, {1: 2}]
2025-07-17T07:05:38.7705760Z 
2025-07-17T07:05:38.7705910Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.7706130Z 
2025-07-17T07:05:38.7706540Z msg = Cannot scrape callname=all_gather in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=3794.
2025-07-17T07:05:38.7707160Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.7707380Z 
2025-07-17T07:05:38.7707460Z Gathers tensors from the whole group in a list.
2025-07-17T07:05:38.7707610Z 
2025-07-17T07:05:38.7707690Z Complex and uneven sized tensors are supported.
2025-07-17T07:05:38.7707840Z 
2025-07-17T07:05:38.7707890Z Args:
2025-07-17T07:05:38.7708060Z     tensor_list (list[Tensor]): Output list. It should contain
2025-07-17T07:05:38.7708350Z         correctly-sized tensors to be used for output of the collective.
2025-07-17T07:05:38.7708620Z         Uneven sized tensors are supported.
2025-07-17T07:05:38.7708860Z     tensor (Tensor): Tensor to be broadcast from current process.
2025-07-17T07:05:38.7709180Z     group (ProcessGroup, optional): The process group to work on. If None,
2025-07-17T07:05:38.7709460Z         the default process group will be used.
2025-07-17T07:05:38.7709720Z     async_op (bool, optional): Whether this op should be an async op
2025-07-17T07:05:38.7709910Z 
2025-07-17T07:05:38.7709950Z Returns:
2025-07-17T07:05:38.7710100Z     Async work handle, if async_op is set to True.
2025-07-17T07:05:38.7710340Z     None, if not async_op or if not part of the group
2025-07-17T07:05:38.7710490Z 
2025-07-17T07:05:38.7710580Z Examples:
2025-07-17T07:05:38.7710730Z     >>> # xdoctest: +SKIP("need process group init")
2025-07-17T07:05:38.7710950Z     >>> # All tensors below are of torch.int64 dtype.
2025-07-17T07:05:38.7711160Z     >>> # We have 2 process groups, 2 ranks.
2025-07-17T07:05:38.7711360Z     >>> device = torch.device(f"cuda:{rank}")
2025-07-17T07:05:38.7711550Z     >>> tensor_list = [
2025-07-17T07:05:38.7711770Z     ...     torch.zeros(2, dtype=torch.int64, device=device) for _ in range(2)
2025-07-17T07:05:38.7712010Z     ... ]
2025-07-17T07:05:38.7712110Z     >>> tensor_list
2025-07-17T07:05:38.7712320Z     [tensor([0, 0], device='cuda:0'), tensor([0, 0], device='cuda:0')] # Rank 0
2025-07-17T07:05:38.7712630Z     [tensor([0, 0], device='cuda:1'), tensor([0, 0], device='cuda:1')] # Rank 1
2025-07-17T07:05:38.7712950Z     >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank
2025-07-17T07:05:38.7713190Z     >>> tensor
2025-07-17T07:05:38.7713330Z     tensor([1, 2], device='cuda:0') # Rank 0
2025-07-17T07:05:38.7713530Z     tensor([3, 4], device='cuda:1') # Rank 1
2025-07-17T07:05:38.7713720Z     >>> dist.all_gather(tensor_list, tensor)
2025-07-17T07:05:38.7713890Z     >>> tensor_list
2025-07-17T07:05:38.7714090Z     [tensor([1, 2], device='cuda:0'), tensor([3, 4], device='cuda:0')] # Rank 0
2025-07-17T07:05:38.7714440Z     [tensor([1, 2], device='cuda:1'), tensor([3, 4], device='cuda:1')] # Rank 1
2025-07-17T07:05:38.7714620Z 
2025-07-17T07:05:38.7714710Z     >>> # All tensors below are of torch.cfloat dtype.
2025-07-17T07:05:38.7714930Z     >>> # We have 2 process groups, 2 ranks.
2025-07-17T07:05:38.7715160Z     >>> tensor_list = [
2025-07-17T07:05:38.7715380Z     ...     torch.zeros(2, dtype=torch.cfloat, device=device) for _ in range(2)
2025-07-17T07:05:38.7715620Z     ... ]
2025-07-17T07:05:38.7715730Z     >>> tensor_list
2025-07-17T07:05:38.7715970Z     [tensor([0.+0.j, 0.+0.j], device='cuda:0'), tensor([0.+0.j, 0.+0.j], device='cuda:0')] # Rank 0
2025-07-17T07:05:38.7716330Z     [tensor([0.+0.j, 0.+0.j], device='cuda:1'), tensor([0.+0.j, 0.+0.j], device='cuda:1')] # Rank 1
2025-07-17T07:05:38.7716600Z     >>> tensor = torch.tensor(
2025-07-17T07:05:38.7716800Z     ...     [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device
2025-07-17T07:05:38.7717010Z     ... ) + 2 * rank * (1 + 1j)
2025-07-17T07:05:38.7717220Z     >>> tensor
2025-07-17T07:05:38.7717430Z     tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0
2025-07-17T07:05:38.7717660Z     tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1
2025-07-17T07:05:38.7717870Z     >>> dist.all_gather(tensor_list, tensor)
2025-07-17T07:05:38.7718040Z     >>> tensor_list
2025-07-17T07:05:38.7718270Z     [tensor([1.+1.j, 2.+2.j], device='cuda:0'), tensor([3.+3.j, 4.+4.j], device='cuda:0')] # Rank 0
2025-07-17T07:05:38.7718630Z     [tensor([1.+1.j, 2.+2.j], device='cuda:1'), tensor([3.+3.j, 4.+4.j], device='cuda:1')] # Rank 1
2025-07-17T07:05:38.7718850Z 
2025-07-17T07:05:38.7718850Z 
2025-07-17T07:05:38.7719000Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.7719280Z 
2025-07-17T07:05:38.7719720Z msg = Cannot scrape callname=all_to_all_single in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=4500.
2025-07-17T07:05:38.7720400Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.7726500Z 
2025-07-17T07:05:38.7726670Z Split input tensor and then scatter the split list to all processes in a group.
2025-07-17T07:05:38.7726890Z 
2025-07-17T07:05:38.7727050Z Later the received tensors are concatenated from all the processes in the group
2025-07-17T07:05:38.7727340Z and returned as a single output tensor.
2025-07-17T07:05:38.7727470Z 
2025-07-17T07:05:38.7727540Z Complex tensors are supported.
2025-07-17T07:05:38.7727650Z 
2025-07-17T07:05:38.7727700Z Args:
2025-07-17T07:05:38.7727860Z     output (Tensor): Gathered concatenated output tensor.
2025-07-17T07:05:38.7728100Z     input (Tensor): Input tensor to scatter.
2025-07-17T07:05:38.7728360Z     output_split_sizes: (list[Int], optional): Output split sizes for dim 0
2025-07-17T07:05:38.7728690Z         if specified None or empty, dim 0 of ``output`` tensor must divide
2025-07-17T07:05:38.7728940Z         equally by ``world_size``.
2025-07-17T07:05:38.7729180Z     input_split_sizes: (list[Int], optional): Input split sizes for dim 0
2025-07-17T07:05:38.7729490Z         if specified None or empty, dim 0 of ``input`` tensor must divide
2025-07-17T07:05:38.7729740Z         equally by ``world_size``.
2025-07-17T07:05:38.7729990Z     group (ProcessGroup, optional): The process group to work on. If None,
2025-07-17T07:05:38.7730270Z         the default process group will be used.
2025-07-17T07:05:38.7730540Z     async_op (bool, optional): Whether this op should be an async op.
2025-07-17T07:05:38.7730720Z 
2025-07-17T07:05:38.7730770Z Returns:
2025-07-17T07:05:38.7730910Z     Async work handle, if async_op is set to True.
2025-07-17T07:05:38.7731150Z     None, if not async_op or if not part of the group.
2025-07-17T07:05:38.7731300Z 
2025-07-17T07:05:38.7731350Z .. warning::
2025-07-17T07:05:38.7731520Z     `all_to_all_single` is experimental and subject to change.
2025-07-17T07:05:38.7731690Z 
2025-07-17T07:05:38.7731740Z Examples:
2025-07-17T07:05:38.7731870Z     >>> # xdoctest: +SKIP("Undefined rank")
2025-07-17T07:05:38.7732170Z     >>> input = torch.arange(4) + rank * 4
2025-07-17T07:05:38.7732350Z     >>> input
2025-07-17T07:05:38.7732480Z     tensor([0, 1, 2, 3])     # Rank 0
2025-07-17T07:05:38.7732650Z     tensor([4, 5, 6, 7])     # Rank 1
2025-07-17T07:05:38.7732850Z     tensor([8, 9, 10, 11])   # Rank 2
2025-07-17T07:05:38.7733020Z     tensor([12, 13, 14, 15]) # Rank 3
2025-07-17T07:05:38.7733220Z     >>> output = torch.empty([4], dtype=torch.int64)
2025-07-17T07:05:38.7733440Z     >>> dist.all_to_all_single(output, input)
2025-07-17T07:05:38.7733490Z     >>> output
2025-07-17T07:05:38.7733540Z     tensor([0, 4, 8, 12])    # Rank 0
2025-07-17T07:05:38.7733600Z     tensor([1, 5, 9, 13])    # Rank 1
2025-07-17T07:05:38.7733650Z     tensor([2, 6, 10, 14])   # Rank 2
2025-07-17T07:05:38.7733700Z     tensor([3, 7, 11, 15])   # Rank 3
2025-07-17T07:05:38.7733700Z 
2025-07-17T07:05:38.7733800Z     >>> # Essentially, it is similar to following operation:
2025-07-17T07:05:38.7733990Z     >>> scatter_list = list(input.chunk(world_size))
2025-07-17T07:05:38.7734140Z     >>> gather_list = list(output.chunk(world_size))
2025-07-17T07:05:38.7734210Z     >>> for i in range(world_size):
2025-07-17T07:05:38.7734340Z     >>>     dist.scatter(gather_list[i], scatter_list if i == rank else [], src = i)
2025-07-17T07:05:38.7734350Z 
2025-07-17T07:05:38.7734410Z     >>> # Another example with uneven split
2025-07-17T07:05:38.7734460Z     >>> input
2025-07-17T07:05:38.7734550Z     tensor([0, 1, 2, 3, 4, 5])                                       # Rank 0
2025-07-17T07:05:38.7734650Z     tensor([10, 11, 12, 13, 14, 15, 16, 17, 18])                     # Rank 1
2025-07-17T07:05:38.7734750Z     tensor([20, 21, 22, 23, 24])                                     # Rank 2
2025-07-17T07:05:38.7734850Z     tensor([30, 31, 32, 33, 34, 35, 36])                             # Rank 3
2025-07-17T07:05:38.7734900Z     >>> input_splits
2025-07-17T07:05:38.7734980Z     [2, 2, 1, 1]                                                     # Rank 0
2025-07-17T07:05:38.7735060Z     [3, 2, 2, 2]                                                     # Rank 1
2025-07-17T07:05:38.7735140Z     [2, 1, 1, 1]                                                     # Rank 2
2025-07-17T07:05:38.7735210Z     [2, 2, 2, 1]                                                     # Rank 3
2025-07-17T07:05:38.7735260Z     >>> output_splits
2025-07-17T07:05:38.7735340Z     [2, 3, 2, 2]                                                     # Rank 0
2025-07-17T07:05:38.7735420Z     [2, 2, 1, 2]                                                     # Rank 1
2025-07-17T07:05:38.7735490Z     [1, 2, 1, 2]                                                     # Rank 2
2025-07-17T07:05:38.7735560Z     [1, 2, 1, 1]                                                     # Rank 3
2025-07-17T07:05:38.7735610Z     >>> output = ...
2025-07-17T07:05:38.7735740Z     >>> dist.all_to_all_single(output, input, output_splits, input_splits)
2025-07-17T07:05:38.7735780Z     >>> output
2025-07-17T07:05:38.7735880Z     tensor([ 0,  1, 10, 11, 12, 20, 21, 30, 31])                     # Rank 0
2025-07-17T07:05:38.7735970Z     tensor([ 2,  3, 13, 14, 22, 32, 33])                             # Rank 1
2025-07-17T07:05:38.7736070Z     tensor([ 4, 15, 16, 23, 34, 35])                                 # Rank 2
2025-07-17T07:05:38.7736160Z     tensor([ 5, 17, 18, 24, 36])                                     # Rank 3
2025-07-17T07:05:38.7736170Z 
2025-07-17T07:05:38.7736170Z 
2025-07-17T07:05:38.7736260Z     >>> # Another example with tensors of torch.cfloat type.
2025-07-17T07:05:38.7736320Z     >>> input = torch.tensor(
2025-07-17T07:05:38.7736410Z     ...     [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat
2025-07-17T07:05:38.7736460Z     ... ) + 4 * rank * (1 + 1j)
2025-07-17T07:05:38.7736500Z     >>> input
2025-07-17T07:05:38.7736610Z     tensor([1+1j, 2+2j, 3+3j, 4+4j])                                # Rank 0
2025-07-17T07:05:38.7736710Z     tensor([5+5j, 6+6j, 7+7j, 8+8j])                                # Rank 1
2025-07-17T07:05:38.7736840Z     tensor([9+9j, 10+10j, 11+11j, 12+12j])                          # Rank 2
2025-07-17T07:05:38.7736960Z     tensor([13+13j, 14+14j, 15+15j, 16+16j])                        # Rank 3
2025-07-17T07:05:38.7737040Z     >>> output = torch.empty([4], dtype=torch.int64)
2025-07-17T07:05:38.7737140Z     >>> dist.all_to_all_single(output, input)
2025-07-17T07:05:38.7737180Z     >>> output
2025-07-17T07:05:38.7737280Z     tensor([1+1j, 5+5j, 9+9j, 13+13j])                              # Rank 0
2025-07-17T07:05:38.7737390Z     tensor([2+2j, 6+6j, 10+10j, 14+14j])                            # Rank 1
2025-07-17T07:05:38.7737490Z     tensor([3+3j, 7+7j, 11+11j, 15+15j])                            # Rank 2
2025-07-17T07:05:38.7737600Z     tensor([4+4j, 8+8j, 12+12j, 16+16j])                            # Rank 3
2025-07-17T07:05:38.7737600Z 
2025-07-17T07:05:38.7737750Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.7934830Z 
2025-07-17T07:05:38.7935380Z msg = Cannot scrape callname=all_to_all in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=4642.
2025-07-17T07:05:38.7935550Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.7935560Z 
2025-07-17T07:05:38.7935790Z Scatters list of input tensors to all processes in a group and return gathered list of tensors in output list.
2025-07-17T07:05:38.7935790Z 
2025-07-17T07:05:38.7935860Z Complex tensors are supported.
2025-07-17T07:05:38.7935910Z 
2025-07-17T07:05:38.7935950Z Args:
2025-07-17T07:05:38.7936090Z     output_tensor_list (list[Tensor]): List of tensors to be gathered one
2025-07-17T07:05:38.7936140Z         per rank.
2025-07-17T07:05:38.7936290Z     input_tensor_list (list[Tensor]): List of tensors to scatter one per rank.
2025-07-17T07:05:38.7936430Z     group (ProcessGroup, optional): The process group to work on. If None,
2025-07-17T07:05:38.7936510Z         the default process group will be used.
2025-07-17T07:05:38.7936630Z     async_op (bool, optional): Whether this op should be an async op.
2025-07-17T07:05:38.7936640Z 
2025-07-17T07:05:38.7936690Z Returns:
2025-07-17T07:05:38.7936770Z     Async work handle, if async_op is set to True.
2025-07-17T07:05:38.7936860Z     None, if not async_op or if not part of the group.
2025-07-17T07:05:38.7936860Z 
2025-07-17T07:05:38.7936910Z .. warning::
2025-07-17T07:05:38.7937000Z     `all_to_all` is experimental and subject to change.
2025-07-17T07:05:38.7937010Z 
2025-07-17T07:05:38.7937050Z Examples:
2025-07-17T07:05:38.7937130Z     >>> # xdoctest: +SKIP("Undefined rank")
2025-07-17T07:05:38.7937190Z     >>> input = torch.arange(4) + rank * 4
2025-07-17T07:05:38.7937250Z     >>> input = list(input.chunk(4))
2025-07-17T07:05:38.7937300Z     >>> input
2025-07-17T07:05:38.7937410Z     [tensor([0]), tensor([1]), tensor([2]), tensor([3])]     # Rank 0
2025-07-17T07:05:38.7937510Z     [tensor([4]), tensor([5]), tensor([6]), tensor([7])]     # Rank 1
2025-07-17T07:05:38.7937620Z     [tensor([8]), tensor([9]), tensor([10]), tensor([11])]   # Rank 2
2025-07-17T07:05:38.7937730Z     [tensor([12]), tensor([13]), tensor([14]), tensor([15])] # Rank 3
2025-07-17T07:05:38.7937840Z     >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4))
2025-07-17T07:05:38.7937910Z     >>> dist.all_to_all(output, input)
2025-07-17T07:05:38.7937950Z     >>> output
2025-07-17T07:05:38.7938060Z     [tensor([0]), tensor([4]), tensor([8]), tensor([12])]    # Rank 0
2025-07-17T07:05:38.7938160Z     [tensor([1]), tensor([5]), tensor([9]), tensor([13])]    # Rank 1
2025-07-17T07:05:38.7938260Z     [tensor([2]), tensor([6]), tensor([10]), tensor([14])]   # Rank 2
2025-07-17T07:05:38.7938360Z     [tensor([3]), tensor([7]), tensor([11]), tensor([15])]   # Rank 3
2025-07-17T07:05:38.7938360Z 
2025-07-17T07:05:38.7938470Z     >>> # Essentially, it is similar to following operation:
2025-07-17T07:05:38.7938530Z     >>> scatter_list = input
2025-07-17T07:05:38.7938590Z     >>> gather_list = output
2025-07-17T07:05:38.7938750Z     >>> for i in range(world_size):
2025-07-17T07:05:38.7938900Z     >>>     dist.scatter(gather_list[i], scatter_list if i == rank else [], src=i)
2025-07-17T07:05:38.7938900Z 
2025-07-17T07:05:38.7939000Z     >>> input
2025-07-17T07:05:38.7939100Z     tensor([0, 1, 2, 3, 4, 5])                                       # Rank 0
2025-07-17T07:05:38.7939190Z     tensor([10, 11, 12, 13, 14, 15, 16, 17, 18])                     # Rank 1
2025-07-17T07:05:38.7939290Z     tensor([20, 21, 22, 23, 24])                                     # Rank 2
2025-07-17T07:05:38.7939390Z     tensor([30, 31, 32, 33, 34, 35, 36])                             # Rank 3
2025-07-17T07:05:38.7939430Z     >>> input_splits
2025-07-17T07:05:38.7939510Z     [2, 2, 1, 1]                                                     # Rank 0
2025-07-17T07:05:38.7939590Z     [3, 2, 2, 2]                                                     # Rank 1
2025-07-17T07:05:38.7939730Z     [2, 1, 1, 1]                                                     # Rank 2
2025-07-17T07:05:38.7939870Z     [2, 2, 2, 1]                                                     # Rank 3
2025-07-17T07:05:38.7939920Z     >>> output_splits
2025-07-17T07:05:38.7940000Z     [2, 3, 2, 2]                                                     # Rank 0
2025-07-17T07:05:38.7940080Z     [2, 2, 1, 2]                                                     # Rank 1
2025-07-17T07:05:38.7940160Z     [1, 2, 1, 2]                                                     # Rank 2
2025-07-17T07:05:38.7940230Z     [1, 2, 1, 1]                                                     # Rank 3
2025-07-17T07:05:38.7940310Z     >>> input = list(input.split(input_splits))
2025-07-17T07:05:38.7940350Z     >>> input
2025-07-17T07:05:38.7940470Z     [tensor([0, 1]), tensor([2, 3]), tensor([4]), tensor([5])]                   # Rank 0
2025-07-17T07:05:38.7940600Z     [tensor([10, 11, 12]), tensor([13, 14]), tensor([15, 16]), tensor([17, 18])] # Rank 1
2025-07-17T07:05:38.7940720Z     [tensor([20, 21]), tensor([22]), tensor([23]), tensor([24])]                 # Rank 2
2025-07-17T07:05:38.7940840Z     [tensor([30, 31]), tensor([32, 33]), tensor([34, 35]), tensor([36])]         # Rank 3
2025-07-17T07:05:38.7940890Z     >>> output = ...
2025-07-17T07:05:38.7940950Z     >>> dist.all_to_all(output, input)
2025-07-17T07:05:38.7941000Z     >>> output
2025-07-17T07:05:38.7941120Z     [tensor([0, 1]), tensor([10, 11, 12]), tensor([20, 21]), tensor([30, 31])]   # Rank 0
2025-07-17T07:05:38.7941240Z     [tensor([2, 3]), tensor([13, 14]), tensor([22]), tensor([32, 33])]           # Rank 1
2025-07-17T07:05:38.7941360Z     [tensor([4]), tensor([15, 16]), tensor([23]), tensor([34, 35])]              # Rank 2
2025-07-17T07:05:38.7941480Z     [tensor([5]), tensor([17, 18]), tensor([24]), tensor([36])]                  # Rank 3
2025-07-17T07:05:38.7941480Z 
2025-07-17T07:05:38.7941580Z     >>> # Another example with tensors of torch.cfloat type.
2025-07-17T07:05:38.7941640Z     >>> input = torch.tensor(
2025-07-17T07:05:38.7941730Z     ...     [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat
2025-07-17T07:05:38.7941780Z     ... ) + 4 * rank * (1 + 1j)
2025-07-17T07:05:38.7941840Z     >>> input = list(input.chunk(4))
2025-07-17T07:05:38.7941890Z     >>> input
2025-07-17T07:05:38.7942020Z     [tensor([1+1j]), tensor([2+2j]), tensor([3+3j]), tensor([4+4j])]            # Rank 0
2025-07-17T07:05:38.7942140Z     [tensor([5+5j]), tensor([6+6j]), tensor([7+7j]), tensor([8+8j])]            # Rank 1
2025-07-17T07:05:38.7942280Z     [tensor([9+9j]), tensor([10+10j]), tensor([11+11j]), tensor([12+12j])]      # Rank 2
2025-07-17T07:05:38.7942400Z     [tensor([13+13j]), tensor([14+14j]), tensor([15+15j]), tensor([16+16j])]    # Rank 3
2025-07-17T07:05:38.7942520Z     >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4))
2025-07-17T07:05:38.7942580Z     >>> dist.all_to_all(output, input)
2025-07-17T07:05:38.7942620Z     >>> output
2025-07-17T07:05:38.7942770Z     [tensor([1+1j]), tensor([5+5j]), tensor([9+9j]), tensor([13+13j])]          # Rank 0
2025-07-17T07:05:38.7942900Z     [tensor([2+2j]), tensor([6+6j]), tensor([10+10j]), tensor([14+14j])]        # Rank 1
2025-07-17T07:05:38.7943020Z     [tensor([3+3j]), tensor([7+7j]), tensor([11+11j]), tensor([15+15j])]        # Rank 2
2025-07-17T07:05:38.7943210Z     [tensor([4+4j]), tensor([8+8j]), tensor([12+12j]), tensor([16+16j])]        # Rank 3
2025-07-17T07:05:38.7943210Z 
2025-07-17T07:05:38.7943220Z 
2025-07-17T07:05:38.7943370Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.7943370Z 
2025-07-17T07:05:38.7943740Z msg = Cannot scrape callname=__doc__ in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/launch.py line=2.
2025-07-17T07:05:38.7943890Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.7943890Z 
2025-07-17T07:05:38.7944010Z Module ``torch.distributed.launch``.
2025-07-17T07:05:38.7944060Z 
2025-07-17T07:05:38.7944210Z ``torch.distributed.launch`` is a module that spawns up multiple distributed
2025-07-17T07:05:38.7944310Z training processes on each of the training nodes.
2025-07-17T07:05:38.7944310Z 
2025-07-17T07:05:38.7944350Z .. warning::
2025-07-17T07:05:38.7944360Z 
2025-07-17T07:05:38.7944510Z     This module is going to be deprecated in favor of :ref:`torchrun <launcher-api>`.
2025-07-17T07:05:38.7944510Z 
2025-07-17T07:05:38.7944650Z The utility can be used for single-node distributed training, in which one or
2025-07-17T07:05:38.7944800Z more processes per node will be spawned. The utility can be used for either
2025-07-17T07:05:38.7944930Z CPU training or GPU training. If the utility is used for GPU training,
2025-07-17T07:05:38.7945070Z each distributed process will be operating on a single GPU. This can achieve
2025-07-17T07:05:38.7945210Z well-improved single-node training performance. It can also be used in
2025-07-17T07:05:38.7945370Z multi-node distributed training, by spawning up multiple processes on each node
2025-07-17T07:05:38.7945510Z for well-improved multi-node distributed training performance as well.
2025-07-17T07:05:38.7945650Z This will especially be beneficial for systems with multiple Infiniband
2025-07-17T07:05:38.7945810Z interfaces that have direct-GPU support, since all of them can be utilized for
2025-07-17T07:05:38.7945870Z aggregated communication bandwidth.
2025-07-17T07:05:38.7945870Z 
2025-07-17T07:05:38.7946030Z In both cases of single-node distributed training or multi-node distributed
2025-07-17T07:05:38.7946170Z training, this utility will launch the given number of processes per node
2025-07-17T07:05:38.7946310Z (``--nproc-per-node``). If used for GPU training, this number needs to be less
2025-07-17T07:05:38.7946440Z or equal to the number of GPUs on the current system (``nproc_per_node``),
2025-07-17T07:05:38.7946570Z and each process will be operating on a single GPU from *GPU 0 to
2025-07-17T07:05:38.7946630Z GPU (nproc_per_node - 1)*.
2025-07-17T07:05:38.7946630Z 
2025-07-17T07:05:38.7946690Z **How to use this module:**
2025-07-17T07:05:38.7946690Z 
2025-07-17T07:05:38.7946780Z 1. Single-Node multi-process distributed training
2025-07-17T07:05:38.7946780Z 
2025-07-17T07:05:38.7946830Z ::
2025-07-17T07:05:38.7946830Z 
2025-07-17T07:05:38.7946970Z     python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE
2025-07-17T07:05:38.7947100Z                YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 and all other
2025-07-17T07:05:38.7947170Z                arguments of your training script)
2025-07-17T07:05:38.7947170Z 
2025-07-17T07:05:38.7947300Z 2. Multi-Node multi-process distributed training: (e.g. two nodes)
2025-07-17T07:05:38.7947300Z 
2025-07-17T07:05:38.7947300Z 
2025-07-17T07:05:38.7947390Z Node 1: *(IP: 192.168.1.1, and has a free port: 1234)*
2025-07-17T07:05:38.7947390Z 
2025-07-17T07:05:38.7947440Z ::
2025-07-17T07:05:38.7947440Z 
2025-07-17T07:05:38.7947580Z     python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE
2025-07-17T07:05:38.7947700Z                --nnodes=2 --node-rank=0 --master-addr="192.168.1.1"
2025-07-17T07:05:38.7947840Z                --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3
2025-07-17T07:05:38.7947930Z                and all other arguments of your training script)
2025-07-17T07:05:38.7947960Z 
2025-07-17T07:05:38.7948000Z Node 2:
2025-07-17T07:05:38.7948000Z 
2025-07-17T07:05:38.7948050Z ::
2025-07-17T07:05:38.7948050Z 
2025-07-17T07:05:38.7948190Z     python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE
2025-07-17T07:05:38.7948290Z                --nnodes=2 --node-rank=1 --master-addr="192.168.1.1"
2025-07-17T07:05:38.7948410Z                --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3
2025-07-17T07:05:38.7948500Z                and all other arguments of your training script)
2025-07-17T07:05:38.7948510Z 
2025-07-17T07:05:38.7948670Z 3. To look up what optional arguments this module offers:
2025-07-17T07:05:38.7948730Z 
2025-07-17T07:05:38.7948780Z ::
2025-07-17T07:05:38.7948780Z 
2025-07-17T07:05:38.7948870Z     python -m torch.distributed.launch --help
2025-07-17T07:05:38.7948870Z 
2025-07-17T07:05:38.7948870Z 
2025-07-17T07:05:38.7948920Z **Important Notices:**
2025-07-17T07:05:38.7948930Z 
2025-07-17T07:05:38.7949040Z 1. This utility and multi-process distributed (single-node or
2025-07-17T07:05:38.7949190Z multi-node) GPU training currently only achieves the best performance using
2025-07-17T07:05:38.7949340Z the NCCL distributed backend. Thus NCCL backend is the recommended backend to
2025-07-17T07:05:38.7949390Z use for GPU training.
2025-07-17T07:05:38.7949390Z 
2025-07-17T07:05:38.7949520Z 2. In your training program, you must parse the command-line argument:
2025-07-17T07:05:38.7949670Z ``--local-rank=LOCAL_PROCESS_RANK``, which will be provided by this module.
2025-07-17T07:05:38.7949800Z If your training program uses GPUs, you should ensure that your code only
2025-07-17T07:05:38.7949920Z runs on the GPU device of LOCAL_PROCESS_RANK. This can be done by:
2025-07-17T07:05:38.7949930Z 
2025-07-17T07:05:38.7949990Z Parsing the local_rank argument
2025-07-17T07:05:38.7949990Z 
2025-07-17T07:05:38.7950030Z ::
2025-07-17T07:05:38.7950040Z 
2025-07-17T07:05:38.7950090Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:38.7950140Z     >>> import argparse
2025-07-17T07:05:38.7950210Z     >>> parser = argparse.ArgumentParser()
2025-07-17T07:05:38.7950330Z     >>> parser.add_argument("--local-rank", "--local_rank", type=int)
2025-07-17T07:05:38.7950390Z     >>> args = parser.parse_args()
2025-07-17T07:05:38.7950390Z 
2025-07-17T07:05:38.7950460Z Set your device to local rank using either
2025-07-17T07:05:38.7950470Z 
2025-07-17T07:05:38.7950510Z ::
2025-07-17T07:05:38.7950510Z 
2025-07-17T07:05:38.7950630Z     >>> torch.cuda.set_device(args.local_rank)  # before your code runs
2025-07-17T07:05:38.7950630Z 
2025-07-17T07:05:38.7950670Z or
2025-07-17T07:05:38.7950680Z 
2025-07-17T07:05:38.7950720Z ::
2025-07-17T07:05:38.7950720Z 
2025-07-17T07:05:38.7950800Z     >>> with torch.cuda.device(args.local_rank):
2025-07-17T07:05:38.7950850Z     >>>    # your code to run
2025-07-17T07:05:38.7950900Z     >>>    ...
2025-07-17T07:05:38.7950900Z 
2025-07-17T07:05:38.7950950Z .. versionchanged:: 2.0.0
2025-07-17T07:05:38.7950960Z 
2025-07-17T07:05:38.7951100Z     The launcher will passes the ``--local-rank=<rank>`` argument to your script.
2025-07-17T07:05:38.7951250Z     From PyTorch 2.0.0 onwards, the dashed ``--local-rank`` is preferred over the
2025-07-17T07:05:38.7951330Z     previously used underscored ``--local_rank``.
2025-07-17T07:05:38.7951330Z 
2025-07-17T07:05:38.7951470Z     For backward compatibility, it may be necessary for users to handle both
2025-07-17T07:05:38.7951630Z     cases in their argument parsing code. This means including both ``"--local-rank"``
2025-07-17T07:05:38.7951760Z     and ``"--local_rank"`` in the argument parser. If only ``"--local_rank"`` is
2025-07-17T07:05:38.7951920Z     provided, the launcher will trigger an error: "error: unrecognized arguments:
2025-07-17T07:05:38.7952070Z     --local-rank=<rank>". For training code that only supports PyTorch 2.0.0+,
2025-07-17T07:05:38.7952170Z     including ``"--local-rank"`` should be sufficient.
2025-07-17T07:05:38.7952190Z 
2025-07-17T07:05:38.7952330Z 3. In your training program, you are supposed to call the following function
2025-07-17T07:05:38.7952480Z at the beginning to start the distributed backend. It is strongly recommended
2025-07-17T07:05:38.7952620Z that ``init_method=env://``. Other init methods (e.g. ``tcp://``) may work,
2025-07-17T07:05:38.7952740Z but ``env://`` is the one that is officially supported by this module.
2025-07-17T07:05:38.7952740Z 
2025-07-17T07:05:38.7952790Z ::
2025-07-17T07:05:38.7952790Z 
2025-07-17T07:05:38.7952920Z     >>> torch.distributed.init_process_group(backend='YOUR BACKEND',
2025-07-17T07:05:38.7953020Z     >>>                                      init_method='env://')
2025-07-17T07:05:38.7953080Z 
2025-07-17T07:05:38.7953280Z 4. In your training program, you can either use regular distributed functions
2025-07-17T07:05:38.7953420Z or use :func:`torch.nn.parallel.DistributedDataParallel` module. If your
2025-07-17T07:05:38.7953550Z training program uses GPUs for training and you would like to use
2025-07-17T07:05:38.7953660Z :func:`torch.nn.parallel.DistributedDataParallel` module,
2025-07-17T07:05:38.7953730Z here is how to configure it.
2025-07-17T07:05:38.7953730Z 
2025-07-17T07:05:38.7953770Z ::
2025-07-17T07:05:38.7953770Z 
2025-07-17T07:05:38.7953890Z     >>> model = torch.nn.parallel.DistributedDataParallel(model,
2025-07-17T07:05:38.7953980Z     >>>                                                   device_ids=[args.local_rank],
2025-07-17T07:05:38.7954070Z     >>>                                                   output_device=args.local_rank)
2025-07-17T07:05:38.7954070Z 
2025-07-17T07:05:38.7954220Z Please ensure that ``device_ids`` argument is set to be the only GPU device id
2025-07-17T07:05:38.7954360Z that your code will be operating on. This is generally the local rank of the
2025-07-17T07:05:38.7954510Z process. In other words, the ``device_ids`` needs to be ``[args.local_rank]``,
2025-07-17T07:05:38.7954640Z and ``output_device`` needs to be ``args.local_rank`` in order to use this
2025-07-17T07:05:38.7954690Z utility
2025-07-17T07:05:38.7954690Z 
2025-07-17T07:05:38.7954840Z 5. Another way to pass ``local_rank`` to the subprocesses via environment variable
2025-07-17T07:05:38.7954960Z ``LOCAL_RANK``. This behavior is enabled when you launch the script with
2025-07-17T07:05:38.7955100Z ``--use-env=True``. You must adjust the subprocess example above to replace
2025-07-17T07:05:38.7955220Z ``args.local_rank`` with ``os.environ['LOCAL_RANK']``; the launcher
2025-07-17T07:05:38.7955320Z will not pass ``--local-rank`` when you specify this flag.
2025-07-17T07:05:38.7955330Z 
2025-07-17T07:05:38.7955370Z .. warning::
2025-07-17T07:05:38.7955370Z 
2025-07-17T07:05:38.7955500Z     ``local_rank`` is NOT globally unique: it is only unique per process
2025-07-17T07:05:38.7955610Z     on a machine.  Thus, don't use it to decide if you should, e.g.,
2025-07-17T07:05:38.7955680Z     write to a networked filesystem.  See
2025-07-17T07:05:38.7955810Z     https://github.com/pytorch/pytorch/issues/12042 for an example of
2025-07-17T07:05:38.7955910Z     how things can go wrong if you don't do this correctly.
2025-07-17T07:05:38.7955920Z 
2025-07-17T07:05:38.7955920Z 
2025-07-17T07:05:38.7955920Z 
2025-07-17T07:05:38.7955920Z 
2025-07-17T07:05:38.7956070Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.8129060Z 
2025-07-17T07:05:38.8129730Z msg = Cannot scrape callname=DeviceMesh.__getitem__ in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/device_mesh.py line=685.
2025-07-17T07:05:38.8129900Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:38.8129910Z 
2025-07-17T07:05:38.8130220Z Slice the current DeviceMesh based on the mesh_dim_names given to create a submesh.
2025-07-17T07:05:38.8130400Z The submesh created consists of the dimensions and the communicators indicated by
2025-07-17T07:05:38.8130450Z ``mesh_dim_names``
2025-07-17T07:05:38.8130490Z 
2025-07-17T07:05:38.8130540Z Args:
2025-07-17T07:05:38.8130690Z     mesh_dim_names (Union[str, Tuple[str]]): the name or the tuple of names of the
2025-07-17T07:05:38.8130810Z     mesh dimension of the DeviceMesh to create the submesh for.
2025-07-17T07:05:38.8130860Z Returns:
2025-07-17T07:05:38.8130920Z     A :class:`DeviceMesh` object
2025-07-17T07:05:38.8130920Z 
2025-07-17T07:05:38.8131110Z The following program runs on each process/rank in an SPMD manner in a world size of 8.
2025-07-17T07:05:38.8131160Z In the first example:
2025-07-17T07:05:38.8131350Z     Calling mesh_2d["tp"] on rank 0, 1, 2, 3 returns a 1D submesh of DeviceMesh:([0, 1, 2, 3]).
2025-07-17T07:05:38.8131640Z     Calling mesh_2d["tp"] on rank 4, 5, 6, 7 returns a 1D submesh of  DeviceMesh:([4, 5, 6, 7]).
2025-07-17T07:05:38.8131850Z     Calling mesh_2d["dp"] on rank 0, 4 returns a 1D submesh of  DeviceMesh:([0, 4]).
2025-07-17T07:05:38.8131990Z     Calling mesh_2d["dp"] on rank 1, 5 returns a 1D submesh of  DeviceMesh:([1, 5]).
2025-07-17T07:05:38.8132130Z     Calling mesh_2d["dp"] on rank 2, 6 returns a 1D submesh of  DeviceMesh:([2, 6]).
2025-07-17T07:05:38.8132270Z     Calling mesh_2d["dp"] on rank 3, 7 returns a 1D submesh of  DeviceMesh:([3, 7]).
2025-07-17T07:05:38.8132270Z 
2025-07-17T07:05:38.8132320Z In the second example:
2025-07-17T07:05:38.8132500Z     Calling mesh_3d["dp", "cp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 1], [4, 5]]).
2025-07-17T07:05:38.8132660Z     Calling mesh_3d["dp", "cp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 3], [6, 7]]).
2025-07-17T07:05:38.8132830Z     Calling mesh_3d["cp", "dp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 4], [1, 5]]).
2025-07-17T07:05:38.8132980Z     Calling mesh_3d["cp", "dp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 6], [3, 7]]).
2025-07-17T07:05:38.8132980Z 
2025-07-17T07:05:38.8133040Z Example::
2025-07-17T07:05:38.8133040Z 
2025-07-17T07:05:38.8133100Z     >>> # xdoctest: +SKIP("no rank")
2025-07-17T07:05:38.8133220Z     >>> from torch.distributed.device_mesh import DeviceMesh
2025-07-17T07:05:38.8133260Z     >>>
2025-07-17T07:05:38.8133390Z     >>> # Initialize a 2D device mesh as (2, 4) to represent the topology
2025-07-17T07:05:38.8133470Z     >>> # of cross-host(dim 0), and within-host (dim 1).
2025-07-17T07:05:38.8133630Z     >>> mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))
2025-07-17T07:05:38.8133690Z     >>> tp_mesh = mesh_2d["tp"]
2025-07-17T07:05:38.8133740Z     >>> dp_mesh = mesh_2d["dp"]
2025-07-17T07:05:38.8133780Z     >>>
2025-07-17T07:05:38.8133840Z     >>> # Initialize a 3D mesh.
2025-07-17T07:05:38.8134010Z     >>> mesh_3d = init_device_mesh(device_type="cuda", (2,2,2), mesh_dim_names=("dp", "pp", "cp"))
2025-07-17T07:05:38.8134190Z     >>> # The order of the mesh_dim_names provided deteremines the order of dimensions in the submesh.
2025-07-17T07:05:38.8134260Z     >>> dp_cp_mesh = mesh_3d["dp", "cp"]
2025-07-17T07:05:38.8134320Z     >>> cp_dp_mesh = mesh_3d["cp", "dp"]
2025-07-17T07:05:38.8134320Z 
2025-07-17T07:05:38.8134710Z Original Error: SyntaxError('positional argument follows keyword argument', ('<source_block>', 6, 82, 'mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))\n', 6, 83))
2025-07-17T07:05:38.8134720Z 
2025-07-17T07:05:38.8134870Z mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))
2025-07-17T07:05:38.8134940Z                                                                                  ^
2025-07-17T07:05:38.8135430Z msg = Cannot scrape callname=BroadcastingTorchSaveReader in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/format_utils.py line=40.
2025-07-17T07:05:38.8135610Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.8135610Z 
2025-07-17T07:05:38.8135790Z StorageReader for reading a Torch Save file. This reader will read the entire checkpoint
2025-07-17T07:05:38.8136010Z on the coordinator rank, and then broadcast and shard each tensor to all ranks.
2025-07-17T07:05:38.8136010Z 
2025-07-17T07:05:38.8136110Z . N.B. Intended to be used with DynamicMetaLoadPlanner
2025-07-17T07:05:38.8136110Z 
2025-07-17T07:05:38.8136160Z .. warning::
2025-07-17T07:05:38.8136260Z     Current implementation only supports loading Tensors.
2025-07-17T07:05:38.8136270Z 
2025-07-17T07:05:38.8136330Z >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:38.8136380Z >>> sd = {"mode": model}
2025-07-17T07:05:38.8136430Z >>> dcp.load(
2025-07-17T07:05:38.8136470Z >>>    sd,
2025-07-17T07:05:38.8136560Z >>>    storage_reader=BroadcastingTorchSaveReader(),
2025-07-17T07:05:38.8136690Z >>>    planner=DynamicMetaLoadPlanner(),
2025-07-17T07:05:38.8136810Z >>>    checkpoint_id="path_to_model.pt"
2025-07-17T07:05:38.8136850Z >>> )
2025-07-17T07:05:38.8136850Z 
2025-07-17T07:05:38.8137010Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.8137010Z 
2025-07-17T07:05:38.8137470Z msg = Cannot scrape callname=DynamicMetaLoadPlanner in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/format_utils.py line=151.
2025-07-17T07:05:38.8137630Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.8137630Z 
2025-07-17T07:05:38.8137840Z Extension of DefaultLoadPlanner, which creates a new Metadata object based on the passed in state dict,
2025-07-17T07:05:38.8138040Z avoiding the need to read metadata from disk. This is useful when reading formats which don't have a
2025-07-17T07:05:38.8138100Z metadata file, like Torch Save files.
2025-07-17T07:05:38.8138100Z 
2025-07-17T07:05:38.8138220Z . N.B. Intended to be used with BroadcastingTorchSaveReader
2025-07-17T07:05:38.8138220Z 
2025-07-17T07:05:38.8138260Z .. warning::
2025-07-17T07:05:38.8138360Z     Current implementation only supports loading Tensors.
2025-07-17T07:05:38.8138370Z 
2025-07-17T07:05:38.8138430Z >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:38.8138480Z >>> sd = {"mode": model}
2025-07-17T07:05:38.8138530Z >>> dcp.load(
2025-07-17T07:05:38.8138570Z >>>    sd,
2025-07-17T07:05:38.8138660Z >>>    storage_reader=BroadcastingTorchSaveReader(),
2025-07-17T07:05:38.8138730Z >>>    planner=DynamicMetaLoadPlanner(),
2025-07-17T07:05:38.8138790Z >>>    checkpoint_id="path_to_model.pt"
2025-07-17T07:05:38.8138830Z >>> )
2025-07-17T07:05:38.8138840Z 
2025-07-17T07:05:38.8138990Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.8138990Z 
2025-07-17T07:05:38.8139400Z msg = Cannot scrape callname=SavePlanner in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/planner.py line=122.
2025-07-17T07:05:38.8139560Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.8139560Z 
2025-07-17T07:05:38.8139730Z Abstract class defining the protocol used by save_state_dict to plan the save process.
2025-07-17T07:05:38.8139740Z 
2025-07-17T07:05:38.8139910Z SavePlanners are stateful objects that can be used to customize the whole save process.
2025-07-17T07:05:38.8139910Z 
2025-07-17T07:05:38.8140080Z SavePlanner acts as an access proxy to the state_dict, so any transformation done to it
2025-07-17T07:05:38.8140140Z will be visible to the whole process.
2025-07-17T07:05:38.8140140Z 
2025-07-17T07:05:38.8140310Z A planner subclass can expect the following sequence of calls during save_state_dict:
2025-07-17T07:05:38.8140310Z 
2025-07-17T07:05:38.8140380Z 1) set_up_planner - called on all ranks.
2025-07-17T07:05:38.8140450Z     Signals the start of a checkpoint save.
2025-07-17T07:05:38.8140450Z 
2025-07-17T07:05:38.8140550Z 2) create_local_plan - called on all ranks.
2025-07-17T07:05:38.8140730Z     Process the state_dict and produces a `SavePlan` that will be sent for global planning.
2025-07-17T07:05:38.8140730Z 
2025-07-17T07:05:38.8140860Z 3) create_global_plan - called on the coordinator rank only.
2025-07-17T07:05:38.8140980Z     Takes the SavePlan from all ranks and make any global decision.
2025-07-17T07:05:38.8140980Z 
2025-07-17T07:05:38.8141050Z 4) finish_plan - called on all ranks.
2025-07-17T07:05:38.8141180Z     This gives each rank a chance to adjust to global planning decisions.
2025-07-17T07:05:38.8141180Z 
2025-07-17T07:05:38.8141270Z 5) resolve_data - called multiple times on each rank
2025-07-17T07:05:38.8141400Z     Lookups a value on the `state_dict` for the storage layer to write.
2025-07-17T07:05:38.8141400Z 
2025-07-17T07:05:38.8141680Z Users are recommended to extend DefaultSavePlanner instead of this interface directly as
2025-07-17T07:05:38.8141850Z most changes can be expressed by changes in a single method.
2025-07-17T07:05:38.8141850Z 
2025-07-17T07:05:38.8141920Z There are 3 usual patterns of extension:
2025-07-17T07:05:38.8141920Z 
2025-07-17T07:05:38.8142080Z Rewriting state_dict. This is the simplest way to extend the save process as it
2025-07-17T07:05:38.8142210Z doesn't requite understanding the intrincacies of how SavePlan works:
2025-07-17T07:05:38.8142220Z 
2025-07-17T07:05:38.8142280Z >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:38.8142360Z >>> class RenamePlanner(DefaultSavePlanner):
2025-07-17T07:05:38.8142410Z >>>     def set_up_planner(
2025-07-17T07:05:38.8142460Z >>>         self,
2025-07-17T07:05:38.8142520Z >>>         state_dict: STATE_DICT_TYPE,
2025-07-17T07:05:38.8142600Z >>>         storage_meta: Optional[StorageMeta],
2025-07-17T07:05:38.8142650Z >>>         is_coordinator: bool,
2025-07-17T07:05:38.8142700Z >>>     ) -> None:
2025-07-17T07:05:38.8142760Z >>> # prefix all keys with `foo_``
2025-07-17T07:05:38.8142950Z >>>         super().set_up_planner({"foo_" + k: v for k, v in state_dict.items()}, storage_meta, is_coordinator)
2025-07-17T07:05:38.8142950Z 
2025-07-17T07:05:38.8143150Z Modifying local plan and lookup in tandem. This is useful when fine control of how data is persisted
2025-07-17T07:05:38.8143150Z 
2025-07-17T07:05:38.8143220Z >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:38.8143290Z >>> class FP16Planner(DefaultSavePlanner):
2025-07-17T07:05:38.8143350Z >>>     def create_local_plan(self):
2025-07-17T07:05:38.8143420Z >>>         plan = super().create_local_plan()
2025-07-17T07:05:38.8143470Z >>>         for p in plan:
2025-07-17T07:05:38.8143530Z >>>             if p.tensor_data is not None:
2025-07-17T07:05:38.8143640Z >>>                 p.tensor_data.properties.dtype = torch.float16
2025-07-17T07:05:38.8143690Z >>>         return plan
2025-07-17T07:05:38.8143730Z >>>
2025-07-17T07:05:38.8143790Z >>>     def resolve_data(self, write_item):
2025-07-17T07:05:38.8143870Z >>>         item = super().resolve_data(write_item)
2025-07-17T07:05:38.8144040Z >>>         return item if write_item.type == WriteItemType.BYTE_IO else item.to(torch.float16)
2025-07-17T07:05:38.8144040Z 
2025-07-17T07:05:38.8144240Z Using the global planning step to make central decisions that can't be made individually by each rank
2025-07-17T07:05:38.8144250Z 
2025-07-17T07:05:38.8144310Z >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:38.8144370Z >>> from itertools import zip_longest
2025-07-17T07:05:38.8144440Z >>> from dataclasses import replace
2025-07-17T07:05:38.8144540Z >>> class DDPLoadBalancingPlanner(DefaultSavePlanner):
2025-07-17T07:05:38.8144700Z >>> # This uses the default local plan behavior of having all non-sharded writes in rank 0
2025-07-17T07:05:38.8144780Z >>> # This sample doesn't handle ShardedTensors
2025-07-17T07:05:38.8144860Z >>>     def create_global_plan(self, all_plans):
2025-07-17T07:05:38.8144950Z >>>         iters = [iter(all_plans[0].items)] * len(all_plans)
2025-07-17T07:05:38.8145010Z >>>         items_per_rank = [
2025-07-17T07:05:38.8145110Z >>>             [item for item in items if item is not None]
2025-07-17T07:05:38.8145220Z >>>             for items in zip(*zip_longest(*iters), strict=True)
2025-07-17T07:05:38.8145290Z >>>         ]
2025-07-17T07:05:38.8145340Z >>>         all_plans = [
2025-07-17T07:05:38.8145400Z >>>             replace(plan, items=items)
2025-07-17T07:05:38.8145520Z >>>             for plan, items in zip(all_plans, items_per_rank, strict=True)
2025-07-17T07:05:38.8145560Z >>>         ]
2025-07-17T07:05:38.8145650Z >>>         return super().create_global_plan(all_plans)
2025-07-17T07:05:38.8145650Z 
2025-07-17T07:05:38.8145810Z Finally, some planners need to save additional metadata in the checkpoint, this is
2025-07-17T07:05:38.8145960Z accomplished by having each rank contribute their data items in the local plan and
2025-07-17T07:05:38.8146030Z the global planner aggregate them:
2025-07-17T07:05:38.8146030Z 
2025-07-17T07:05:38.8146150Z >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:38.8146310Z >>> class SaveExtraDataPlanner(DefaultSavePlanner):
2025-07-17T07:05:38.8146380Z >>>     def create_local_plan(self) -> SavePlan:
2025-07-17T07:05:38.8146450Z >>>         plan = super().create_local_plan()
2025-07-17T07:05:38.8146550Z >>>         return replace(plan, planner_data="per-rank-data")
2025-07-17T07:05:38.8146600Z >>>
2025-07-17T07:05:38.8146780Z >>>     def create_global_plan(self, all_plans: List[SavePlan]) -> Tuple[List[SavePlan], Metadata]:
2025-07-17T07:05:38.8146900Z >>>         global_plan, metadata = super().create_global_plan(all_plans)
2025-07-17T07:05:38.8146990Z >>>         merged_data = [p.planner_data for p in global_plan]
2025-07-17T07:05:38.8147100Z >>>         metadata = replace(metadata, planner_data=merged_data)
2025-07-17T07:05:38.8147160Z >>>         return global_plan, metadata
2025-07-17T07:05:38.8147160Z 
2025-07-17T07:05:38.8147320Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.8291870Z 
2025-07-17T07:05:38.8292440Z msg = Cannot scrape callname=LoadPlanner in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/planner.py line=305.
2025-07-17T07:05:38.8292640Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.8292640Z 
2025-07-17T07:05:38.8292820Z Abstract class defining the protocol used by load_state_dict to plan the load process.
2025-07-17T07:05:38.8292820Z 
2025-07-17T07:05:38.8292990Z LoadPlanner are stateful objects that can be used to customize the whole load process.
2025-07-17T07:05:38.8293000Z 
2025-07-17T07:05:38.8293170Z LoadPlanner acts as an access proxy to the state_dict, so any transformation done to it
2025-07-17T07:05:38.8293240Z will be visible to the whole process.
2025-07-17T07:05:38.8293240Z 
2025-07-17T07:05:38.8293410Z A planner subclass can expect the following sequence of calls during load_state_dict:
2025-07-17T07:05:38.8293410Z 
2025-07-17T07:05:38.8293480Z 1) set_up_planner - called on all ranks.
2025-07-17T07:05:38.8293560Z     Signals the start of loading a checkpoint.
2025-07-17T07:05:38.8293560Z 
2025-07-17T07:05:38.8293630Z 2) create_local_plan - called on all ranks.
2025-07-17T07:05:38.8293810Z     Process the state_dict and produces a `LoadPlan` that will be sent for global planning.
2025-07-17T07:05:38.8293820Z 
2025-07-17T07:05:38.8293930Z 3) create_global_plan - called on the coordinator rank only.
2025-07-17T07:05:38.8294050Z     Takes the LoadPlan from all ranks and make any global decision.
2025-07-17T07:05:38.8294060Z 
2025-07-17T07:05:38.8294140Z 4) load_bytes - called multiple times on each rank
2025-07-17T07:05:38.8294250Z     This is called once per non-tensor value in state_dict.
2025-07-17T07:05:38.8294250Z 
2025-07-17T07:05:38.8294390Z 5) resolve_tensor and commit_tensor - called multiple times on each rank
2025-07-17T07:05:38.8294500Z     They are called in pair for each Tensor value in state_dict.
2025-07-17T07:05:38.8294510Z 
2025-07-17T07:05:38.8294760Z Users are recommended to extend DefaultLoadPlanner instead of this interface directly as
2025-07-17T07:05:38.8294880Z most changes can be expressed by changes in a single method.
2025-07-17T07:05:38.8294910Z 
2025-07-17T07:05:38.8294980Z There are two usual patterns of extension:
2025-07-17T07:05:38.8294980Z 
2025-07-17T07:05:38.8295140Z Rewriting state_dict. This is the simplest way to extend the load process as it
2025-07-17T07:05:38.8295300Z doesn't requite understanding the intrincacies of how LoadPlan works. We need
2025-07-17T07:05:38.8295440Z to keep a reference to the original state_dict as load happens in place so
2025-07-17T07:05:38.8295510Z we need to be able to perform it in place
2025-07-17T07:05:38.8295520Z 
2025-07-17T07:05:38.8295580Z >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:38.8295660Z >>> class RenamePlanner(DefaultLoadPlanner):
2025-07-17T07:05:38.8295720Z >>>     def set_up_planner(
2025-07-17T07:05:38.8295860Z >>>         self,
2025-07-17T07:05:38.8295990Z >>>         state_dict: STATE_DICT_TYPE,
2025-07-17T07:05:38.8296040Z >>>         metadata: Metadata,
2025-07-17T07:05:38.8296100Z >>>         is_coordinator: bool,
2025-07-17T07:05:38.8296140Z >>>     ) -> None:
2025-07-17T07:05:38.8296220Z >>>         self.original_state_dict = state_dict
2025-07-17T07:05:38.8296330Z >>>         state_dict = {"foo_" + k: v for k, v in state_dict.items()}
2025-07-17T07:05:38.8296370Z >>>
2025-07-17T07:05:38.8296440Z >>>         if self.flatten_sharded_tensors:
2025-07-17T07:05:38.8296530Z >>>             state_dict = _flatten_sharded_tensors(state_dict)
2025-07-17T07:05:38.8296580Z >>>
2025-07-17T07:05:38.8296640Z >>>         if self.flatten_state_dict:
2025-07-17T07:05:38.8296750Z >>>             state_dict, self.mappings = flatten_state_dict(state_dict)
2025-07-17T07:05:38.8296790Z >>>
2025-07-17T07:05:38.8296860Z >>>         self.state_dict = state_dict
2025-07-17T07:05:38.8296910Z >>>         self.metadata = metadata
2025-07-17T07:05:38.8297110Z >>>         self.is_coordinator = is_coordinator
2025-07-17T07:05:38.8297190Z >>>
2025-07-17T07:05:38.8297350Z >>>     def load_bytes(self, read_item, value):
2025-07-17T07:05:38.8297410Z >>> # Remove the "foo_" prefix
2025-07-17T07:05:38.8304010Z >>>         self.original_state_dict[read_item.dest_index.fqn[4:]] = torch.load(value, weights_only=False)
2025-07-17T07:05:38.8304020Z 
2025-07-17T07:05:38.8304020Z 
2025-07-17T07:05:38.8304190Z Modifying resolve_tensor and commit_tensor to handle load time transformation.
2025-07-17T07:05:38.8304190Z 
2025-07-17T07:05:38.8304250Z >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:38.8304350Z >>> class MetaModelMaterialize(DefaultSavePlanner):
2025-07-17T07:05:38.8304420Z >>>     def resolve_tensor(self, read_item):
2025-07-17T07:05:38.8304490Z >>>         tensor = super().resolve_tensor(read_item)
2025-07-17T07:05:38.8304580Z >>>         return torch.empty_like(tensor, device="cpu")
2025-07-17T07:05:38.8304620Z >>>
2025-07-17T07:05:38.8304700Z >>>     def commit_tensor(self, read_item, tensor):
2025-07-17T07:05:38.8304800Z >>>         self.state_dict[read_item.dest_index.fqn] = tensor
2025-07-17T07:05:38.8304800Z 
2025-07-17T07:05:38.8304950Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.8304960Z 
2025-07-17T07:05:38.8305380Z msg = Cannot scrape callname=get_state_dict in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict.py line=1118.
2025-07-17T07:05:38.8305560Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.8305560Z 
2025-07-17T07:05:38.8305650Z Return the model state_dict and optimizers state_dict.
2025-07-17T07:05:38.8305660Z 
2025-07-17T07:05:38.8305790Z ``get_state_dict`` can process any module that is parallelized by PyTorch
2025-07-17T07:05:38.8305940Z FSDP/fully_shard, DDP/replicate, tensor_parallel/parallelize_module, and any
2025-07-17T07:05:38.8306140Z combination of these parallelisms. The main functions of ``get_state_dict``
2025-07-17T07:05:38.8306270Z are: 1.) returning a model and optimizer state_dict that can be resharded
2025-07-17T07:05:38.8306400Z with a different number of trainers and/or different parallelisms.
2025-07-17T07:05:38.8306580Z 2.) hiding the parallelism-specific state_dict APIs. Users don't have to call
2025-07-17T07:05:38.8306630Z these APIs.
2025-07-17T07:05:38.8306700Z 3.) sanity checking the result state_dict.
2025-07-17T07:05:38.8306700Z 
2025-07-17T07:05:38.8306830Z The keys of the result state dictionary are the canonical FQNs (Fully
2025-07-17T07:05:38.8306970Z Qualified Names).  A canonical FQN refers to the FQN based on a parameter's
2025-07-17T07:05:38.8307110Z position in an nn.Module hierarchy. More specifically, a canonical FQN to a
2025-07-17T07:05:38.8307240Z parameter is the FQN returned by ``module.named_parameters()`` or
2025-07-17T07:05:38.8307460Z ``module.named_buffers()`` when the module is not distributed by any
2025-07-17T07:05:38.8307670Z parallelisms. Since the optimizer internally uses parameter IDs to represent
2025-07-17T07:05:38.8307800Z a parameter, there will be a conversion from the parameter IDs to the
2025-07-17T07:05:38.8307870Z canonical FQNs when calling this API.
2025-07-17T07:05:38.8307870Z 
2025-07-17T07:05:38.8308000Z ``get_state_dict`` can also process a module that is not parallelized. In
2025-07-17T07:05:38.8308140Z such a case, ``get_state_dict`` only performs one function -- converting the
2025-07-17T07:05:38.8308230Z optimizer parameter IDs to the canonical FQNs.
2025-07-17T07:05:38.8308230Z 
2025-07-17T07:05:38.8308280Z Example:
2025-07-17T07:05:38.8308330Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:38.8308380Z     >>> import torch
2025-07-17T07:05:38.8308520Z     >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-07-17T07:05:38.8308650Z     >>> from torch.nn.parallel import DistributedDataParallel as DDP
2025-07-17T07:05:38.8308790Z     >>> from torch.distributed.checkpoint.state_dict import get_state_dict
2025-07-17T07:05:38.8308790Z 
2025-07-17T07:05:38.8308870Z     >>> fsdp_model = FSDP(copy.deepcopy(model))
2025-07-17T07:05:38.8308980Z     >>> fsdp_optim = torch.optim.Adam(model.parameters(), lr=1e-3)
2025-07-17T07:05:38.8309060Z     >>> ddp_model = DDP(copy.deepcopy(model))
2025-07-17T07:05:38.8309170Z     >>> ddp_optim = torch.optim.Adam(model.parameters(), lr=1e-3)
2025-07-17T07:05:38.8309170Z 
2025-07-17T07:05:38.8309170Z 
2025-07-17T07:05:38.8309320Z     >>> ddp_state_dict, ddp_optim_state_dict = get_state_dict(ddp_model, ddp_optim)
2025-07-17T07:05:38.8309420Z     >>> fsdp_state_dict, fsdp_optim_state_dict = get_state_dict(
2025-07-17T07:05:38.8309480Z     ...     fsdp_model, fsdp_optim
2025-07-17T07:05:38.8309530Z     ... )
2025-07-17T07:05:38.8309530Z 
2025-07-17T07:05:38.8309660Z     >>> # if we simply call ddp_model.state_dict() and fsdp_model.state_dict(),
2025-07-17T07:05:38.8309720Z     >>> # the asserts will fail.
2025-07-17T07:05:38.8309790Z     >>> assert ddp_state_dict == fsdp_state_dict
2025-07-17T07:05:38.8309880Z     >>> assert ddp_optim_state == fsdp_optim_state_dict
2025-07-17T07:05:38.8309890Z 
2025-07-17T07:05:38.8309890Z 
2025-07-17T07:05:38.8309930Z Args:
2025-07-17T07:05:38.8310010Z     model (nn.Module): the nn.Module to the model.
2025-07-17T07:05:38.8310120Z     optimizers (Union[None, Optimizer, Iterable[Optimizer]]):
2025-07-17T07:05:38.8310220Z         The optimizers that are used to optimize ``model``.
2025-07-17T07:05:38.8310390Z     submodules (deprecated): Optional[set[nn.Module]]: only return the model parameters
2025-07-17T07:05:38.8310450Z         that belong to the submodules.
2025-07-17T07:05:38.8310550Z     options (StateDictOptions): the options to control how
2025-07-17T07:05:38.8310670Z         model state_dict and optimizer state_dict should be returned. See
2025-07-17T07:05:38.8310740Z         `StateDictOptions` for the details.
2025-07-17T07:05:38.8310740Z 
2025-07-17T07:05:38.8310790Z Returns:
2025-07-17T07:05:38.8310930Z     ``Tuple`` that contain model state_dict and optimizer state_dict.
2025-07-17T07:05:38.8310930Z 
2025-07-17T07:05:38.8311080Z :rtype: typing.Tuple[typing.Dict[str, ValueType], OptimizerStateType]
2025-07-17T07:05:38.8311080Z 
2025-07-17T07:05:38.8311250Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.8311260Z 
2025-07-17T07:05:38.8311670Z msg = Cannot scrape callname=save in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=96.
2025-07-17T07:05:38.8311820Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.8311830Z 
2025-07-17T07:05:38.8311900Z Save a distributed model in SPMD style.
2025-07-17T07:05:38.8311900Z 
2025-07-17T07:05:38.8312060Z This function is different from ``torch.save()`` as it handles
2025-07-17T07:05:38.8312290Z ``ShardedTensor`` , and ``DTensor`` by having each rank only save their local shards.
2025-07-17T07:05:38.8312350Z 
2025-07-17T07:05:38.8312510Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``),
2025-07-17T07:05:38.8312600Z save will call ``state_dict`` before serialization.
2025-07-17T07:05:38.8312610Z 
2025-07-17T07:05:38.8312660Z .. warning::
2025-07-17T07:05:38.8312800Z     There is no guarantees of Backwards Compatibility across PyTorch versions
2025-07-17T07:05:38.8312860Z     for saved state_dicts.
2025-07-17T07:05:38.8312860Z 
2025-07-17T07:05:38.8312910Z .. warning::
2025-07-17T07:05:38.8313040Z     If using the `process_group` argument, make sure that only its ranks
2025-07-17T07:05:38.8313170Z     call `save_state_dict` and that all data in state_dict belong to it.
2025-07-17T07:05:38.8313170Z 
2025-07-17T07:05:38.8313220Z .. note::
2025-07-17T07:05:38.8313370Z     When saving checkpoint for FSDP's `ShardingStrategy.HYBRID_SHARD`, only one of
2025-07-17T07:05:38.8313530Z     the shard_group should be calling `save_state_dict` and the corresponding process
2025-07-17T07:05:38.8313590Z     group needs to be passed in.
2025-07-17T07:05:38.8313600Z 
2025-07-17T07:05:38.8313640Z .. note::
2025-07-17T07:05:38.8313800Z     If no process group is available, this function assumes the intention is to save the
2025-07-17T07:05:38.8313860Z      state_dict in the local process.
2025-07-17T07:05:38.8313860Z 
2025-07-17T07:05:38.8313910Z .. note:
2025-07-17T07:05:38.8313990Z     Rank 0 is assumed to be the coordinator rank.
2025-07-17T07:05:38.8313990Z 
2025-07-17T07:05:38.8314000Z 
2025-07-17T07:05:38.8314040Z Args:
2025-07-17T07:05:38.8314130Z     state_dict (Dict[str, Any]): The state_dict to save.
2025-07-17T07:05:38.8314220Z     checkpoint_id (Union[str, os.PathLike, None]):
2025-07-17T07:05:38.8314350Z         The ID of this checkpoint instance. The meaning of the checkpoint_id
2025-07-17T07:05:38.8314470Z         depends on the storage. It can be a path to a folder or to a file.
2025-07-17T07:05:38.8314570Z         It can also be a key if the storage is a key-value store.
2025-07-17T07:05:38.8314630Z         (Default: ``None``)
2025-07-17T07:05:38.8314700Z     storage_writer (Optional[StorageWriter]):
2025-07-17T07:05:38.8314820Z         Instance of StorageWriter used to perform writes. If this is not
2025-07-17T07:05:38.8314950Z         specified, DCP will automatically infer the writer based on the
2025-07-17T07:05:38.8315070Z         checkpoint_id. If checkpoint_id is also None, an exception will
2025-07-17T07:05:38.8315140Z         be raised. (Default: ``None``)
2025-07-17T07:05:38.8315200Z     planner (Optional[SavePlanner]):
2025-07-17T07:05:38.8315330Z         Instance of SavePlanner. If this is not specified, the default
2025-07-17T07:05:38.8315400Z         planner will be used. (Default: ``None``)
2025-07-17T07:05:38.8315480Z     process_group (Optional[ProcessGroup]):
2025-07-17T07:05:38.8315580Z         ProcessGroup to be used for cross-rank synchronization.
2025-07-17T07:05:38.8315640Z         (Default: ``None``)
2025-07-17T07:05:38.8315690Z     no_dist (bool):
2025-07-17T07:05:38.8315810Z         If ``True``, this function will assume the intent is to load
2025-07-17T07:05:38.8315920Z         a checkpoint without using cross-rank synchronization.
2025-07-17T07:05:38.8315980Z         (Default: ``False``)
2025-07-17T07:05:38.8316000Z 
2025-07-17T07:05:38.8316050Z Returns:
2025-07-17T07:05:38.8316140Z     Metadata: Metadata object for the saved checkpoint.
2025-07-17T07:05:38.8316140Z 
2025-07-17T07:05:38.8316200Z Example:
2025-07-17T07:05:38.8316250Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:38.8316330Z     >>> my_model = MyModule()
2025-07-17T07:05:38.8316330Z 
2025-07-17T07:05:38.8316390Z     >>> state_dict = {"model": my_model}
2025-07-17T07:05:38.8316390Z 
2025-07-17T07:05:38.8316530Z     >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter(
2025-07-17T07:05:38.8316580Z     ...     "/checkpoint/1"
2025-07-17T07:05:38.8316630Z     ... )
2025-07-17T07:05:38.8316760Z     >>> torch.distributed.checkpoint.save(
2025-07-17T07:05:38.8316870Z     >>>     state_dict=state_dict,
2025-07-17T07:05:38.8316940Z     >>>     storage_writer=fs_storage_writer,
2025-07-17T07:05:38.8316980Z     >>> )
2025-07-17T07:05:38.8316990Z 
2025-07-17T07:05:38.8317030Z .. note::
2025-07-17T07:05:38.8317160Z     save_state_dict uses collectives to coordinate writes across ranks.
2025-07-17T07:05:38.8317290Z     For NCCL-based process groups, internal tensor representations of
2025-07-17T07:05:38.8317430Z     objects must be moved to the GPU device before communication takes place.
2025-07-17T07:05:38.8317570Z     In this case, the device used is given by ``torch.cuda.current_device()``
2025-07-17T07:05:38.8317690Z     and it is the user's responsibility to ensure that this is set so that
2025-07-17T07:05:38.8317810Z     each rank has an individual GPU, via ``torch.cuda.set_device()``.
2025-07-17T07:05:38.8317810Z 
2025-07-17T07:05:38.8317960Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.8506220Z 
2025-07-17T07:05:38.8506780Z msg = Cannot scrape callname=async_save in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=221.
2025-07-17T07:05:38.8506950Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.8507140Z Asynchronous version of ``save``. This code first de-stages the state_dict on to the
2025-07-17T07:05:38.8507320Z     staging storage (defaults to CPU memory), and then calls the `save` in a separate thread.
2025-07-17T07:05:38.8507320Z 
2025-07-17T07:05:38.8507380Z     .. warning::
2025-07-17T07:05:38.8507480Z         This feature is experimental and subject to change.
2025-07-17T07:05:38.8507570Z         MUST CALL CLOSE AFTER LAST CHECKPOINT IS SAVED
2025-07-17T07:05:38.8507580Z 
2025-07-17T07:05:38.8507620Z     Args:
2025-07-17T07:05:38.8507750Z         state_dict (Dict[str, Any]): The state_dict to save.
2025-07-17T07:05:38.8507840Z         checkpoint_id (Union[str, os.PathLike, None]):
2025-07-17T07:05:38.8507970Z             The ID of this checkpoint instance. The meaning of the checkpoint_id
2025-07-17T07:05:38.8508100Z             depends on the storage. It can be a path to a folder or to a file.
2025-07-17T07:05:38.8508210Z             It can also be a key if the storage is a key-value store.
2025-07-17T07:05:38.8508260Z             (Default: ``None``)
2025-07-17T07:05:38.8508340Z         storage_writer (Optional[StorageWriter]):
2025-07-17T07:05:38.8508480Z             Instance of StorageWriter used to perform 'stage' and  'save'. If
2025-07-17T07:05:38.8508620Z             this is not specified, DCP will automatically infer the writer based on the
2025-07-17T07:05:38.8508750Z             checkpoint_id. If checkpoint_id is also None, an exception will
2025-07-17T07:05:38.8508820Z             be raised. (Default: ``None``)
2025-07-17T07:05:38.8508890Z         planner (Optional[SavePlanner]):
2025-07-17T07:05:38.8509010Z             Instance of SavePlanner. If this is not specified, the default
2025-07-17T07:05:38.8509160Z             planner will be used. (Default: ``None``)
2025-07-17T07:05:38.8509240Z         process_group (Optional[ProcessGroup]):
2025-07-17T07:05:38.8509360Z             ProcessGroup to be used for cross-rank synchronization.
2025-07-17T07:05:38.8509440Z             (Default: ``None``)
2025-07-17T07:05:38.8509540Z         async_checkpointer_type (AsyncCheckpointerType):
2025-07-17T07:05:38.8509650Z             whether to do checkpoint in separate thread or process
2025-07-17T07:05:38.8509740Z             (Default: ``AsyncCheckpointerType.THREAD``)
2025-07-17T07:05:38.8509800Z         async_stager (AsyncStager):
2025-07-17T07:05:38.8509960Z             provides staging implementation. If storage_writer implements AsyncStager
2025-07-17T07:05:38.8510100Z             and async_stager is provided, async_stager will be used for staging
2025-07-17T07:05:38.8510100Z 
2025-07-17T07:05:38.8510140Z     Returns:
2025-07-17T07:05:38.8510350Z         Future: A future holding the resultant Metadata object from `save`.
2025-07-17T07:05:38.8510410Z 
2025-07-17T07:05:38.8510460Z     Example:
2025-07-17T07:05:38.8510520Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:38.8510580Z         >>> my_model = MyModule()
2025-07-17T07:05:38.8510580Z 
2025-07-17T07:05:38.8510650Z         >>> state_dict = {"model": my_model}
2025-07-17T07:05:38.8510660Z 
2025-07-17T07:05:38.8510800Z         >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter(
2025-07-17T07:05:38.8510850Z         ...     "/checkpoint/1"
2025-07-17T07:05:38.8510900Z         ... )
2025-07-17T07:05:38.8511020Z         >>> checkpoint_future = torch.distributed.checkpoint.async_save(
2025-07-17T07:05:38.8511080Z         >>>     state_dict=state_dict,
2025-07-17T07:05:38.8511150Z         >>>     storage_writer=fs_storage_writer,
2025-07-17T07:05:38.8511200Z         >>> )
2025-07-17T07:05:38.8511240Z         >>>
2025-07-17T07:05:38.8511300Z         >>> # ... do some work ...
2025-07-17T07:05:38.8511340Z         >>>
2025-07-17T07:05:38.8511400Z         >>> checkpoint_future.result()
2025-07-17T07:05:38.8511400Z 
2025-07-17T07:05:38.8511440Z     
2025-07-17T07:05:38.8511600Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.8511600Z 
2025-07-17T07:05:38.8512050Z msg = Cannot scrape callname=load in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict_loader.py line=62.
2025-07-17T07:05:38.8512200Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.8512200Z 
2025-07-17T07:05:38.8512320Z Load a checkpoint into a distributed state dict in SPMD style.
2025-07-17T07:05:38.8512320Z 
2025-07-17T07:05:38.8512450Z Each rank must have the same keys in their ``state_dict`` provided to this
2025-07-17T07:05:38.8512590Z API. Mismatched keys may result in hangs or errors. If unsure, you can use
2025-07-17T07:05:38.8512730Z the ``utils._assert_same_keys`` API to check (but may incur communication
2025-07-17T07:05:38.8512770Z costs).
2025-07-17T07:05:38.8512770Z 
2025-07-17T07:05:38.8512880Z Each rank will try to read the least amount of data necessary
2025-07-17T07:05:38.8513020Z to fulfill the requested `state_dict`. When loading :class:`ShardedTensor`
2025-07-17T07:05:38.8513170Z or :class:`DTensor` instances, each rank only reads data for their local shards.
2025-07-17T07:05:38.8513170Z 
2025-07-17T07:05:38.8513360Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``),
2025-07-17T07:05:38.8513510Z load will first call ``state_dict`` before attempting deserialization, followed by
2025-07-17T07:05:38.8513610Z ``load_state_dict`` once the deserialization is complete.
2025-07-17T07:05:38.8513760Z For each non-``Stateful`` object, load will deserialize the object, and then replace
2025-07-17T07:05:38.8513850Z it in the ``state_dict`` with the deserialized object.
2025-07-17T07:05:38.8513850Z 
2025-07-17T07:05:38.8513900Z .. warning::
2025-07-17T07:05:38.8514040Z     All tensors in ``state_dict`` must be allocated on their
2025-07-17T07:05:38.8514140Z     destination device *prior to* calling this function.
2025-07-17T07:05:38.8514140Z 
2025-07-17T07:05:38.8514280Z     All non-tensor data is loaded using `torch.load()` and modified in place
2025-07-17T07:05:38.8514380Z     on state_dict.
2025-07-17T07:05:38.8514390Z 
2025-07-17T07:05:38.8514430Z .. warning::
2025-07-17T07:05:38.8514590Z     Users must call `load_state_dict` on the root module to ensure load
2025-07-17T07:05:38.8514700Z     pos-processing and non-tensor data properly propagates.
2025-07-17T07:05:38.8514700Z 
2025-07-17T07:05:38.8514740Z .. note:
2025-07-17T07:05:38.8514880Z     If no process group is initialized, this function will assume the intent
2025-07-17T07:05:38.8515020Z     is to load a checkpoint into the local process. This can be useful in the
2025-07-17T07:05:38.8515250Z     case of local inference, and when using regular Tensors (as opposed to DTensor
2025-07-17T07:05:38.8515350Z      or ShardedTensor)
2025-07-17T07:05:38.8515350Z 
2025-07-17T07:05:38.8515400Z .. note:
2025-07-17T07:05:38.8515480Z     Rank 0 is assumed to be the coordinator rank.
2025-07-17T07:05:38.8515480Z 
2025-07-17T07:05:38.8515520Z Args:
2025-07-17T07:05:38.8515650Z     state_dict (Dict[str, Any]): The state_dict to load the checkpoint into.
2025-07-17T07:05:38.8515730Z     checkpoint_id (Union[str, os.PathLike, None]):
2025-07-17T07:05:38.8515860Z         The ID of this checkpoint instance. The meaning of the checkpoint_id
2025-07-17T07:05:38.8515980Z         depends on the storage. It can be a path to a folder or to a file.
2025-07-17T07:05:38.8516080Z         It can also be a key if the storage is a key-value store.
2025-07-17T07:05:38.8516140Z         (Default: ``None``)
2025-07-17T07:05:38.8516220Z     storage_reader (Optional[StorageReader]):
2025-07-17T07:05:38.8516340Z         Instance of StorageWriter used to perform reads. If this is not
2025-07-17T07:05:38.8516460Z         specified, DCP will automatically infer the reader based on the
2025-07-17T07:05:38.8516590Z         checkpoint_id. If checkpoint_id is also None, an exception will
2025-07-17T07:05:38.8516650Z         be raised. (Default: ``None``)
2025-07-17T07:05:38.8516710Z     planner (Optional[LoadPlanner]):
2025-07-17T07:05:38.8516840Z         Instance of LoadPlanner. If this is not specified, the default
2025-07-17T07:05:38.8516910Z         planner will be used. (Default: ``None``)
2025-07-17T07:05:38.8516990Z     process_group (Optional[ProcessGroup]):
2025-07-17T07:05:38.8517090Z         ProcessGroup to be used for cross-rank synchronization.
2025-07-17T07:05:38.8517150Z         (Default: ``None``)
2025-07-17T07:05:38.8517310Z     no_dist (bool): If ``True``, this function will assume the intent is to load
2025-07-17T07:05:38.8517460Z         a checkpoint without using cross-rank synchronization. (Default: ``False``)
2025-07-17T07:05:38.8517500Z Returns:
2025-07-17T07:05:38.8517550Z     None.
2025-07-17T07:05:38.8517550Z 
2025-07-17T07:05:38.8517590Z Examples
2025-07-17T07:05:38.8517650Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:38.8517700Z     >>> my_model = MyModule()
2025-07-17T07:05:38.8517780Z     >>> optimizer = Adagrad(my_model.parameters())
2025-07-17T07:05:38.8517870Z     >>> model_state_dict = my_model.state_dict()
2025-07-17T07:05:38.8518010Z     >>> fs_storage_reader = torch.distributed.checkpoint.FileSystemReader(
2025-07-17T07:05:38.8518060Z     ...     "/checkpoint/1"
2025-07-17T07:05:38.8518100Z     ... )
2025-07-17T07:05:38.8518100Z 
2025-07-17T07:05:38.8518190Z     >>> torch.distributed.checkpoint.load_state_dict(
2025-07-17T07:05:38.8518250Z     >>>     state_dict=model_state_dict,
2025-07-17T07:05:38.8518320Z     >>>     storage_reader=fs_storage_reader,
2025-07-17T07:05:38.8518360Z     >>> )
2025-07-17T07:05:38.8518360Z 
2025-07-17T07:05:38.8518480Z     >>> # module.load_state_dict() function might have customized steps
2025-07-17T07:05:38.8518560Z     >>> # to flush the state_dict, must call it to
2025-07-17T07:05:38.8518640Z     >>> # ensure correct behavior.
2025-07-17T07:05:38.8518710Z     >>> my_model.load_state_dict(model_state_dict)
2025-07-17T07:05:38.8518720Z 
2025-07-17T07:05:38.8518760Z .. note::
2025-07-17T07:05:38.8518890Z     load_state_dict uses collectives to coordinate reads across ranks.
2025-07-17T07:05:38.8519040Z     For NCCL-based process groups, internal tensor representations of
2025-07-17T07:05:38.8519180Z     objects must be moved to the GPU device before communication takes place.
2025-07-17T07:05:38.8519310Z     In this case, the device used is given by ``torch.cuda.current_device()``
2025-07-17T07:05:38.8519450Z     and it is the user's responsibility to ensure that this is set so that each
2025-07-17T07:05:38.8519560Z     rank has an individual GPU, via ``torch.cuda.set_device()``.
2025-07-17T07:05:38.8519560Z 
2025-07-17T07:05:38.8519710Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.8519780Z 
2025-07-17T07:05:38.8520310Z msg = Cannot scrape callname=load_sharded_optimizer_state_dict in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/optimizer.py line=221.
2025-07-17T07:05:38.8520470Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.8520480Z 
2025-07-17T07:05:38.8520600Z Load a state_dict in conjunction with FSDP sharded optimizer state.
2025-07-17T07:05:38.8520600Z 
2025-07-17T07:05:38.8520700Z This is the current recommended way to checkpoint FSDP.
2025-07-17T07:05:38.8520750Z >>> # xdoctest: +SKIP
2025-07-17T07:05:38.8520840Z >>> import torch.distributed.checkpoint as dist_cp
2025-07-17T07:05:38.8520880Z >>> # Save
2025-07-17T07:05:38.8520940Z >>> model: torch.nn.Model
2025-07-17T07:05:38.8521010Z >>> optim_params = model.parameters()
2025-07-17T07:05:38.8521090Z >>> optim = torch.optim.SGD(optim_params, lr=0.01)
2025-07-17T07:05:38.8521130Z >>> # Save
2025-07-17T07:05:38.8521270Z >>> with FSDP.state_dict_type(model, StateDictType.SHARDED_STATE_DICT):
2025-07-17T07:05:38.8521320Z >>>     state_dict = {
2025-07-17T07:05:38.8521420Z >>>         "optimizer": FSDP.optim_state_dict(model, optim),
2025-07-17T07:05:38.8521480Z >>>         "model": model.state_dict()
2025-07-17T07:05:38.8521520Z >>>     }
2025-07-17T07:05:38.8521580Z >>>     dist_cp.save_state_dict(
2025-07-17T07:05:38.8521640Z >>>         state_dict=optim_state,
2025-07-17T07:05:38.8521750Z >>>         storage_writer=dist_cp.FileSystemWriter("checkpoint"),
2025-07-17T07:05:38.8521820Z >>>         planner=dist_cp.DefaultSavePlanner(),
2025-07-17T07:05:38.8521870Z >>>     )
2025-07-17T07:05:38.8521910Z >>>
2025-07-17T07:05:38.8521950Z >>> # Load
2025-07-17T07:05:38.8522080Z >>> with FSDP.state_dict_type(model_tp, StateDictType.SHARDED_STATE_DICT):
2025-07-17T07:05:38.8522160Z >>>     model_state_dict = model_tp.state_dict()
2025-07-17T07:05:38.8522210Z >>>     checkpoint = {
2025-07-17T07:05:38.8522270Z >>>         "model": model_state_dict
2025-07-17T07:05:38.8522340Z >>>     }
2025-07-17T07:05:38.8522400Z >>>     dist_cp.load_state_dict(
2025-07-17T07:05:38.8522460Z >>>         state_dict=checkpoint,
2025-07-17T07:05:38.8522580Z >>>         storage_reader=dist_cp.FileSystemReader(checkpoint_file),
2025-07-17T07:05:38.8522650Z >>>         planner=dist_cp.DefaultLoadPlanner(),
2025-07-17T07:05:38.8522700Z >>>     )
2025-07-17T07:05:38.8522790Z >>>     model.load_state_dict(checkpoint["model_state"])
2025-07-17T07:05:38.8522830Z >>>
2025-07-17T07:05:38.8522930Z >>>     optim_state = dist_cp.load_sharded_optimizer_state_dict(
2025-07-17T07:05:38.8522990Z >>>         model_state_dict,
2025-07-17T07:05:38.8523050Z >>>         optimizer_key="optimizer",
2025-07-17T07:05:38.8523150Z >>>         storage_reader=dist_cp.FileSystemReader("checkpoint"),
2025-07-17T07:05:38.8523190Z >>>     )
2025-07-17T07:05:38.8523230Z >>>
2025-07-17T07:05:38.8523320Z >>>     flattened_osd = FSDP.optim_state_dict_to_load(
2025-07-17T07:05:38.8523400Z >>>        model, optim, optim_state["optimizer"]
2025-07-17T07:05:38.8523460Z >>>     )
2025-07-17T07:05:38.8523500Z >>>
2025-07-17T07:05:38.8523570Z >>>     optim.load_state_dict(flattened_osd)
2025-07-17T07:05:38.8523570Z 
2025-07-17T07:05:38.8523720Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.9306370Z 
2025-07-17T07:05:38.9307030Z msg = Cannot scrape callname=_RemoteModule.__init__ in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/nn/api/remote_module.py line=129.
2025-07-17T07:05:38.9307200Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.9307200Z 
2025-07-17T07:05:38.9307350Z RemoteModule instance can only be created after RPC initialization.
2025-07-17T07:05:38.9307350Z 
2025-07-17T07:05:38.9307470Z It creates a user-specified module on a specified remote node.
2025-07-17T07:05:38.9307890Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is
2025-07-17T07:05:38.9308050Z executed on the remote node.
2025-07-17T07:05:38.9308200Z It takes care of autograd recording to ensure the backward pass propagates
2025-07-17T07:05:38.9308290Z gradients back to the corresponding remote module.
2025-07-17T07:05:38.9308520Z It can be shared across processors using `RPC framework <https://pytorch.org/docs/stable/rpc.html>`__,
2025-07-17T07:05:38.9308650Z without incurring any overheads of copying the actual module,
2025-07-17T07:05:38.9308780Z which is equivalent to an :class:`~torch.distributed.rpc.RRef`
2025-07-17T07:05:38.9308840Z pointing to the remote module.
2025-07-17T07:05:38.9308840Z 
2025-07-17T07:05:38.9308970Z The arguments of ``forward_async`` and ``forward`` are the same as
2025-07-17T07:05:38.9309090Z the ``forward`` method of the module returned by the ``module_cls``.
2025-07-17T07:05:38.9309100Z 
2025-07-17T07:05:38.9309290Z Apart from ``forward_async`` and ``forward``, no other methods are supported from nn.Module for now.
2025-07-17T07:05:38.9309300Z 
2025-07-17T07:05:38.9309450Z Particularly, to create a hybrid model, typically the local modules should be
2025-07-17T07:05:38.9309680Z created outside of remote modules, rather than as submodules of any remote module (by calling ``add_module``).
2025-07-17T07:05:38.9309770Z Hybrid Example:
2025-07-17T07:05:38.9309840Z         >>> class HybridModel(nn.Module):
2025-07-17T07:05:38.9309910Z         >>>     def __init__(self) -> None:
2025-07-17T07:05:38.9309970Z         >>>         nn.Module.__init__(self)
2025-07-17T07:05:38.9310060Z         >>>         self.remote_embedding = RemoteModule(...)
2025-07-17T07:05:38.9310140Z         >>>         self.local_linear = nn.Linear(...)
2025-07-17T07:05:38.9310140Z 
2025-07-17T07:05:38.9310270Z For example, if ``module_cls`` returns an instance of ``nn.Linear``,
2025-07-17T07:05:38.9310420Z that has ``forward`` method signature, ``def forward(input: Tensor) -> Tensor:``,
2025-07-17T07:05:38.9310550Z the generated ``RemoteModule`` will have 2 methods in signature of
2025-07-17T07:05:38.9310640Z ``def forward(input: Tensor) -> Tensor:`` and
2025-07-17T07:05:38.9310740Z ``def forward_async(input: Tensor) -> Future[Tensor]:``.
2025-07-17T07:05:38.9310740Z 
2025-07-17T07:05:38.9310800Z .. note::
2025-07-17T07:05:38.9310890Z     If the remote module is placed on a cuda device,
2025-07-17T07:05:38.9311040Z     any input CPU tensors will be automatically moved to the same cuda device,
2025-07-17T07:05:38.9311280Z     and GPU tensors are returned over the wire according to the device map of the remote worker on TensorPipe RPC backend.
2025-07-17T07:05:38.9311280Z 
2025-07-17T07:05:38.9311330Z Args:
2025-07-17T07:05:38.9311510Z     remote_device (str): Device on the destination worker where we'd like to place this module.
2025-07-17T07:05:38.9311700Z         The device can be a local device or a remote device specified by one of the following remote
2025-07-17T07:05:38.9311740Z         formats:
2025-07-17T07:05:38.9311750Z 
2025-07-17T07:05:38.9311840Z             1. "rank:<rank>/<device>" (ex: "rank:0/cuda:0").
2025-07-17T07:05:38.9312010Z             2. "<worker_name>/<device>" (ex: "trainer0/cuda:0").
2025-07-17T07:05:38.9312010Z 
2025-07-17T07:05:38.9312170Z         In addition, the device field can be optional and the default value is "cpu".
2025-07-17T07:05:38.9312280Z     module_cls (nn.Module): For example,
2025-07-17T07:05:38.9312350Z         >>> class MyModule(nn.Module):
2025-07-17T07:05:38.9312410Z         >>>     def forward(input):
2025-07-17T07:05:38.9312470Z         >>>         return input + 1
2025-07-17T07:05:38.9312510Z         >>>
2025-07-17T07:05:38.9312570Z         >>> module_cls = MyModule
2025-07-17T07:05:38.9312690Z     args (Sequence, optional): args to be passed to ``module_cls``.
2025-07-17T07:05:38.9312810Z     kwargs (Dict, optional): kwargs to be passed to ``module_cls``.
2025-07-17T07:05:38.9312990Z     _module_interface_cls (type, optional): The TorchScript interface type for the module
2025-07-17T07:05:38.9313160Z         to be created. The type object should be decorated by @torch.jit.interface.
2025-07-17T07:05:38.9313330Z         If not provided, the generated RemoteModule is not torchscript-able.
2025-07-17T07:05:38.9313470Z         Warning, this is an experimental API and susceptible to frequent changes.
2025-07-17T07:05:38.9313480Z 
2025-07-17T07:05:38.9313520Z Returns:
2025-07-17T07:05:38.9313670Z     A remote module instance which wraps the :class:`~nn.Module` created by the
2025-07-17T07:05:38.9313820Z     user-provided ``module_cls``, it has a blocking ``forward`` method and an
2025-07-17T07:05:38.9313980Z     asynchronous ``forward_async`` method that returns a future of the ``forward`` call
2025-07-17T07:05:38.9314070Z     on the user-provided module on the remote side.
2025-07-17T07:05:38.9314080Z 
2025-07-17T07:05:38.9314120Z Example::
2025-07-17T07:05:38.9314210Z     Run the following code in two different processes:
2025-07-17T07:05:38.9314210Z 
2025-07-17T07:05:38.9314280Z     >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:38.9314330Z     >>> # On worker 0:
2025-07-17T07:05:38.9314370Z     >>> import torch
2025-07-17T07:05:38.9314450Z     >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:38.9314500Z     >>> from torch import nn, Tensor
2025-07-17T07:05:38.9314640Z     >>> from torch.distributed.nn.api.remote_module import RemoteModule
2025-07-17T07:05:38.9314680Z     >>>
2025-07-17T07:05:38.9314760Z     >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-07-17T07:05:38.9314830Z     >>> remote_linear_module = RemoteModule(
2025-07-17T07:05:38.9314910Z     >>>     "worker1/cpu", nn.Linear, args=(20, 30),
2025-07-17T07:05:38.9314950Z     >>> )
2025-07-17T07:05:38.9315010Z     >>> input = torch.randn(128, 20)
2025-07-17T07:05:38.9315100Z     >>> ret_fut = remote_linear_module.forward_async(input)
2025-07-17T07:05:38.9315160Z     >>> ret = ret_fut.wait()
2025-07-17T07:05:38.9315210Z     >>> rpc.shutdown()
2025-07-17T07:05:38.9315210Z 
2025-07-17T07:05:38.9315250Z     >>> # On worker 1:
2025-07-17T07:05:38.9315310Z     >>> import torch
2025-07-17T07:05:38.9315380Z     >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:38.9315420Z     >>>
2025-07-17T07:05:38.9315500Z     >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-07-17T07:05:38.9315550Z     >>> rpc.shutdown()
2025-07-17T07:05:38.9315550Z 
2025-07-17T07:05:38.9315700Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.9315700Z 
2025-07-17T07:05:38.9316180Z msg = Cannot scrape callname=_RemoteModule.init_from_module_rref in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/nn/api/remote_module.py line=506.
2025-07-17T07:05:38.9316330Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.9316330Z 
2025-07-17T07:05:38.9316530Z Besides the constructor, a RemoteModule instance can also be initialized given a module RRef.
2025-07-17T07:05:38.9316530Z 
2025-07-17T07:05:38.9316740Z This alternate initialization method can be particularly useful if we want to create multiple
2025-07-17T07:05:38.9316930Z RemoteModule instances that share the same underlying module and reduce memory consumption.
2025-07-17T07:05:38.9316940Z 
2025-07-17T07:05:38.9317100Z Moreover, this also provides a workaround for passing script RemoteModule over RPC,
2025-07-17T07:05:38.9317260Z which is not supported. The recommended way is as follows:
2025-07-17T07:05:38.9317260Z 
2025-07-17T07:05:38.9317330Z     1. the sender creates a RemoteModule;
2025-07-17T07:05:38.9317420Z     2. the sender sends its ``module_rref`` over RPC;
2025-07-17T07:05:38.9317620Z     3. the receiver calls this method to initialize another RemoteModule using the same ``module_rref``.
2025-07-17T07:05:38.9317620Z 
2025-07-17T07:05:38.9317670Z Example::
2025-07-17T07:05:38.9317760Z     Run the following code in two different processes:
2025-07-17T07:05:38.9317760Z 
2025-07-17T07:05:38.9317820Z     >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:38.9317890Z     >>> # On worker 0:
2025-07-17T07:05:38.9317950Z     >>> import torch
2025-07-17T07:05:38.9318030Z     >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:38.9318090Z     >>> from torch import nn, Tensor
2025-07-17T07:05:38.9318220Z     >>> from torch.distributed.nn.api.remote_module import RemoteModule
2025-07-17T07:05:38.9318270Z     >>>
2025-07-17T07:05:38.9318360Z     >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-07-17T07:05:38.9318420Z     >>> remote_module = RemoteModule(
2025-07-17T07:05:38.9318500Z     >>>     "worker1/cpu", nn.Linear, args=(20, 30),
2025-07-17T07:05:38.9318540Z     >>> )
2025-07-17T07:05:38.9318580Z     >>>
2025-07-17T07:05:38.9318640Z     >>> remote_module1 = rpc.rpc_sync(
2025-07-17T07:05:38.9318690Z     >>>     "worker1/cpu",
2025-07-17T07:05:38.9318760Z     >>>     RemoteModule.init_from_module_rref,
2025-07-17T07:05:38.9318860Z     >>>     ("worker1/cpu", remote_module1.get_module_rref()),
2025-07-17T07:05:38.9318900Z     >>> )
2025-07-17T07:05:38.9318950Z     >>> rpc.shutdown()
2025-07-17T07:05:38.9318950Z 
2025-07-17T07:05:38.9319000Z     >>> # On worker 1:
2025-07-17T07:05:38.9319050Z     >>> import torch
2025-07-17T07:05:38.9319120Z     >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:38.9319160Z     >>>
2025-07-17T07:05:38.9319250Z     >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-07-17T07:05:38.9319300Z     >>> rpc.shutdown()
2025-07-17T07:05:38.9319300Z 
2025-07-17T07:05:38.9319340Z Args:
2025-07-17T07:05:38.9319520Z     remote_device (str): Device on the destination worker where we'd like to place this module.
2025-07-17T07:05:38.9319700Z         The device can be a local device or a remote device specified by one of the following remote
2025-07-17T07:05:38.9319740Z         formats:
2025-07-17T07:05:38.9319740Z 
2025-07-17T07:05:38.9319830Z             1. "rank:<rank>/<device>" (ex: "rank:0/cuda:0").
2025-07-17T07:05:38.9319920Z             2. "<worker_name>/<device>" (ex: "trainer0/cuda:0").
2025-07-17T07:05:38.9319920Z 
2025-07-17T07:05:38.9320080Z         In addition, the device field can be optional and the default value is "cpu".
2025-07-17T07:05:38.9320220Z     module_rref (RRef[nn.Module]): The module reference shared by both the caller and
2025-07-17T07:05:38.9320290Z         the created remote module.
2025-07-17T07:05:38.9320450Z     _module_interface_cls (type, optional): The TorchScript interface type for the module
2025-07-17T07:05:38.9320600Z         to be created. The type object should be decorated by @torch.jit.interface.
2025-07-17T07:05:38.9320730Z         If not provided, the generated RemoteModule is not torchscript-able.
2025-07-17T07:05:38.9320870Z         Warning, this is an experimental API and susceptible to frequent changes.
2025-07-17T07:05:38.9320870Z 
2025-07-17T07:05:38.9320920Z Returns:
2025-07-17T07:05:38.9321060Z     A remote module instance which wraps the :class:`~nn.Module` created by the
2025-07-17T07:05:38.9321200Z     user-provided ``module_rref``, it has a blocking ``forward`` method and an
2025-07-17T07:05:38.9321390Z     asynchronous ``forward_async`` method that returns a future of the ``forward`` call
2025-07-17T07:05:38.9321480Z     on the user-provided module on the remote side.
2025-07-17T07:05:38.9321480Z 
2025-07-17T07:05:38.9321630Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.9321650Z 
2025-07-17T07:05:38.9322080Z msg = Cannot scrape callname=RemoteModule in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/nn/api/remote_module.py line=598.
2025-07-17T07:05:38.9322230Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.9322230Z 
2025-07-17T07:05:38.9322370Z     A RemoteModule instance can only be created after RPC initialization.
2025-07-17T07:05:38.9322370Z 
2025-07-17T07:05:38.9322490Z     It creates a user-specified module on a specified remote node.
2025-07-17T07:05:38.9322650Z     It behaves like a regular ``nn.Module`` except that the ``forward`` method is
2025-07-17T07:05:38.9322750Z     executed on the remote node.
2025-07-17T07:05:38.9322890Z     It takes care of autograd recording to ensure the backward pass propagates
2025-07-17T07:05:38.9322990Z     gradients back to the corresponding remote module.
2025-07-17T07:05:38.9323000Z 
2025-07-17T07:05:38.9323130Z     It generates two methods ``forward_async`` and ``forward`` based on the
2025-07-17T07:05:38.9323260Z     signature of the ``forward`` method of ``module_cls``. ``forward_async``
2025-07-17T07:05:38.9323400Z     runs asynchronously and returns a Future. The arguments of ``forward_async``
2025-07-17T07:05:38.9323520Z     and ``forward`` are the same as the ``forward`` method of the module
2025-07-17T07:05:38.9323580Z     returned by the ``module_cls``.
2025-07-17T07:05:38.9323590Z 
2025-07-17T07:05:38.9323700Z     For example, if ``module_cls`` returns an instance of ``nn.Linear``,
2025-07-17T07:05:38.9323850Z     that has ``forward`` method signature: ``def forward(input: Tensor) -> Tensor:``,
2025-07-17T07:05:38.9323990Z     the generated ``RemoteModule`` will have 2 methods with the signatures:
2025-07-17T07:05:38.9323990Z 
2025-07-17T07:05:38.9324070Z     | ``def forward(input: Tensor) -> Tensor:``
2025-07-17T07:05:38.9324170Z     | ``def forward_async(input: Tensor) -> Future[Tensor]:``
2025-07-17T07:05:38.9324170Z 
2025-07-17T07:05:38.9324210Z Args:
2025-07-17T07:05:38.9324390Z     remote_device (str): Device on the destination worker where we'd like to place this module.
2025-07-17T07:05:38.9324600Z         The format should be "<workername>/<device>", where the device field can be parsed as torch.device type.
2025-07-17T07:05:38.9324680Z         E.g., "trainer0/cpu", "trainer0", "ps0/cuda:0".
2025-07-17T07:05:38.9324830Z         In addition, the device field can be optional and the default value is "cpu".
2025-07-17T07:05:38.9324980Z     module_cls (nn.Module): Class for the module to be created remotely. For example,
2025-07-17T07:05:38.9324980Z 
2025-07-17T07:05:38.9325050Z         >>> class MyModule(nn.Module):
2025-07-17T07:05:38.9325110Z         >>>     def forward(input):
2025-07-17T07:05:38.9325170Z         >>>         return input + 1
2025-07-17T07:05:38.9325210Z         >>>
2025-07-17T07:05:38.9325260Z         >>> module_cls = MyModule
2025-07-17T07:05:38.9325270Z 
2025-07-17T07:05:38.9325390Z     args (Sequence, optional): args to be passed to ``module_cls``.
2025-07-17T07:05:38.9325510Z     kwargs (Dict, optional): kwargs to be passed to ``module_cls``.
2025-07-17T07:05:38.9325510Z 
2025-07-17T07:05:38.9325550Z Returns:
2025-07-17T07:05:38.9325700Z     A remote module instance which wraps the :class:`~nn.Module` created by the
2025-07-17T07:05:38.9325840Z     user-provided ``module_cls``, it has a blocking ``forward`` method and an
2025-07-17T07:05:38.9326000Z     asynchronous ``forward_async`` method that returns a future of the ``forward`` call
2025-07-17T07:05:38.9326090Z     on the user-provided module on the remote side.
2025-07-17T07:05:38.9326090Z 
2025-07-17T07:05:38.9326140Z Example::
2025-07-17T07:05:38.9326250Z     Run the following code in two different processes:
2025-07-17T07:05:38.9326250Z 
2025-07-17T07:05:38.9326310Z     >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:38.9326360Z     >>> # On worker 0:
2025-07-17T07:05:38.9326430Z     >>> import torch
2025-07-17T07:05:38.9326510Z     >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:38.9326570Z     >>> from torch import nn, Tensor
2025-07-17T07:05:38.9326700Z     >>> from torch.distributed.nn.api.remote_module import RemoteModule
2025-07-17T07:05:38.9326740Z     >>>
2025-07-17T07:05:38.9326820Z     >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-07-17T07:05:38.9326890Z     >>> remote_linear_module = RemoteModule(
2025-07-17T07:05:38.9326970Z     >>>     "worker1/cpu", nn.Linear, args=(20, 30),
2025-07-17T07:05:38.9327010Z     >>> )
2025-07-17T07:05:38.9327070Z     >>> input = torch.randn(128, 20)
2025-07-17T07:05:38.9327180Z     >>> ret_fut = remote_linear_module.forward_async(input)
2025-07-17T07:05:38.9327260Z     >>> ret = ret_fut.wait()
2025-07-17T07:05:38.9327310Z     >>> rpc.shutdown()
2025-07-17T07:05:38.9327310Z 
2025-07-17T07:05:38.9327360Z     >>> # On worker 1:
2025-07-17T07:05:38.9327410Z     >>> import torch
2025-07-17T07:05:38.9327470Z     >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:38.9327520Z     >>>
2025-07-17T07:05:38.9327600Z     >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-07-17T07:05:38.9327650Z     >>> rpc.shutdown()
2025-07-17T07:05:38.9327650Z 
2025-07-17T07:05:38.9327790Z     Furthermore, a more practical example that is combined with
2025-07-17T07:05:38.9328080Z     `DistributedDataParallel <https://pytorch.org/docs/stable/nn.html#torch.nn.parallel.DistributedDataParallel>`__ (DDP)
2025-07-17T07:05:38.9328270Z     can be found in this `tutorial <https://pytorch.org/tutorials/advanced/rpc_ddp_tutorial.html>`__.
2025-07-17T07:05:38.9328280Z 
2025-07-17T07:05:38.9328430Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.9492110Z 
2025-07-17T07:05:38.9492840Z msg = Cannot scrape callname=construct_and_record_rdzv_event in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/elastic/events/__init__.py line=94.
2025-07-17T07:05:38.9493030Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.9493030Z 
2025-07-17T07:05:38.9493230Z Initialize rendezvous event object and record its operations.
2025-07-17T07:05:38.9493240Z 
2025-07-17T07:05:38.9499820Z Args:
2025-07-17T07:05:38.9500170Z     run_id (str): The run id of the rendezvous.
2025-07-17T07:05:38.9500440Z     message (str): The message describing the event.
2025-07-17T07:05:38.9500870Z     node_state (NodeState): The state of the node (INIT, RUNNING, SUCCEEDED, FAILED).
2025-07-17T07:05:38.9501180Z     name (str): Event name. (E.g. Current action being performed).
2025-07-17T07:05:38.9501370Z     hostname (str): Hostname of the node.
2025-07-17T07:05:38.9501630Z     pid (Optional[int]): The process id of the node.
2025-07-17T07:05:38.9502030Z     master_endpoint (str): The master endpoint for the rendezvous store, if known.
2025-07-17T07:05:38.9502540Z     local_id (Optional[int]):  The local_id of the node, if defined in dynamic_rendezvous.py
2025-07-17T07:05:38.9502730Z     rank (Optional[int]): The rank of the node, if known.
2025-07-17T07:05:38.9502780Z Returns:
2025-07-17T07:05:38.9502820Z     None
2025-07-17T07:05:38.9502870Z Example:
2025-07-17T07:05:38.9502950Z     >>> # See DynamicRendezvousHandler class
2025-07-17T07:05:38.9502990Z     >>> def _record(
2025-07-17T07:05:38.9503100Z     ...     self,
2025-07-17T07:05:38.9503150Z     ...     message: str,
2025-07-17T07:05:38.9503240Z     ...     node_state: NodeState = NodeState.RUNNING,
2025-07-17T07:05:38.9503310Z     ...     rank: Optional[int] = None,
2025-07-17T07:05:38.9503350Z     ... ) -> None:
2025-07-17T07:05:38.9503430Z     ...     construct_and_record_rdzv_event(
2025-07-17T07:05:38.9503740Z     ...         name=f"{self.__class__.__name__}.{get_method_name()}",
2025-07-17T07:05:38.9503840Z     ...         run_id=self._settings.run_id,
2025-07-17T07:05:38.9503900Z     ...         message=message,
2025-07-17T07:05:38.9503960Z     ...         node_state=node_state,
2025-07-17T07:05:38.9504090Z     ...         hostname=self._this_node.addr,
2025-07-17T07:05:38.9504150Z     ...         pid=self._this_node.pid,
2025-07-17T07:05:38.9504230Z     ...         local_id=self._this_node.local_id,
2025-07-17T07:05:38.9504280Z     ...         rank=rank,
2025-07-17T07:05:38.9504320Z     ...     )
2025-07-17T07:05:38.9504330Z 
2025-07-17T07:05:38.9504480Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.9504480Z 
2025-07-17T07:05:38.9504920Z msg = Cannot scrape callname=_CustomReducer in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/pipelining/microbatch.py line=29.
2025-07-17T07:05:38.9505120Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.9505140Z 
2025-07-17T07:05:38.9505290Z Custom reducer class that can be used to specify a custom operation that
2025-07-17T07:05:38.9505390Z reduces losses of multiple microbatches into one value.
2025-07-17T07:05:38.9505390Z 
2025-07-17T07:05:38.9505440Z Example:
2025-07-17T07:05:38.9505490Z >>> # xdoctest: +SKIP
2025-07-17T07:05:38.9505550Z >>> sum_reducer = _CustomReducer(
2025-07-17T07:05:38.9505600Z >>>     torch.tensor(0.0),
2025-07-17T07:05:38.9505650Z >>>     lambda a, b: a + b
2025-07-17T07:05:38.9505690Z >>> )
2025-07-17T07:05:38.9505690Z 
2025-07-17T07:05:38.9505870Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.9505880Z 
2025-07-17T07:05:38.9506400Z msg = Cannot scrape callname=PeriodicModelAverager in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/algorithms/model_averaging/averagers.py line=38.
2025-07-17T07:05:38.9506590Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.9506600Z 
2025-07-17T07:05:38.9506710Z Averages parameters periodically after the warm-up stage.
2025-07-17T07:05:38.9506710Z 
2025-07-17T07:05:38.9506900Z This can be used for running `post-local SGD <https://arxiv.org/abs/1808.07217>`_,
2025-07-17T07:05:38.9507020Z by running :class:`~torch.nn.DistributedDataParallel` (DDP)
2025-07-17T07:05:38.9507170Z using the subgroups created by :meth:`~torch.distributed.new_subgroups`.
2025-07-17T07:05:38.9507170Z 
2025-07-17T07:05:38.9507210Z Args:
2025-07-17T07:05:38.9507310Z     period (int): The number of steps per model averaging.
2025-07-17T07:05:38.9507470Z                   Usually the period should be greater than ``1`` to reduce the communication cost.
2025-07-17T07:05:38.9507560Z                   Otherwise, only DDP needs to be used.
2025-07-17T07:05:38.9507690Z     warmup_steps (int): The number of warm-up steps. During this stage,
2025-07-17T07:05:38.9507770Z                         model averaging is skipped.
2025-07-17T07:05:38.9507880Z     process_group: The process group to be used for all-reduce.
2025-07-17T07:05:38.9507970Z                    If ``None``, the default process group, which
2025-07-17T07:05:38.9508090Z                    is created by :func:`torch.distributed.init_process_group`,
2025-07-17T07:05:38.9508170Z                    will be used. (default: ``None``)
2025-07-17T07:05:38.9508170Z 
2025-07-17T07:05:38.9508220Z Example::
2025-07-17T07:05:38.9508220Z 
2025-07-17T07:05:38.9508300Z     >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:38.9508340Z     >>> import torch
2025-07-17T07:05:38.9508410Z     >>> import torch.distributed as dist
2025-07-17T07:05:38.9508600Z     >>> import torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook as post_localSGD
2025-07-17T07:05:38.9508760Z     >>> import torch.distributed.algorithms.model_averaging.averagers as averagers
2025-07-17T07:05:38.9508810Z     >>> import torch.nn as nn
2025-07-17T07:05:38.9508880Z     >>>
2025-07-17T07:05:38.9509000Z     >>> dist.init_process_group("nccl", rank=rank, world_size=16)
2025-07-17T07:05:38.9509060Z     >>> torch.cuda.set_device(rank)
2025-07-17T07:05:38.9509150Z     >>> module = nn.Linear(1, 1, bias=False).cuda()
2025-07-17T07:05:38.9509290Z     >>> model = nn.parallel.DistributedDataParallel(
2025-07-17T07:05:38.9509380Z     >>>    module, device_ids=[rank], output_device=rank
2025-07-17T07:05:38.9509420Z     >>> )
2025-07-17T07:05:38.9509510Z     >>> # Register a post-localSGD communication hook.
2025-07-17T07:05:38.9509690Z     >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100)
2025-07-17T07:05:38.9509780Z     >>> model.register_comm_hook(state, post_localSGD_hook)
2025-07-17T07:05:38.9509820Z     >>>
2025-07-17T07:05:38.9509980Z     >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step.
2025-07-17T07:05:38.9510100Z     >>> # After 100 steps, run model averaging every 4 steps.
2025-07-17T07:05:38.9510310Z     >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``.
2025-07-17T07:05:38.9510460Z     >>> averager = averagers.PeriodicModelAverager(period=4, warmup_steps=100)
2025-07-17T07:05:38.9510520Z     >>> for step in range(0, 200):
2025-07-17T07:05:38.9510580Z     >>>    optimizer.zero_grad()
2025-07-17T07:05:38.9510650Z     >>>    loss = loss_fn(output, labels)
2025-07-17T07:05:38.9510700Z     >>>    loss.backward()
2025-07-17T07:05:38.9510760Z     >>>    optimizer.step()
2025-07-17T07:05:38.9510880Z     >>>    # Will average model parameters globally every 4 steps. Thus,
2025-07-17T07:05:38.9511000Z     >>>    # inter-node communication only occurs every 4 iterations after
2025-07-17T07:05:38.9511070Z     >>>    # the initial ``warmup_steps`` period.
2025-07-17T07:05:38.9511170Z     >>>    averager.average_parameters(model.parameters())
2025-07-17T07:05:38.9511170Z 
2025-07-17T07:05:38.9511320Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.9511330Z 
2025-07-17T07:05:38.9511880Z msg = Cannot scrape callname=HierarchicalModelAverager in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/algorithms/model_averaging/hierarchical_model_averager.py line=19.
2025-07-17T07:05:38.9512040Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.9512040Z 
2025-07-17T07:05:38.9512240Z Runs hierarchical model averaging (`hierarchical SGD <https://arxiv.org/pdf/2010.12998.pdf>`_).
2025-07-17T07:05:38.9512240Z 
2025-07-17T07:05:38.9512430Z Process groups of different sizes are organized in a hierarchy, and they average parameters
2025-07-17T07:05:38.9512550Z by using different periods concurrently after the warm-up stage.
2025-07-17T07:05:38.9512800Z This is an extension of :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`
2025-07-17T07:05:38.9513000Z that supports `post-local SGD <https://arxiv.org/abs/1808.07217>`_, which essentially only supports
2025-07-17T07:05:38.9513180Z a two-level hierarchy: the intra-machine level and the global level, where the intra-machine
2025-07-17T07:05:38.9513390Z level is usually embedded in :meth:`~torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook`.
2025-07-17T07:05:38.9513570Z Similarly, the process groups within this class do not have such an intra-machine process
2025-07-17T07:05:38.9513730Z subgroup, which should be embedded by the post-local SGD communication hook instead.
2025-07-17T07:05:38.9513740Z 
2025-07-17T07:05:38.9513780Z Args:
2025-07-17T07:05:38.9513940Z     period_group_size_dict: An ordered dict mapping keys of model averaging period to
2025-07-17T07:05:38.9514060Z                             process group size, used for initializing process groups of
2025-07-17T07:05:38.9514200Z                             different sizes in a hierarchy to average parameters concurrently.
2025-07-17T07:05:38.9514360Z                             Particularly, at each iteration, there will be at most a single
2025-07-17T07:05:38.9514500Z                             process group that runs averaging -- the period of such group should
2025-07-17T07:05:38.9514660Z                             have the largest period which the current step can be divided by.
2025-07-17T07:05:38.9514770Z                             For example, if the dict has three keys: 2, 4, and 8,
2025-07-17T07:05:38.9514900Z                             then this means totally three process groups will be created to
2025-07-17T07:05:38.9515020Z                             average parameters every 2, 4, and 8 iterations, respectively.
2025-07-17T07:05:38.9515140Z                             At the 4th iteration, only the second process group will run
2025-07-17T07:05:38.9515250Z                             averaging, because the first process group should be a
2025-07-17T07:05:38.9515440Z                             subset of the second process group, and no need to execute the first
2025-07-17T07:05:38.9515550Z                             process group redundantly.
2025-07-17T07:05:38.9515680Z                             On the other hand, the third process group can only be triggered
2025-07-17T07:05:38.9515810Z                             every 8 iterations, so it will not be triggered at the 4th iteration.
2025-07-17T07:05:38.9516000Z     warmup_steps (int): The number of warm-up steps. During this stage, model averaging is skipped.
2025-07-17T07:05:38.9516260Z     process_group (ProcessGroup, optional): The overall process group containing all the processes that runs model averaging.
2025-07-17T07:05:38.9516370Z                                             If ``None``, the default process group, which is created
2025-07-17T07:05:38.9516500Z                                             by :func:`torch.distributed.init_process_group`, will be used.
2025-07-17T07:05:38.9516580Z                                             (default: ``None``)
2025-07-17T07:05:38.9516590Z 
2025-07-17T07:05:38.9516640Z Example::
2025-07-17T07:05:38.9516710Z     >>> # xdoctest: +SKIP('undefined rank')
2025-07-17T07:05:38.9516770Z     >>> from collections import OrderedDict
2025-07-17T07:05:38.9516820Z     >>> import torch
2025-07-17T07:05:38.9516890Z     >>> import torch.distributed as dist
2025-07-17T07:05:38.9517050Z     >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import (
2025-07-17T07:05:38.9517120Z     >>>     PostLocalSGDState,
2025-07-17T07:05:38.9517170Z     >>>     post_localSGD_hook,
2025-07-17T07:05:38.9517210Z     >>> )
2025-07-17T07:05:38.9517430Z     >>> import torch.distributed.algorithms.model_averaging.hierarchical_model_averager as hierarchicalSGD
2025-07-17T07:05:38.9517490Z     >>> import torch.nn as nn
2025-07-17T07:05:38.9517530Z     >>>
2025-07-17T07:05:38.9517640Z     >>> dist.init_process_group("nccl", rank=rank, world_size=16)
2025-07-17T07:05:38.9517700Z     >>> torch.cuda.set_device(rank)
2025-07-17T07:05:38.9517790Z     >>> module = nn.Linear(1, 1, bias=False).to(rank)
2025-07-17T07:05:38.9517910Z     >>> model = nn.parallel.DistributedDataParallel(
2025-07-17T07:05:38.9518000Z     >>>    module, device_ids=[rank], output_device=rank
2025-07-17T07:05:38.9518040Z     >>> )
2025-07-17T07:05:38.9518130Z     >>> # Register a post-localSGD communication hook.
2025-07-17T07:05:38.9518290Z     >>> # Assume that each machine has 4 GPUs, then each intra-machine subgroup has a size of 4.
2025-07-17T07:05:38.9518360Z     >>> subgroup, _ = dist.new_subgroups()
2025-07-17T07:05:38.9518550Z     >>> state = PostLocalSGDState(process_group=None, subgroup=subgroup, start_localSGD_iter=100)
2025-07-17T07:05:38.9518640Z     >>> model.register_comm_hook(state, post_localSGD_hook)
2025-07-17T07:05:38.9518680Z     >>>
2025-07-17T07:05:38.9518850Z     >>> # Average parameters among each group of 8 processes every 4 iterations, and among all
2025-07-17T07:05:38.9518930Z     >>> # the 16 processes every 16 iterations.
2025-07-17T07:05:38.9519060Z     >>> averager = hierarchicalSGD.HierarchicalModelAverager(
2025-07-17T07:05:38.9519210Z     >>>     period_group_size_dict=OrderedDict([(4, 8), (16, 16)]), warmup_steps=100)
2025-07-17T07:05:38.9519410Z     >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``.
2025-07-17T07:05:38.9519590Z     >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step.
2025-07-17T07:05:38.9519690Z     >>> # After 100 steps, run model averaging at two levels.
2025-07-17T07:05:38.9519750Z     >>> for step in range(0, 200):
2025-07-17T07:05:38.9519810Z     >>>    optimizer.zero_grad()
2025-07-17T07:05:38.9519870Z     >>>    loss = loss_fn(output, labels)
2025-07-17T07:05:38.9519920Z     >>>    loss.backward()
2025-07-17T07:05:38.9519980Z     >>>    optimizer.step()
2025-07-17T07:05:38.9520070Z     >>>    # Average parameters after ``optimizer.step()``.
2025-07-17T07:05:38.9520260Z     >>>    # Thus, the inter-node communication only occurs periodically after ``warmup_steps``.
2025-07-17T07:05:38.9520380Z     >>>    averager.average_parameters(model.parameters())
2025-07-17T07:05:38.9520390Z 
2025-07-17T07:05:38.9520430Z .. warning ::
2025-07-17T07:05:38.9520580Z     The last group size in the dict must be the size of the provided ``process_group``,
2025-07-17T07:05:38.9520720Z     which indicates model averaging at the highest level of the hierarchy.
2025-07-17T07:05:38.9520910Z     If ``process_group`` is not provided, then the last group size should be equal to the world size.
2025-07-17T07:05:38.9520910Z 
2025-07-17T07:05:38.9520960Z .. warning ::
2025-07-17T07:05:38.9521100Z     `HierarchicalModelAverager` is experimental and subject to change.
2025-07-17T07:05:38.9521100Z 
2025-07-17T07:05:38.9521250Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.9965200Z 
2025-07-17T07:05:38.9965970Z msg = Cannot scrape callname=post_localSGD_hook in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/post_localSGD_hook.py line=72.
2025-07-17T07:05:38.9966170Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.9966180Z 
2025-07-17T07:05:38.9966240Z Run post-localSGD algorithm.
2025-07-17T07:05:38.9966240Z 
2025-07-17T07:05:38.9966390Z This DDP communication hook is used for running post-localSGD algorithm,
2025-07-17T07:05:38.9966490Z by combining with a model averaging component (e.g.,
2025-07-17T07:05:38.9966700Z :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`)
2025-07-17T07:05:38.9966770Z that runs after the optimizer step.
2025-07-17T07:05:38.9966770Z 
2025-07-17T07:05:38.9966820Z Args:
2025-07-17T07:05:38.9966960Z     state (PostLocalSGDState): State information to run post-localSGD.
2025-07-17T07:05:38.9967140Z         Users mainly need to tune ``start_localSGD_iter`` to determine when to start local SGD.
2025-07-17T07:05:38.9967400Z     bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors.
2025-07-17T07:05:38.9967550Z         Note that since DDP comm hook only supports single process single device mode,
2025-07-17T07:05:38.9967650Z         only exactly one tensor is stored in this bucket.
2025-07-17T07:05:38.9967650Z 
2025-07-17T07:05:38.9967700Z Returns:
2025-07-17T07:05:38.9967850Z     Future handler of the communication, which updates the gradients in place.
2025-07-17T07:05:38.9967850Z 
2025-07-17T07:05:38.9967910Z Example::
2025-07-17T07:05:38.9967960Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:38.9968120Z     >>> state = PostLocalSGDState(process_group=process_group, subgroup=subgroup,
2025-07-17T07:05:38.9968200Z                               start_localSGD_iter=10)
2025-07-17T07:05:38.9968300Z     >>> ddp_model.register_comm_hook(state, post_localSGD_hook)
2025-07-17T07:05:38.9968520Z     >>> # Also need to establish a model averaging module and run model averaging after ``optimizer.step()``.
2025-07-17T07:05:38.9968910Z     >>> # Please refer to the examples in ``torch.distributed.algorithms.model_averaging.averagers`` module.
2025-07-17T07:05:38.9968910Z 
2025-07-17T07:05:38.9969070Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.9969100Z 
2025-07-17T07:05:38.9969580Z msg = Cannot scrape callname=powerSGD_hook in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py line=342.
2025-07-17T07:05:38.9969730Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.9969740Z 
2025-07-17T07:05:38.9969800Z Implement PowerSGD algorithm.
2025-07-17T07:05:38.9969800Z 
2025-07-17T07:05:38.9969930Z This DDP communication hook implements PowerSGD gradient compression
2025-07-17T07:05:38.9970130Z algorithm described in the `paper <https://arxiv.org/abs/1905.13727>`_.
2025-07-17T07:05:38.9970310Z Once gradient tensors are aggregated across all workers, this hook applies
2025-07-17T07:05:38.9970360Z compression as follows:
2025-07-17T07:05:38.9970360Z 
2025-07-17T07:05:38.9970620Z 1. Views the input flattened 1D gradient tensor as a list of per-parameter tensors, and divides all the tensors into two groups:
2025-07-17T07:05:38.9970630Z 
2025-07-17T07:05:38.9970870Z     1.1 The tensors that should be compressed before allreduce, because the compression can give enough saving in bandwidth.
2025-07-17T07:05:38.9970870Z 
2025-07-17T07:05:38.9971110Z     1.2 Rest of the tensors will be directly allreduced without compression, including all the vector tensors (for biases).
2025-07-17T07:05:38.9971110Z 
2025-07-17T07:05:38.9971170Z 2. Handles uncompressed tensors:
2025-07-17T07:05:38.9971180Z 
2025-07-17T07:05:38.9971470Z     2.1. Allocate contiguous memory for those uncompressed tensors, and allreduces all the uncompressed tensors as a batch, without compression;
2025-07-17T07:05:38.9971480Z 
2025-07-17T07:05:38.9971680Z     2.2. Copies the individual uncompressed tensors from the contiguous memory back to the input tensor.
2025-07-17T07:05:38.9971690Z 
2025-07-17T07:05:38.9971820Z 3. Handles the tensors that should be compressed by PowerSGD compression:
2025-07-17T07:05:38.9971830Z 
2025-07-17T07:05:38.9971980Z     3.1. For each tensor M, creates two low-rank tensors P and Q for decomposing M,
2025-07-17T07:05:38.9972200Z     such that M = PQ^T, where Q is initialized from a standard normal distribution and orthogonalized;
2025-07-17T07:05:38.9972200Z 
2025-07-17T07:05:38.9972290Z     3.2. Computes each P in Ps, which is equal to MQ;
2025-07-17T07:05:38.9972290Z 
2025-07-17T07:05:38.9972350Z     3.3. Allreduces Ps as a batch;
2025-07-17T07:05:38.9972350Z 
2025-07-17T07:05:38.9972420Z     3.4. Orthogonalizes each P in Ps;
2025-07-17T07:05:38.9972420Z 
2025-07-17T07:05:38.9972540Z     3.5. Computes each Q in Qs, which is approximately equal to M^TP;
2025-07-17T07:05:38.9972540Z 
2025-07-17T07:05:38.9972610Z     3.6. Allreduces Qs as a batch;
2025-07-17T07:05:38.9972610Z 
2025-07-17T07:05:38.9972790Z     3.7. Computes each M among all the compressed tensors, which is approximately equal to PQ^T.
2025-07-17T07:05:38.9972790Z 
2025-07-17T07:05:38.9973030Z Note that this communication hook enforces vanilla allreduce for the first ``state.start_powerSGD_iter`` iterations.
2025-07-17T07:05:38.9973200Z This not only gives the user more control over the tradeoff between speedup and accuracy,
2025-07-17T07:05:38.9973460Z but also helps abstract away some complexity of the internal optimization of DDP for future communication hook developers.
2025-07-17T07:05:38.9973460Z 
2025-07-17T07:05:38.9973500Z Args:
2025-07-17T07:05:38.9973760Z     state (PowerSGDState): State information to configure the compression rate and support error feedback, warm start, etc.
2025-07-17T07:05:38.9973970Z         To tune the compression configs, mainly need to tune ``matrix_approximation_rank``, ``start_powerSGD_iter``
2025-07-17T07:05:38.9974060Z         and ``min_compression_rate``.
2025-07-17T07:05:38.9974310Z     bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors.
2025-07-17T07:05:38.9974460Z         Note that since DDP comm hook only supports single process single device mode,
2025-07-17T07:05:38.9974580Z         only exactly one tensor is stored in this bucket.
2025-07-17T07:05:38.9974590Z 
2025-07-17T07:05:38.9974640Z Returns:
2025-07-17T07:05:38.9974780Z     Future handler of the communication, which updates the gradients in place.
2025-07-17T07:05:38.9974780Z 
2025-07-17T07:05:38.9974830Z Example::
2025-07-17T07:05:38.9974880Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:38.9975080Z     >>> state = PowerSGDState(process_group=process_group, matrix_approximation_rank=1,
2025-07-17T07:05:38.9975180Z                               start_powerSGD_iter=10, min_compression_rate=0.5)
2025-07-17T07:05:38.9975290Z     >>> ddp_model.register_comm_hook(state, powerSGD_hook)
2025-07-17T07:05:38.9975310Z 
2025-07-17T07:05:38.9975470Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.9975470Z 
2025-07-17T07:05:38.9975950Z msg = Cannot scrape callname=PostLocalSGDOptimizer in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/optim/post_localSGD_optimizer.py line=9.
2025-07-17T07:05:38.9976100Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.9976110Z 
2025-07-17T07:05:38.9976340Z Wraps an arbitrary :class:`torch.optim.Optimizer` and runs `post-local SGD <https://arxiv.org/abs/1808.07217>`_,
2025-07-17T07:05:38.9976430Z This optimizer runs local optimizer at every step.
2025-07-17T07:05:38.9976630Z After the warm-up stage, it averages parameters periodically after the local optimizer is applied.
2025-07-17T07:05:38.9976630Z 
2025-07-17T07:05:38.9976670Z Args:
2025-07-17T07:05:38.9976730Z     optim: The local optimizer.
2025-07-17T07:05:38.9976860Z     averager: A model averager instance to run post-localSGD algorithm.
2025-07-17T07:05:38.9976870Z 
2025-07-17T07:05:38.9976920Z Example::
2025-07-17T07:05:38.9976920Z 
2025-07-17T07:05:38.9976990Z     >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:38.9977050Z     >>> import torch
2025-07-17T07:05:38.9977110Z     >>> import torch.distributed as dist
2025-07-17T07:05:38.9977270Z     >>> import torch.distributed.algorithms.model_averaging.averagers as averagers
2025-07-17T07:05:38.9977330Z     >>> import torch.nn as nn
2025-07-17T07:05:38.9977450Z     >>> from torch.distributed.optim import PostLocalSGDOptimizer
2025-07-17T07:05:38.9977610Z     >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import (
2025-07-17T07:05:38.9977670Z     >>>   PostLocalSGDState,
2025-07-17T07:05:38.9977720Z     >>>   post_localSGD_hook,
2025-07-17T07:05:38.9977760Z     >>> )
2025-07-17T07:05:38.9977810Z     >>>
2025-07-17T07:05:38.9977900Z     >>> model = nn.parallel.DistributedDataParallel(
2025-07-17T07:05:38.9977990Z     >>>    module, device_ids=[rank], output_device=rank
2025-07-17T07:05:38.9978030Z     >>> )
2025-07-17T07:05:38.9978080Z     >>>
2025-07-17T07:05:38.9978160Z     >>> # Register a post-localSGD communication hook.
2025-07-17T07:05:38.9978350Z     >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100)
2025-07-17T07:05:38.9978440Z     >>> model.register_comm_hook(state, post_localSGD_hook)
2025-07-17T07:05:38.9978480Z     >>>
2025-07-17T07:05:38.9978600Z     >>> # Create a post-localSGD optimizer that wraps a local optimizer.
2025-07-17T07:05:38.9978750Z     >>> # Note that ``warmup_steps`` used in ``PostLocalSGDOptimizer`` must be the same as
2025-07-17T07:05:38.9978850Z     >>> # ``start_localSGD_iter`` used in ``PostLocalSGDState``.
2025-07-17T07:05:38.9978980Z     >>> local_optim = torch.optim.SGD(params=model.parameters(), lr=0.01)
2025-07-17T07:05:38.9979050Z     >>> opt = PostLocalSGDOptimizer(
2025-07-17T07:05:38.9979110Z     >>>     optim=local_optim,
2025-07-17T07:05:38.9979280Z     >>>     averager=averagers.PeriodicModelAverager(period=4, warmup_steps=100)
2025-07-17T07:05:38.9979330Z     >>> )
2025-07-17T07:05:38.9979370Z     >>>
2025-07-17T07:05:38.9979510Z     >>> # In the first 100 steps, DDP runs global gradient averaging at every step.
2025-07-17T07:05:38.9979720Z     >>> # After 100 steps, DDP runs gradient averaging within each subgroup (intra-node by default),
2025-07-17T07:05:38.9979940Z     >>> # and post-localSGD optimizer runs global model averaging every 4 steps after applying the local optimizer.
2025-07-17T07:05:38.9980000Z     >>> for step in range(0, 200):
2025-07-17T07:05:38.9980060Z     >>>    opt.zero_grad()
2025-07-17T07:05:38.9980120Z     >>>    loss = loss_fn(output, labels)
2025-07-17T07:05:38.9980170Z     >>>    loss.backward()
2025-07-17T07:05:38.9980220Z     >>>    opt.step()
2025-07-17T07:05:38.9980220Z 
2025-07-17T07:05:38.9980410Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:38.9980430Z 
2025-07-17T07:05:38.9980870Z msg = Cannot scrape callname=DistributedOptimizer in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/optim/optimizer.py line=129.
2025-07-17T07:05:38.9981030Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:38.9981030Z 
2025-07-17T07:05:38.9981180Z DistributedOptimizer takes remote references to parameters scattered
2025-07-17T07:05:38.9981320Z across workers and applies the given optimizer locally for each parameter.
2025-07-17T07:05:38.9981320Z 
2025-07-17T07:05:38.9981460Z This class uses :meth:`~torch.distributed.autograd.get_gradients` in order
2025-07-17T07:05:38.9981550Z to retrieve the gradients for specific parameters.
2025-07-17T07:05:38.9981550Z 
2025-07-17T07:05:38.9981600Z Concurrent calls to
2025-07-17T07:05:38.9981730Z :meth:`~torch.distributed.optim.DistributedOptimizer.step`,
2025-07-17T07:05:38.9981810Z either from the same or different clients, will
2025-07-17T07:05:38.9981950Z be serialized on each worker -- as each worker's optimizer can only work
2025-07-17T07:05:38.9982070Z on one set of gradients at a time. However, there is no guarantee that
2025-07-17T07:05:38.9982220Z the full forward-backward-optimizer sequence will execute for one client
2025-07-17T07:05:38.9982350Z at a time. This means that the gradients being applied may not correspond
2025-07-17T07:05:38.9982480Z to the latest forward pass executed on a given worker. Also, there is no
2025-07-17T07:05:38.9982540Z guaranteed ordering across workers.
2025-07-17T07:05:38.9982550Z 
2025-07-17T07:05:38.9982700Z `DistributedOptimizer` creates the local optimizer with TorchScript enabled
2025-07-17T07:05:38.9982840Z by default, so that optimizer updates are not blocked by the Python Global
2025-07-17T07:05:38.9982980Z Interpreter Lock (GIL) in the case of multithreaded training (e.g. Distributed
2025-07-17T07:05:38.9983120Z Model Parallel). This feature is currently enabled for most optimizers. You
2025-07-17T07:05:38.9983280Z can also follow `the recipe`__ in PyTorch tutorials to enable TorchScript support
2025-07-17T07:05:38.9983340Z for your own custom optimizers.
2025-07-17T07:05:38.9983340Z 
2025-07-17T07:05:38.9983390Z Args:
2025-07-17T07:05:38.9983510Z     optimizer_class (optim.Optimizer): the class of optimizer to
2025-07-17T07:05:38.9983570Z         instantiate on each worker.
2025-07-17T07:05:38.9983690Z     params_rref (list[RRef]): list of RRefs to local or remote parameters
2025-07-17T07:05:38.9983750Z         to optimize.
2025-07-17T07:05:38.9983870Z     args: arguments to pass to the optimizer constructor on each worker.
2025-07-17T07:05:38.9984010Z     kwargs: arguments to pass to the optimizer constructor on each worker.
2025-07-17T07:05:38.9984010Z 
2025-07-17T07:05:38.9984050Z Example::
2025-07-17T07:05:38.9984120Z     >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:38.9984220Z     >>> import torch.distributed.autograd as dist_autograd
2025-07-17T07:05:38.9984310Z     >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:38.9984360Z     >>> from torch import optim
2025-07-17T07:05:38.9984510Z     >>> from torch.distributed.optim import DistributedOptimizer
2025-07-17T07:05:38.9984570Z     >>>
2025-07-17T07:05:38.9984650Z     >>> with dist_autograd.context() as context_id:
2025-07-17T07:05:38.9984710Z     >>>   # Forward pass.
2025-07-17T07:05:38.9984830Z     >>>   rref1 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 3))
2025-07-17T07:05:38.9984950Z     >>>   rref2 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 1))
2025-07-17T07:05:38.9985020Z     >>>   loss = rref1.to_here() + rref2.to_here()
2025-07-17T07:05:38.9985060Z     >>>
2025-07-17T07:05:38.9985110Z     >>>   # Backward pass.
2025-07-17T07:05:38.9985200Z     >>>   dist_autograd.backward(context_id, [loss.sum()])
2025-07-17T07:05:38.9985240Z     >>>
2025-07-17T07:05:38.9985290Z     >>>   # Optimizer.
2025-07-17T07:05:38.9985430Z     >>>   dist_optim = DistributedOptimizer(
2025-07-17T07:05:38.9985500Z     >>>      optim.SGD,
2025-07-17T07:05:38.9985560Z     >>>      [rref1, rref2],
2025-07-17T07:05:38.9985600Z     >>>      lr=0.05,
2025-07-17T07:05:38.9985640Z     >>>   )
2025-07-17T07:05:38.9985700Z     >>>   dist_optim.step(context_id)
2025-07-17T07:05:38.9985710Z 
2025-07-17T07:05:38.9985800Z __ https://github.com/pytorch/tutorials/pull/1465
2025-07-17T07:05:38.9985800Z 
2025-07-17T07:05:38.9985950Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.0145370Z 
2025-07-17T07:05:39.0146130Z msg = Cannot scrape callname=ZeroRedundancyOptimizer in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/optim/zero_redundancy_optimizer.py line=284.
2025-07-17T07:05:39.0146300Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.0146310Z 
2025-07-17T07:05:39.0146570Z Wrap an arbitrary :class:`optim.Optimizer <torch.optim.Optimizer>` and shards its states across ranks in the group.
2025-07-17T07:05:39.0146570Z 
2025-07-17T07:05:39.0146740Z The sharing is done as described by `ZeRO <https://arxiv.org/abs/1910.02054>`_.
2025-07-17T07:05:39.0146740Z 
2025-07-17T07:05:39.0146840Z The local optimizer instance in each rank is only
2025-07-17T07:05:39.0146990Z responsible for updating approximately ``1 / world_size`` parameters and
2025-07-17T07:05:39.0147120Z hence only needs to keep ``1 / world_size`` optimizer states. After
2025-07-17T07:05:39.0147280Z parameters are updated locally, each rank will broadcast its parameters to
2025-07-17T07:05:39.0147390Z all other peers to keep all model replicas in the same state.
2025-07-17T07:05:39.0147520Z ``ZeroRedundancyOptimizer`` can be used in conjunction with
2025-07-17T07:05:39.0147680Z :class:`torch.nn.parallel.DistributedDataParallel` to reduce per-rank peak
2025-07-17T07:05:39.0147730Z memory consumption.
2025-07-17T07:05:39.0147740Z 
2025-07-17T07:05:39.0147900Z ``ZeroRedundancyOptimizer`` uses a sorted-greedy algorithm to pack a number
2025-07-17T07:05:39.0148050Z of parameters at each rank. Each parameter belongs to a single rank and is
2025-07-17T07:05:39.0148200Z not divided among ranks. The partition is arbitrary and might not match the
2025-07-17T07:05:39.0148280Z the parameter registration or usage order.
2025-07-17T07:05:39.0148280Z 
2025-07-17T07:05:39.0148330Z Arguments:
2025-07-17T07:05:39.0148450Z     params (``Iterable``): an ``Iterable`` of :class:`torch.Tensor` s
2025-07-17T07:05:39.0148580Z         or :class:`dict` s giving all parameters, which will be sharded
2025-07-17T07:05:39.0148630Z         across ranks.
2025-07-17T07:05:39.0148630Z 
2025-07-17T07:05:39.0148680Z Keyword Args:
2025-07-17T07:05:39.0148820Z     optimizer_class (:class:`torch.nn.Optimizer`): the class of the local
2025-07-17T07:05:39.0148870Z         optimizer.
2025-07-17T07:05:39.0149000Z     process_group (``ProcessGroup``, optional): ``torch.distributed``
2025-07-17T07:05:39.0149360Z         ``ProcessGroup`` (default: ``dist.group.WORLD`` initialized by
2025-07-17T07:05:39.0149490Z         :meth:`torch.distributed.init_process_group`).
2025-07-17T07:05:39.0149630Z     parameters_as_bucket_view (bool, optional): if ``True``, parameters are
2025-07-17T07:05:39.0149800Z         packed into buckets to speed up communication, and ``param.data``
2025-07-17T07:05:39.0149920Z         fields point to bucket views at different offsets; if ``False``,
2025-07-17T07:05:39.0150050Z         each individual parameter is communicated separately, and each
2025-07-17T07:05:39.0150140Z         ``params.data`` stays intact (default: ``False``).
2025-07-17T07:05:39.0150260Z     overlap_with_ddp (bool, optional): if ``True``, :meth:`step` is
2025-07-17T07:05:39.0150380Z         overlapped with :class:`DistributedDataParallel` 's gradient
2025-07-17T07:05:39.0150510Z         synchronization; this requires (1) either a functional optimizer
2025-07-17T07:05:39.0150660Z         for the ``optimizer_class`` argument or one with a functional
2025-07-17T07:05:39.0150800Z         equivalent and (2) registering a DDP communication hook
2025-07-17T07:05:39.0150930Z         constructed from one of the functions in ``ddp_zero_hook.py``;
2025-07-17T07:05:39.0151030Z         parameters are packed into buckets matching those in
2025-07-17T07:05:39.0151120Z         :class:`DistributedDataParallel`, meaning that the
2025-07-17T07:05:39.0151210Z         ``parameters_as_bucket_view`` argument is ignored.
2025-07-17T07:05:39.0151330Z         If ``False``, :meth:`step` runs disjointly after the backward pass
2025-07-17T07:05:39.0151380Z         (per normal).
2025-07-17T07:05:39.0151440Z         (default: ``False``)
2025-07-17T07:05:39.0151560Z     **defaults: any trailing arguments, which are forwarded to the local
2025-07-17T07:05:39.0151620Z         optimizer.
2025-07-17T07:05:39.0151620Z 
2025-07-17T07:05:39.0151670Z Example::
2025-07-17T07:05:39.0151670Z 
2025-07-17T07:05:39.0151730Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:39.0151790Z     >>> import torch.nn as nn
2025-07-17T07:05:39.0151920Z     >>> from torch.distributed.optim import ZeroRedundancyOptimizer
2025-07-17T07:05:39.0152040Z     >>> from torch.nn.parallel import DistributedDataParallel as DDP
2025-07-17T07:05:39.0152190Z     >>> model = nn.Sequential(*[nn.Linear(2000, 2000).to(rank) for _ in range(20)])
2025-07-17T07:05:39.0152250Z     >>> ddp = DDP(model, device_ids=[rank])
2025-07-17T07:05:39.0152320Z     >>> opt = ZeroRedundancyOptimizer(
2025-07-17T07:05:39.0152380Z     >>>     ddp.parameters(),
2025-07-17T07:05:39.0152450Z     >>>     optimizer_class=torch.optim.Adam,
2025-07-17T07:05:39.0152500Z     >>>     lr=0.01
2025-07-17T07:05:39.0152540Z     >>> )
2025-07-17T07:05:39.0152600Z     >>> ddp(inputs).sum().backward()
2025-07-17T07:05:39.0152640Z     >>> opt.step()
2025-07-17T07:05:39.0152640Z 
2025-07-17T07:05:39.0152700Z .. warning::
2025-07-17T07:05:39.0152820Z     Currently, ``ZeroRedundancyOptimizer`` requires that all of the
2025-07-17T07:05:39.0152910Z     passed-in parameters are the same dense type.
2025-07-17T07:05:39.0152920Z 
2025-07-17T07:05:39.0152960Z .. warning::
2025-07-17T07:05:39.0153100Z     If you pass ``overlap_with_ddp=True``, be wary of the following: Given
2025-07-17T07:05:39.0153220Z     the way that overlapping :class:`DistributedDataParallel` with
2025-07-17T07:05:39.0153360Z     :class:`ZeroRedundancyOptimizer` is currently implemented, the first
2025-07-17T07:05:39.0153490Z     two or three training iterations do not perform parameter updates in
2025-07-17T07:05:39.0153610Z     the optimizer step, depending on if ``static_graph=False`` or
2025-07-17T07:05:39.0153720Z     ``static_graph=True``, respectively. This is because it needs
2025-07-17T07:05:39.0153830Z     information about the gradient bucketing strategy used by
2025-07-17T07:05:39.0153960Z     :class:`DistributedDataParallel`, which is not finalized until the
2025-07-17T07:05:39.0154080Z     second forward pass if ``static_graph=False`` or until the third
2025-07-17T07:05:39.0154230Z     forward pass if ``static_graph=True``. To adjust for this, one option
2025-07-17T07:05:39.0154300Z     is to prepend dummy inputs.
2025-07-17T07:05:39.0154300Z 
2025-07-17T07:05:39.0154460Z .. warning:: ZeroRedundancyOptimizer is experimental and subject to change.
2025-07-17T07:05:39.0154490Z 
2025-07-17T07:05:39.0154650Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.0154650Z 
2025-07-17T07:05:39.0155190Z msg = Cannot scrape callname=FullyShardedDataParallel.set_state_dict_type in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=637.
2025-07-17T07:05:39.0155350Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.0155500Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module.
2025-07-17T07:05:39.0155500Z 
2025-07-17T07:05:39.0155680Z         Also takes (optional) configuration for the model's and optimizer's state dict.
2025-07-17T07:05:39.0155830Z         The target module does not have to be a FSDP module. If the target
2025-07-17T07:05:39.0155960Z         module is a FSDP module, its ``state_dict_type`` will also be changed.
2025-07-17T07:05:39.0155960Z 
2025-07-17T07:05:39.0156080Z         .. note:: This API should be called for only the top-level (root)
2025-07-17T07:05:39.0156130Z             module.
2025-07-17T07:05:39.0156130Z 
2025-07-17T07:05:39.0156250Z         .. note:: This API enables users to transparently use the conventional
2025-07-17T07:05:39.0156370Z             ``state_dict`` API to take model checkpoints in cases where the
2025-07-17T07:05:39.0156490Z             root FSDP module is wrapped by another ``nn.Module``. For example,
2025-07-17T07:05:39.0156620Z             the following will ensure ``state_dict`` is called on all non-FSDP
2025-07-17T07:05:39.0156760Z             instances, while dispatching into `sharded_state_dict` implementation
2025-07-17T07:05:39.0156810Z             for FSDP:
2025-07-17T07:05:39.0156820Z 
2025-07-17T07:05:39.0156870Z         Example::
2025-07-17T07:05:39.0156870Z 
2025-07-17T07:05:39.0156950Z             >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:39.0157010Z             >>> model = DDP(FSDP(...))
2025-07-17T07:05:39.0157070Z             >>> FSDP.set_state_dict_type(
2025-07-17T07:05:39.0157120Z             >>>     model,
2025-07-17T07:05:39.0157200Z             >>>     StateDictType.SHARDED_STATE_DICT,
2025-07-17T07:05:39.0157330Z             >>>     state_dict_config = ShardedStateDictConfig(offload_to_cpu=True),
2025-07-17T07:05:39.0157470Z             >>>     optim_state_dict_config = OptimStateDictConfig(offload_to_cpu=True),
2025-07-17T07:05:39.0157520Z             >>> )
2025-07-17T07:05:39.0157600Z             >>> param_state_dict = model.state_dict()
2025-07-17T07:05:39.0157710Z             >>> optim_state_dict = FSDP.optim_state_dict(model, optim)
2025-07-17T07:05:39.0157710Z 
2025-07-17T07:05:39.0157760Z         Args:
2025-07-17T07:05:39.0157840Z             module (torch.nn.Module): Root module.
2025-07-17T07:05:39.0157980Z             state_dict_type (StateDictType): the desired ``state_dict_type`` to set.
2025-07-17T07:05:39.0158120Z             state_dict_config (Optional[StateDictConfig]): the configuration for the
2025-07-17T07:05:39.0158190Z                 target ``state_dict_type``.
2025-07-17T07:05:39.0158340Z             optim_state_dict_config (Optional[OptimStateDictConfig]): the configuration
2025-07-17T07:05:39.0158410Z                 for the optimizer state dict.
2025-07-17T07:05:39.0158410Z 
2025-07-17T07:05:39.0158460Z         Returns:
2025-07-17T07:05:39.0158590Z             A StateDictSettings that include the previous state_dict type and
2025-07-17T07:05:39.0158650Z             configuration for the module.
2025-07-17T07:05:39.0158700Z         
2025-07-17T07:05:39.0158850Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.0158850Z 
2025-07-17T07:05:39.0159400Z msg = Cannot scrape callname=FullyShardedDataParallel.state_dict_type in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=795.
2025-07-17T07:05:39.0159580Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.0159730Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module.
2025-07-17T07:05:39.0159730Z 
2025-07-17T07:05:39.0159930Z         This context manager has the same functions as :meth:`set_state_dict_type`. Read the document of
2025-07-17T07:05:39.0160000Z         :meth:`set_state_dict_type` for the detail.
2025-07-17T07:05:39.0160010Z 
2025-07-17T07:05:39.0160050Z         Example::
2025-07-17T07:05:39.0160060Z 
2025-07-17T07:05:39.0160140Z             >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:39.0160190Z             >>> model = DDP(FSDP(...))
2025-07-17T07:05:39.0160290Z             >>> with FSDP.state_dict_type(
2025-07-17T07:05:39.0160380Z             >>>     model,
2025-07-17T07:05:39.0160460Z             >>>     StateDictType.SHARDED_STATE_DICT,
2025-07-17T07:05:39.0160500Z             >>> ):
2025-07-17T07:05:39.0160580Z             >>>     checkpoint = model.state_dict()
2025-07-17T07:05:39.0160580Z 
2025-07-17T07:05:39.0160630Z         Args:
2025-07-17T07:05:39.0160700Z             module (torch.nn.Module): Root module.
2025-07-17T07:05:39.0160840Z             state_dict_type (StateDictType): the desired ``state_dict_type`` to set.
2025-07-17T07:05:39.0160990Z             state_dict_config (Optional[StateDictConfig]): the model ``state_dict``
2025-07-17T07:05:39.0161080Z                 configuration for the target ``state_dict_type``.
2025-07-17T07:05:39.0161230Z             optim_state_dict_config (Optional[OptimStateDictConfig]): the optimizer
2025-07-17T07:05:39.0161350Z                ``state_dict`` configuration for the target ``state_dict_type``.
2025-07-17T07:05:39.0161400Z         
2025-07-17T07:05:39.0161560Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.0750550Z 
2025-07-17T07:05:39.0751340Z msg = Cannot scrape callname=FullyShardedDataParallel.optim_state_dict in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1808.
2025-07-17T07:05:39.0751520Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.0751520Z 
2025-07-17T07:05:39.0751670Z Transform the state-dict of an optimizer corresponding to a sharded model.
2025-07-17T07:05:39.0751670Z 
2025-07-17T07:05:39.0751790Z The given state-dict can be transformed to one of three types:
2025-07-17T07:05:39.0751970Z 1) full optimizer state_dict, 2) sharded optimizer state_dict, 3) local optimizer state_dict.
2025-07-17T07:05:39.0751980Z 
2025-07-17T07:05:39.0752130Z For full optimizer state_dict, all states are unflattened and not sharded.
2025-07-17T07:05:39.0752270Z Rank0 only and CPU only can be specified via :meth:`state_dict_type` to
2025-07-17T07:05:39.0752320Z avoid OOM.
2025-07-17T07:05:39.0752320Z 
2025-07-17T07:05:39.0752460Z For sharded optimizer state_dict, all states are unflattened but sharded.
2025-07-17T07:05:39.0752590Z CPU only can be specified via :meth:`state_dict_type` to further save
2025-07-17T07:05:39.0752640Z memory.
2025-07-17T07:05:39.0752640Z 
2025-07-17T07:05:39.0752780Z For local state_dict, no transformation will be performed. But a state
2025-07-17T07:05:39.0752920Z will be converted from nn.Tensor to ShardedTensor to represent its sharding
2025-07-17T07:05:39.0752990Z nature (this is not supported yet).
2025-07-17T07:05:39.0752990Z 
2025-07-17T07:05:39.0753040Z Example::
2025-07-17T07:05:39.0753080Z 
2025-07-17T07:05:39.0753160Z     >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:39.0753310Z     >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-07-17T07:05:39.0753410Z     >>> from torch.distributed.fsdp import StateDictType
2025-07-17T07:05:39.0753640Z     >>> from torch.distributed.fsdp import FullStateDictConfig
2025-07-17T07:05:39.0753770Z     >>> from torch.distributed.fsdp import FullOptimStateDictConfig
2025-07-17T07:05:39.0753900Z     >>> # Save a checkpoint
2025-07-17T07:05:39.0753960Z     >>> model, optim = ...
2025-07-17T07:05:39.0754020Z     >>> FSDP.set_state_dict_type(
2025-07-17T07:05:39.0754070Z     >>>     model,
2025-07-17T07:05:39.0754140Z     >>>     StateDictType.FULL_STATE_DICT,
2025-07-17T07:05:39.0754220Z     >>>     FullStateDictConfig(rank0_only=False),
2025-07-17T07:05:39.0754300Z     >>>     FullOptimStateDictConfig(rank0_only=False),
2025-07-17T07:05:39.0754350Z     >>> )
2025-07-17T07:05:39.0754410Z     >>> state_dict = model.state_dict()
2025-07-17T07:05:39.0754510Z     >>> optim_state_dict = FSDP.optim_state_dict(model, optim)
2025-07-17T07:05:39.0754600Z     >>> save_a_checkpoint(state_dict, optim_state_dict)
2025-07-17T07:05:39.0754830Z     >>> # Load a checkpoint
2025-07-17T07:05:39.0754960Z     >>> model, optim = ...
2025-07-17T07:05:39.0755050Z     >>> state_dict, optim_state_dict = load_a_checkpoint()
2025-07-17T07:05:39.0755120Z     >>> FSDP.set_state_dict_type(
2025-07-17T07:05:39.0755160Z     >>>     model,
2025-07-17T07:05:39.0755230Z     >>>     StateDictType.FULL_STATE_DICT,
2025-07-17T07:05:39.0755300Z     >>>     FullStateDictConfig(rank0_only=False),
2025-07-17T07:05:39.0755390Z     >>>     FullOptimStateDictConfig(rank0_only=False),
2025-07-17T07:05:39.0755430Z     >>> )
2025-07-17T07:05:39.0761640Z     >>> model.load_state_dict(state_dict)
2025-07-17T07:05:39.0761770Z     >>> optim_state_dict = FSDP.optim_state_dict_to_load(
2025-07-17T07:05:39.0761840Z     >>>     model, optim, optim_state_dict
2025-07-17T07:05:39.0761880Z     >>> )
2025-07-17T07:05:39.0761980Z     >>> optim.load_state_dict(optim_state_dict)
2025-07-17T07:05:39.0761980Z 
2025-07-17T07:05:39.0762020Z Args:
2025-07-17T07:05:39.0762150Z     model (torch.nn.Module): Root module (which may or may not be a
2025-07-17T07:05:39.0762270Z         :class:`FullyShardedDataParallel` instance) whose parameters
2025-07-17T07:05:39.0762360Z         were passed into the optimizer ``optim``.
2025-07-17T07:05:39.0762470Z     optim (torch.optim.Optimizer): Optimizer for ``model`` 's
2025-07-17T07:05:39.0762520Z         parameters.
2025-07-17T07:05:39.0762650Z     optim_state_dict (Dict[str, Any]): the target optimizer state_dict to
2025-07-17T07:05:39.0762780Z         transform. If the value is None, optim.state_dict() will be used. (
2025-07-17T07:05:39.0762830Z         Default: ``None``)
2025-07-17T07:05:39.0762980Z     group (dist.ProcessGroup): Model's process group across which parameters
2025-07-17T07:05:39.0763090Z         are sharded or ``None`` if using the default process group. (
2025-07-17T07:05:39.0763140Z         Default: ``None``)
2025-07-17T07:05:39.0763140Z 
2025-07-17T07:05:39.0763190Z Returns:
2025-07-17T07:05:39.0763310Z     Dict[str, Any]: A :class:`dict` containing the optimizer state for
2025-07-17T07:05:39.0763410Z     ``model``. The sharding of the optimizer state is based on
2025-07-17T07:05:39.0763460Z     ``state_dict_type``.
2025-07-17T07:05:39.0763470Z 
2025-07-17T07:05:39.0763620Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.0763620Z 
2025-07-17T07:05:39.0764180Z msg = Cannot scrape callname=FullyShardedDataParallel.optim_state_dict_to_load in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1906.
2025-07-17T07:05:39.0764330Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.0764340Z 
2025-07-17T07:05:39.0764550Z Convert an optimizer state-dict so that it can be loaded into the optimizer associated with the FSDP model.
2025-07-17T07:05:39.0764550Z 
2025-07-17T07:05:39.0764660Z Given a ``optim_state_dict`` that is transformed through
2025-07-17T07:05:39.0764870Z :meth:`optim_state_dict`, it gets converted to the flattened optimizer
2025-07-17T07:05:39.0765000Z state_dict that can be loaded to ``optim`` which is the optimizer for
2025-07-17T07:05:39.0765120Z ``model``. ``model`` must be sharded by FullyShardedDataParallel.
2025-07-17T07:05:39.0765140Z 
2025-07-17T07:05:39.0765230Z     >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:39.0765370Z     >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-07-17T07:05:39.0765470Z     >>> from torch.distributed.fsdp import StateDictType
2025-07-17T07:05:39.0765570Z     >>> from torch.distributed.fsdp import FullStateDictConfig
2025-07-17T07:05:39.0765690Z     >>> from torch.distributed.fsdp import FullOptimStateDictConfig
2025-07-17T07:05:39.0765750Z     >>> # Save a checkpoint
2025-07-17T07:05:39.0765800Z     >>> model, optim = ...
2025-07-17T07:05:39.0765860Z     >>> FSDP.set_state_dict_type(
2025-07-17T07:05:39.0765900Z     >>>     model,
2025-07-17T07:05:39.0765990Z     >>>     StateDictType.FULL_STATE_DICT,
2025-07-17T07:05:39.0766090Z     >>>     FullStateDictConfig(rank0_only=False),
2025-07-17T07:05:39.0766180Z     >>>     FullOptimStateDictConfig(rank0_only=False),
2025-07-17T07:05:39.0766220Z     >>> )
2025-07-17T07:05:39.0766280Z     >>> state_dict = model.state_dict()
2025-07-17T07:05:39.0766350Z     >>> original_osd = optim.state_dict()
2025-07-17T07:05:39.0766430Z     >>> optim_state_dict = FSDP.optim_state_dict(
2025-07-17T07:05:39.0766470Z     >>>     model,
2025-07-17T07:05:39.0766510Z     >>>     optim,
2025-07-17T07:05:39.0766570Z     >>>     optim_state_dict=original_osd
2025-07-17T07:05:39.0766620Z     >>> )
2025-07-17T07:05:39.0766700Z     >>> save_a_checkpoint(state_dict, optim_state_dict)
2025-07-17T07:05:39.0766750Z     >>> # Load a checkpoint
2025-07-17T07:05:39.0766810Z     >>> model, optim = ...
2025-07-17T07:05:39.0766890Z     >>> state_dict, optim_state_dict = load_a_checkpoint()
2025-07-17T07:05:39.0766950Z     >>> FSDP.set_state_dict_type(
2025-07-17T07:05:39.0767000Z     >>>     model,
2025-07-17T07:05:39.0767070Z     >>>     StateDictType.FULL_STATE_DICT,
2025-07-17T07:05:39.0767140Z     >>>     FullStateDictConfig(rank0_only=False),
2025-07-17T07:05:39.0767230Z     >>>     FullOptimStateDictConfig(rank0_only=False),
2025-07-17T07:05:39.0767270Z     >>> )
2025-07-17T07:05:39.0767330Z     >>> model.load_state_dict(state_dict)
2025-07-17T07:05:39.0767420Z     >>> optim_state_dict = FSDP.optim_state_dict_to_load(
2025-07-17T07:05:39.0767490Z     >>>     model, optim, optim_state_dict
2025-07-17T07:05:39.0767530Z     >>> )
2025-07-17T07:05:39.0767600Z     >>> optim.load_state_dict(optim_state_dict)
2025-07-17T07:05:39.0767600Z 
2025-07-17T07:05:39.0767640Z Args:
2025-07-17T07:05:39.0767760Z     model (torch.nn.Module): Root module (which may or may not be a
2025-07-17T07:05:39.0767880Z         :class:`FullyShardedDataParallel` instance) whose parameters
2025-07-17T07:05:39.0767960Z         were passed into the optimizer ``optim``.
2025-07-17T07:05:39.0768070Z     optim (torch.optim.Optimizer): Optimizer for ``model`` 's
2025-07-17T07:05:39.0768120Z         parameters.
2025-07-17T07:05:39.0768250Z     optim_state_dict (Dict[str, Any]): The optimizer states to be loaded.
2025-07-17T07:05:39.0768370Z     is_named_optimizer (bool): Is this optimizer a NamedOptimizer or
2025-07-17T07:05:39.0768490Z         KeyedOptimizer. Only set to True if ``optim`` is TorchRec's
2025-07-17T07:05:39.0768590Z         KeyedOptimizer or torch.distributed's NamedOptimizer.
2025-07-17T07:05:39.0768710Z     load_directly (bool): If this is set to True, this API will also
2025-07-17T07:05:39.0768830Z         call optim.load_state_dict(result) before returning the result.
2025-07-17T07:05:39.0768960Z         Otherwise, users are responsible to call ``optim.load_state_dict()``
2025-07-17T07:05:39.0769020Z         (Default: ``False``)
2025-07-17T07:05:39.0769160Z     group (dist.ProcessGroup): Model's process group across which parameters
2025-07-17T07:05:39.0769270Z         are sharded or ``None`` if using the default process group. (
2025-07-17T07:05:39.0769340Z         Default: ``None``)
2025-07-17T07:05:39.0769350Z 
2025-07-17T07:05:39.0769500Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.0769500Z 
2025-07-17T07:05:39.0769940Z msg = Cannot scrape callname=MixedPrecision in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/fsdp/api.py line=114.
2025-07-17T07:05:39.0770100Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.0770100Z 
2025-07-17T07:05:39.0770200Z This configures FSDP-native mixed precision training.
2025-07-17T07:05:39.0770200Z 
2025-07-17T07:05:39.0770250Z Attributes:
2025-07-17T07:05:39.0770390Z     param_dtype (Optional[torch.dtype]): This specifies the dtype for model
2025-07-17T07:05:39.0770510Z         parameters during forward and backward and thus the dtype for
2025-07-17T07:05:39.0770710Z         forward and backward computation. Outside forward and backward, the
2025-07-17T07:05:39.0770850Z         *sharded* parameters are kept in full precision (e.g. for the
2025-07-17T07:05:39.0770980Z         optimizer step), and for model checkpointing, the parameters are
2025-07-17T07:05:39.0771070Z         always saved in full precision. (Default: ``None``)
2025-07-17T07:05:39.0771200Z     reduce_dtype (Optional[torch.dtype]): This specifies the dtype for
2025-07-17T07:05:39.0771330Z         gradient reduction (i.e. reduce-scatter or all-reduce). If this is
2025-07-17T07:05:39.0771440Z         ``None`` but ``param_dtype`` is not ``None``, then this takes on
2025-07-17T07:05:39.0771560Z         the ``param_dtype`` value, still running gradient reduction in low
2025-07-17T07:05:39.0771680Z         precision. This is permitted to differ from ``param_dtype``, e.g.
2025-07-17T07:05:39.0771800Z         to force gradient reduction to run in full precision. (Default:
2025-07-17T07:05:39.0771850Z         ``None``)
2025-07-17T07:05:39.0771980Z     buffer_dtype (Optional[torch.dtype]): This specifies the dtype for
2025-07-17T07:05:39.0772100Z         buffers. FSDP does not shard buffers. Rather, FSDP casts them to
2025-07-17T07:05:39.0772220Z         ``buffer_dtype`` in the first forward pass and keeps them in that
2025-07-17T07:05:39.0772350Z         dtype thereafter. For model checkpointing, the buffers are saved
2025-07-17T07:05:39.0772460Z         in full precision except for ``LOCAL_STATE_DICT``. (Default:
2025-07-17T07:05:39.0772500Z         ``None``)
2025-07-17T07:05:39.0772620Z     keep_low_precision_grads (bool): If ``False``, then FSDP upcasts
2025-07-17T07:05:39.0772750Z         gradients to full precision after the backward pass in preparation
2025-07-17T07:05:39.0772870Z         for the optimizer step. If ``True``, then FSDP keeps the gradients
2025-07-17T07:05:39.0772990Z         in the dtype used for gradient reduction, which can save memory if
2025-07-17T07:05:39.0773110Z         using a custom optimizer that supports running in low precision.
2025-07-17T07:05:39.0773170Z         (Default: ``False``)
2025-07-17T07:05:39.0773300Z     cast_forward_inputs (bool): If ``True``, then this FSDP module casts
2025-07-17T07:05:39.0773420Z         its forward args and kwargs to ``param_dtype``. This is to ensure
2025-07-17T07:05:39.0773550Z         that parameter and input dtypes match for forward computation, as
2025-07-17T07:05:39.0773670Z         required by many ops. This may need to be set to ``True`` when only
2025-07-17T07:05:39.0773800Z         applying mixed precision to some but not all FSDP modules, in which
2025-07-17T07:05:39.0773930Z         case a mixed-precision FSDP submodule needs to recast its inputs.
2025-07-17T07:05:39.0773980Z         (Default: ``False``)
2025-07-17T07:05:39.0774110Z     cast_root_forward_inputs (bool): If ``True``, then the root FSDP module
2025-07-17T07:05:39.0774230Z         casts its forward args and kwargs to ``param_dtype``, overriding
2025-07-17T07:05:39.0774350Z         the value of ``cast_forward_inputs``. For non-root FSDP modules,
2025-07-17T07:05:39.0774460Z         this does not do anything. (Default: ``True``)
2025-07-17T07:05:39.0774600Z     _module_classes_to_ignore: (Sequence[Type[nn.Module]]): This specifies
2025-07-17T07:05:39.0774710Z         module classes to ignore for mixed precision when using an
2025-07-17T07:05:39.0774850Z         ``auto_wrap_policy``: Modules of these classes will have FSDP
2025-07-17T07:05:39.0774970Z         applied to them separately with mixed precision disabled (meaning
2025-07-17T07:05:39.0775090Z         that the final FSDP construction would deviate from the specified
2025-07-17T07:05:39.0775210Z         policy). If ``auto_wrap_policy`` is not specified, then this does
2025-07-17T07:05:39.0775330Z         not do anything. This API is experimental and subject to change.
2025-07-17T07:05:39.0775390Z         (Default: ``(_BatchNorm,)``)
2025-07-17T07:05:39.0775400Z 
2025-07-17T07:05:39.0775530Z .. note:: This API is experimental and subject to change.
2025-07-17T07:05:39.0775560Z 
2025-07-17T07:05:39.0775690Z .. note:: Only floating point tensors are cast to their specified dtypes.
2025-07-17T07:05:39.0775700Z 
2025-07-17T07:05:39.0775810Z .. note:: In ``summon_full_params``, parameters are forced to full
2025-07-17T07:05:39.0775870Z     precision, but buffers are not.
2025-07-17T07:05:39.0775870Z 
2025-07-17T07:05:39.0776000Z .. note:: Layer norm and batch norm accumulate in ``float32`` even when
2025-07-17T07:05:39.0776120Z     their inputs are in a low precision like ``float16`` or ``bfloat16``.
2025-07-17T07:05:39.0776260Z     Disabling FSDP's mixed precision for those norm modules only means that
2025-07-17T07:05:39.0776390Z     the affine parameters are kept in ``float32``. However, this incurs
2025-07-17T07:05:39.0776530Z     separate all-gathers and reduce-scatters for those norm modules, which
2025-07-17T07:05:39.0776660Z     may be inefficient, so if the workload permits, the user should prefer
2025-07-17T07:05:39.0776750Z     to still apply mixed precision to those modules.
2025-07-17T07:05:39.0776750Z 
2025-07-17T07:05:39.0776870Z .. note:: By default, if the user passes a model with any ``_BatchNorm``
2025-07-17T07:05:39.0777000Z     modules and specifies an ``auto_wrap_policy``, then the batch norm
2025-07-17T07:05:39.0777130Z     modules will have FSDP applied to them separately with mixed precision
2025-07-17T07:05:39.0777240Z     disabled. See the ``_module_classes_to_ignore`` argument.
2025-07-17T07:05:39.0777240Z 
2025-07-17T07:05:39.0777370Z .. note:: ``MixedPrecision`` has ``cast_root_forward_inputs=True`` and
2025-07-17T07:05:39.0777490Z     ``cast_forward_inputs=False`` by default. For the root FSDP instance,
2025-07-17T07:05:39.0777590Z     its ``cast_root_forward_inputs`` takes precedence over its
2025-07-17T07:05:39.0777700Z     ``cast_forward_inputs``. For non-root FSDP instances, their
2025-07-17T07:05:39.0777830Z     ``cast_root_forward_inputs`` values are ignored. The default setting is
2025-07-17T07:05:39.0777960Z     sufficient for the typical case where each FSDP instance has the same
2025-07-17T07:05:39.0778100Z     ``MixedPrecision`` configuration and only needs to cast inputs to the
2025-07-17T07:05:39.0778210Z     ``param_dtype`` at the beginning of the model's forward pass.
2025-07-17T07:05:39.0778210Z 
2025-07-17T07:05:39.0778340Z .. note:: For nested FSDP instances with different ``MixedPrecision``
2025-07-17T07:05:39.0778480Z     configurations, we recommend setting individual ``cast_forward_inputs``
2025-07-17T07:05:39.0778610Z     values to configure casting inputs or not before each instance's
2025-07-17T07:05:39.0778720Z     forward. In such a case, since the casts happen before each FSDP
2025-07-17T07:05:39.0778850Z     instance's forward, a parent FSDP instance should have its non-FSDP
2025-07-17T07:05:39.0778990Z     submodules run before its FSDP submodules to avoid the activation dtype
2025-07-17T07:05:39.0779120Z     being changed due to a different ``MixedPrecision`` configuration.
2025-07-17T07:05:39.0779120Z 
2025-07-17T07:05:39.0779170Z     Example::
2025-07-17T07:05:39.0779190Z 
2025-07-17T07:05:39.0779270Z         >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:39.0779380Z         >>> model = nn.Sequential(nn.Linear(3, 3), nn.Linear(3, 3))
2025-07-17T07:05:39.0779450Z         >>> model[1] = FSDP(
2025-07-17T07:05:39.0779500Z         >>>     model[1],
2025-07-17T07:05:39.0779690Z         >>>     mixed_precision=MixedPrecision(param_dtype=torch.float16, cast_forward_inputs=True),
2025-07-17T07:05:39.0779730Z         >>> )
2025-07-17T07:05:39.0779790Z         >>> model = FSDP(
2025-07-17T07:05:39.0779840Z         >>>     model,
2025-07-17T07:05:39.0780020Z         >>>     mixed_precision=MixedPrecision(param_dtype=torch.bfloat16, cast_forward_inputs=True),
2025-07-17T07:05:39.0780070Z         >>> )
2025-07-17T07:05:39.0780070Z 
2025-07-17T07:05:39.0780200Z     The above shows a working example. On the other hand, if ``model[1]``
2025-07-17T07:05:39.0780340Z     were replaced with ``model[0]``, meaning that the submodule using
2025-07-17T07:05:39.0780500Z     different ``MixedPrecision`` ran its forward first, then ``model[1]``
2025-07-17T07:05:39.0780640Z     would incorrectly see ``float16`` activations instead of ``bfloat16``
2025-07-17T07:05:39.0780690Z     ones.
2025-07-17T07:05:39.0780690Z 
2025-07-17T07:05:39.0780690Z 
2025-07-17T07:05:39.0780840Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.1258200Z 
2025-07-17T07:05:39.1258870Z msg = Cannot scrape callname=FullStateDictConfig in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/fsdp/api.py line=295.
2025-07-17T07:05:39.1259050Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.1259050Z 
2025-07-17T07:05:39.1259180Z ``FullStateDictConfig`` is a config class meant to be used with
2025-07-17T07:05:39.1259300Z ``StateDictType.FULL_STATE_DICT``. We recommend enabling both
2025-07-17T07:05:39.1259440Z ``offload_to_cpu=True`` and ``rank0_only=True`` when saving full state
2025-07-17T07:05:39.1259580Z dicts to save GPU memory and CPU memory, respectively. This config class
2025-07-17T07:05:39.1259710Z is meant to be used via the :func:`state_dict_type` context manager as
2025-07-17T07:05:39.1259750Z follows:
2025-07-17T07:05:39.1259760Z 
2025-07-17T07:05:39.1259840Z     >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:39.1259980Z     >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-07-17T07:05:39.1260070Z     >>> fsdp = FSDP(model, auto_wrap_policy=...)
2025-07-17T07:05:39.1260190Z     >>> cfg = FullStateDictConfig(offload_to_cpu=True, rank0_only=True)
2025-07-17T07:05:39.1260330Z     >>> with FSDP.state_dict_type(fsdp, StateDictType.FULL_STATE_DICT, cfg):
2025-07-17T07:05:39.1260400Z     >>>     state = fsdp.state_dict()
2025-07-17T07:05:39.1260530Z     >>> # `state` will be empty on non rank 0 and contain CPU tensors on rank 0.
2025-07-17T07:05:39.1260680Z     >>> # To reload checkpoint for inference, finetuning, transfer learning, etc:
2025-07-17T07:05:39.1260830Z     >>> model = model_fn()  # Initialize model in preparation for wrapping with FSDP
2025-07-17T07:05:39.1260890Z     >>> if dist.get_rank() == 0:
2025-07-17T07:05:39.1261040Z     >>> # Load checkpoint only on rank 0 to avoid memory redundancy
2025-07-17T07:05:39.1261130Z     >>>     state_dict = torch.load("my_checkpoint.pt")
2025-07-17T07:05:39.1261200Z     >>>     model.load_state_dict(state_dict)
2025-07-17T07:05:39.1261340Z     >>> # All ranks initialize FSDP module as usual. `sync_module_states` argument
2025-07-17T07:05:39.1261490Z     >>> # communicates loaded checkpoint states from rank 0 to rest of the world.
2025-07-17T07:05:39.1261540Z     >>> fsdp = FSDP(
2025-07-17T07:05:39.1261590Z     ...     model,
2025-07-17T07:05:39.1261670Z     ...     device_id=torch.cuda.current_device(),
2025-07-17T07:05:39.1261730Z     ...     auto_wrap_policy=...,
2025-07-17T07:05:39.1261790Z     ...     sync_module_states=True,
2025-07-17T07:05:39.1261840Z     ... )
2025-07-17T07:05:39.1262110Z     >>> # After this point, all ranks have FSDP model with loaded checkpoint.
2025-07-17T07:05:39.1262120Z 
2025-07-17T07:05:39.1262170Z Attributes:
2025-07-17T07:05:39.1262290Z     rank0_only (bool): If ``True``, then only rank 0 saves the full state
2025-07-17T07:05:39.1262460Z         dict, and nonzero ranks save an empty dict. If ``False``, then all
2025-07-17T07:05:39.1262560Z         ranks save the full state dict. (Default: ``False``)
2025-07-17T07:05:39.1262570Z 
2025-07-17T07:05:39.1262730Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.1262730Z 
2025-07-17T07:05:39.1263210Z msg = Cannot scrape callname=init_from_local_shards in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py line=361.
2025-07-17T07:05:39.1263400Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.1263430Z 
2025-07-17T07:05:39.1263580Z Creates an :class:`ShardedTensor` from local shards and the global metadata.
2025-07-17T07:05:39.1263670Z Needs to be called on all ranks in an SPMD fashion.
2025-07-17T07:05:39.1263670Z 
2025-07-17T07:05:39.1263710Z Args:
2025-07-17T07:05:39.1263880Z     local_shards (List[:class `torch.distributed._shard.sharded_tensor.Shard`]): A list
2025-07-17T07:05:39.1263980Z         of shards that represent the local shards on this rank.
2025-07-17T07:05:39.1264130Z     global_size (int...):  a list, tuple, or `torch.Size` of integers defining the
2025-07-17T07:05:39.1264200Z         shape of the overall sharded tensor.
2025-07-17T07:05:39.1264200Z 
2025-07-17T07:05:39.1264250Z Keyword args:
2025-07-17T07:05:39.1264400Z     process_group (ProcessGroup, optional): The process group to work on. If None,
2025-07-17T07:05:39.1264480Z         the default process group will be used.
2025-07-17T07:05:39.1264590Z     init_rrefs (bool, optional): Whether or not to initialize
2025-07-17T07:05:39.1264710Z         :class:`torch.distributed.rpc.RRef`s pointing to remote shards.
2025-07-17T07:05:39.1264840Z         Need to initialize the RPC Framework if specified as ``True``.
2025-07-17T07:05:39.1264890Z         Default: ``False``.
2025-07-17T07:05:39.1264890Z 
2025-07-17T07:05:39.1264940Z Returns:
2025-07-17T07:05:39.1265030Z     A :class:`ShardedTensor` object handle on this rank
2025-07-17T07:05:39.1265030Z 
2025-07-17T07:05:39.1265030Z 
2025-07-17T07:05:39.1265080Z Examples:
2025-07-17T07:05:39.1265260Z     Suppose we want construct a sharded tensor on two ranks, global size = (10, 5),
2025-07-17T07:05:39.1265370Z     each shard have a (5, 5) local tensor, we can do it like below:
2025-07-17T07:05:39.1265370Z 
2025-07-17T07:05:39.1265420Z     on rank 0:
2025-07-17T07:05:39.1265490Z     >>> # xdoctest: +SKIP("not distributed")
2025-07-17T07:05:39.1265560Z     >>> local_shard_metadata = ShardMetadata(
2025-07-17T07:05:39.1265620Z     >>>     shard_offsets=[0, 0],
2025-07-17T07:05:39.1265670Z     >>>     shard_lengths=[5, 5],
2025-07-17T07:05:39.1265740Z     >>>     placement="rank:0/cuda:0"
2025-07-17T07:05:39.1265780Z     >>> )
2025-07-17T07:05:39.1265900Z     >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)]
2025-07-17T07:05:39.1266020Z     >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5])
2025-07-17T07:05:39.1266020Z 
2025-07-17T07:05:39.1266070Z     on rank 1:
2025-07-17T07:05:39.1266140Z     >>> # xdoctest: +SKIP("not distributed")
2025-07-17T07:05:39.1266210Z     >>> local_shard_metadata = ShardMetadata(
2025-07-17T07:05:39.1266260Z     >>>     shard_offsets=[5, 0],
2025-07-17T07:05:39.1266320Z     >>>     shard_lengths=[5, 5],
2025-07-17T07:05:39.1266380Z     >>>     placement="rank:1/cuda:1"
2025-07-17T07:05:39.1266420Z     >>> )
2025-07-17T07:05:39.1266540Z     >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)]
2025-07-17T07:05:39.1266660Z     >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5])
2025-07-17T07:05:39.1266670Z 
2025-07-17T07:05:39.1266840Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.1266850Z 
2025-07-17T07:05:39.1267330Z msg = Cannot scrape callname=ShardedTensor._init_from_local_tensor in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=835.
2025-07-17T07:05:39.1267560Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.1267560Z 
2025-07-17T07:05:39.1267710Z Initialize a ShardedTensor given only one local tensor, global sharded tensor
2025-07-17T07:05:39.1267780Z size and sharding spec on each rank.
2025-07-17T07:05:39.1267780Z 
2025-07-17T07:05:39.1267820Z Args:
2025-07-17T07:05:39.1267960Z     local_tensor (Tensor): Single tensor of local shard stored in each rank.
2025-07-17T07:05:39.1268130Z     sharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`):
2025-07-17T07:05:39.1268260Z         The specification describing how to shard the Tensor.
2025-07-17T07:05:39.1268370Z     global_size (Sequence[int]): Size of the sharded tensor.
2025-07-17T07:05:39.1268520Z     process_group (ProcessGroup, optional): The process group to aggregate on.
2025-07-17T07:05:39.1268560Z         Default: None
2025-07-17T07:05:39.1268670Z     init_rrefs (bool, optional): Whether or not to initialize
2025-07-17T07:05:39.1268790Z         :class:`torch.distributed.rpc.RRef`s pointing to remote shards.
2025-07-17T07:05:39.1268910Z         Need to initialize the RPC Framework if specified as ``True``.
2025-07-17T07:05:39.1268970Z         Default: ``False``.
2025-07-17T07:05:39.1268970Z 
2025-07-17T07:05:39.1269010Z Returns:
2025-07-17T07:05:39.1269150Z     A :class:`ShardedTensor` sharded based on the given sharding_spec with local
2025-07-17T07:05:39.1269220Z         tensor stored in the current rank.
2025-07-17T07:05:39.1269220Z 
2025-07-17T07:05:39.1269260Z Examples:
2025-07-17T07:05:39.1269320Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:39.1269400Z     >>> # All tensors below are of torch.int64 type.
2025-07-17T07:05:39.1269470Z     >>> # We have 2 process groups, 2 ranks.
2025-07-17T07:05:39.1269580Z     >>> tensor = torch.arange(2, dtype=torch.int64) + 1 + 2 * rank
2025-07-17T07:05:39.1269700Z     >>> local_tensor = torch.unsqueeze(torch.cat([tensor, tensor + 2]))
2025-07-17T07:05:39.1269750Z     >>> local_tensor
2025-07-17T07:05:39.1269800Z     tensor([[1, 2, 3, 4]]) # Rank 0
2025-07-17T07:05:39.1269850Z     tensor([[3, 4, 5, 6]]) # Rank 1
2025-07-17T07:05:39.1269900Z     >>> sharding_dim = 0
2025-07-17T07:05:39.1269970Z     >>> sharding_spec = ChunkShardingSpec(
2025-07-17T07:05:39.1270030Z             dim=sharding_dim,
2025-07-17T07:05:39.1270080Z             placements=[
2025-07-17T07:05:39.1270130Z                 "rank:0/cuda:0",
2025-07-17T07:05:39.1270180Z                 "rank:1/cuda:1",
2025-07-17T07:05:39.1270220Z             ],
2025-07-17T07:05:39.1270270Z         )
2025-07-17T07:05:39.1270350Z     >>> st = ShardedTensor._init_from_local_tensor(
2025-07-17T07:05:39.1270420Z     ...     local_tensor, sharding_spec, [2, 4]
2025-07-17T07:05:39.1270460Z     ... )
2025-07-17T07:05:39.1270500Z     >>> st
2025-07-17T07:05:39.1270550Z     ShardedTensor(
2025-07-17T07:05:39.1270610Z         ShardedTensorMetadata(
2025-07-17T07:05:39.1270670Z             shards_metadata=[
2025-07-17T07:05:39.1270830Z                 ShardMetadata(shard_offsets=[0, 0], shard_sizes=[1, 4], placement=rank:0/cuda:0),
2025-07-17T07:05:39.1270990Z                 ShardMetadata(shard_offsets=[1, 0], shard_sizes=[1, 4], placement=rank:1/cuda:1),
2025-07-17T07:05:39.1271030Z             ],
2025-07-17T07:05:39.1271090Z             size=torch.Size([2, 4])
2025-07-17T07:05:39.1271130Z     )
2025-07-17T07:05:39.1271180Z     >>> st.local_tensor()
2025-07-17T07:05:39.1271230Z     tensor([1, 2, 3, 4]) # Rank 0
2025-07-17T07:05:39.1271280Z     tensor([3, 4, 5, 6]) # Rank 1
2025-07-17T07:05:39.1271290Z 
2025-07-17T07:05:39.1271470Z Warning: This API is experimental and subject to change. It lacks of a fully across
2025-07-17T07:05:39.1271620Z          rank validations, and we only validate the local shard on the current rank.
2025-07-17T07:05:39.1271750Z          We fully rely on the user to ensure local tensor is sharded based on the
2025-07-17T07:05:39.1271830Z          sharding spec.
2025-07-17T07:05:39.1271830Z 
2025-07-17T07:05:39.1271990Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.1271990Z 
2025-07-17T07:05:39.1272440Z msg = Cannot scrape callname=ShardedTensor.reshard in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=1076.
2025-07-17T07:05:39.1272610Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.1272610Z 
2025-07-17T07:05:39.1272790Z Reshard a sharded tensor given the ``resharding_spec``. For now, we only support
2025-07-17T07:05:39.1272870Z single local shard.
2025-07-17T07:05:39.1272880Z 
2025-07-17T07:05:39.1273010Z If ``resharding_spec`` is same as the original one, this becomes a no-op.
2025-07-17T07:05:39.1273160Z If only ``resharding_spec`` shares the same sharding dim with the original one,
2025-07-17T07:05:39.1273220Z we swap local shards directly.
2025-07-17T07:05:39.1273370Z For more generic cases, we merge different shards across different ranks and split
2025-07-17T07:05:39.1273520Z the local shards based on the ``resharding_spec`` via `all_to_all` collective API.
2025-07-17T07:05:39.1273520Z 
2025-07-17T07:05:39.1273570Z Args:
2025-07-17T07:05:39.1273740Z     resharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): The
2025-07-17T07:05:39.1273850Z         specification describing how the tensor is sharded.
2025-07-17T07:05:39.1273850Z 
2025-07-17T07:05:39.1273890Z Returns:
2025-07-17T07:05:39.1274020Z     A :class:`ShardedTensor` object whose local shards are resharded.
2025-07-17T07:05:39.1274020Z 
2025-07-17T07:05:39.1274060Z Examples:
2025-07-17T07:05:39.1274120Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:39.1274190Z     >>> # We have 2 process groups, 2 ranks.
2025-07-17T07:05:39.1274300Z     >>> tensor = torch.arange(4, dtype=torch.int64) + 1 + 2 * rank
2025-07-17T07:05:39.1274370Z     >>> tensor = torch.stack([tensor, tensor])
2025-07-17T07:05:39.1274410Z     >>> tensor
2025-07-17T07:05:39.1274480Z     tensor([[1, 2, 3, 4], [1, 2, 3, 4]]) # Rank 0
2025-07-17T07:05:39.1274550Z     tensor([[3, 4, 5, 6], [3, 4, 5, 6]]) # Rank 1
2025-07-17T07:05:39.1274610Z     tensor([[5, 6, 7, 8], [5, 6, 7, 8]]) # Rank 2
2025-07-17T07:05:39.1274680Z     tensor([[7, 8, 9, 10], [7, 8, 9, 10]]) # Rank 3
2025-07-17T07:05:39.1274740Z     >>> sharding_dim = 0
2025-07-17T07:05:39.1274810Z     >>> spec = ChunkShardingSpec(
2025-07-17T07:05:39.1274860Z             dim=sharding_dim,
2025-07-17T07:05:39.1274910Z             placements=[
2025-07-17T07:05:39.1274970Z                 "rank:0/cuda:0",
2025-07-17T07:05:39.1275020Z                 "rank:1/cuda:1",
2025-07-17T07:05:39.1275080Z                 "rank:2/cuda:2",
2025-07-17T07:05:39.1275120Z                 "rank:3/cuda:3",
2025-07-17T07:05:39.1275170Z             ],
2025-07-17T07:05:39.1275210Z         )
2025-07-17T07:05:39.1275270Z     >>> current_offsets = [0] * 2
2025-07-17T07:05:39.1275330Z     >>> current_offsets[0] = rank * 2
2025-07-17T07:05:39.1275390Z     >>> shard_metadata = ShardMetadata(
2025-07-17T07:05:39.1275480Z             shard_offsets=copy.deepcopy(current_offsets),
2025-07-17T07:05:39.1275540Z             shard_sizes=tensor.size(),
2025-07-17T07:05:39.1275610Z             placement=spec.placements[rank],
2025-07-17T07:05:39.1275650Z         )
2025-07-17T07:05:39.1275700Z     >>> local_shards = [
2025-07-17T07:05:39.1275740Z             Shard(
2025-07-17T07:05:39.1275800Z                 tensor=tensor,
2025-07-17T07:05:39.1275850Z                 metadata=shard_metadata,
2025-07-17T07:05:39.1275900Z             )
2025-07-17T07:05:39.1275940Z         ]
2025-07-17T07:05:39.1276100Z     >>> st = ShardedTensor._init_from_local_shards(local_shards, tensor.size())
2025-07-17T07:05:39.1276150Z     >>> sharding_dim = 1
2025-07-17T07:05:39.1276230Z     >>> resharding_spec = ChunkShardingSpec(
2025-07-17T07:05:39.1276310Z             dim=sharding_dim,
2025-07-17T07:05:39.1276360Z             placements=[
2025-07-17T07:05:39.1276410Z                 "rank:0/cuda:0",
2025-07-17T07:05:39.1276460Z                 "rank:1/cuda:1",
2025-07-17T07:05:39.1276520Z                 "rank:2/cuda:2",
2025-07-17T07:05:39.1276560Z                 "rank:3/cuda:3",
2025-07-17T07:05:39.1276610Z             ],
2025-07-17T07:05:39.1276650Z         )
2025-07-17T07:05:39.1276710Z     >>> st.reshard(resharding_spec)
2025-07-17T07:05:39.1276770Z     >>> tensor = st.local_shards()[0].tensor
2025-07-17T07:05:39.1276820Z     >>> tensor
2025-07-17T07:05:39.1276900Z     tensor([[1], [1], [3], [3], [5], [5], [7], [7]]) # Rank 0
2025-07-17T07:05:39.1277010Z     tensor([[2], [2], [4], [4], [6], [6], [8], [8]]) # Rank 1
2025-07-17T07:05:39.1277120Z     tensor([[3], [3], [5], [5], [7], [7], [9], [9]]) # Rank 2
2025-07-17T07:05:39.1277200Z     tensor([[4], [4], [6], [6], [8], [8], [10], [10]]) # Rank 3
2025-07-17T07:05:39.1277210Z 
2025-07-17T07:05:39.1277360Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.1328270Z 
2025-07-17T07:05:39.1328920Z msg = Cannot scrape callname=ShardingPlan in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/_shard/sharding_plan/api.py line=12.
2025-07-17T07:05:39.1329140Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.1329140Z 
2025-07-17T07:05:39.1329280Z Representation of a sharding plan, describes how to shard a module
2025-07-17T07:05:39.1329460Z across hosts. `plan` is used to shard module parameters according to the spec provided,
2025-07-17T07:05:39.1329640Z `output_plan` and `return_local_tensor` are optional, they are used to specify the output
2025-07-17T07:05:39.1329800Z layout of a module with a spec, and when to convert back to data parallel fashion.
2025-07-17T07:05:39.1329810Z 
2025-07-17T07:05:39.1329850Z Args:
2025-07-17T07:05:39.1330020Z     plan (Dict[str, Union[:class:`torch.distributed._shard.sharding_spec.ShardingSpec`,
2025-07-17T07:05:39.1330140Z           :class:`torch.distributed._shard.sharder.Sharder`]):
2025-07-17T07:05:39.1330310Z         a dict describes how to shard a module, there're currently two ways to shard a module:
2025-07-17T07:05:39.1330470Z             1. directly shard a module parameter by a `ShardingSpec`, keyed by the name of
2025-07-17T07:05:39.1330550Z                a parameter to a `ShardingSpec`.
2025-07-17T07:05:39.1330710Z             2. shard a submodule by applying a `Sharder` on it, keyed by the name of a module
2025-07-17T07:05:39.1330770Z                to a `Sharder` object.
2025-07-17T07:05:39.1330980Z     output_plan (Dict[str, :class:`torch.distributed._shard.sharding_spec.ShardingSpec`), optional):
2025-07-17T07:05:39.1331150Z         a dict specifies the layout of a module's output which produces a ShardedTensor,
2025-07-17T07:05:39.1331300Z         keyed by the name of module to ShardingSpec("" in key means the root module).
2025-07-17T07:05:39.1331350Z         Default: `None`
2025-07-17T07:05:39.1331520Z     return_local_tensor (List[str], optional): a list of string, each element enables
2025-07-17T07:05:39.1331670Z         a module's sharded output to be returned as a Tensor from its local shards to
2025-07-17T07:05:39.1331830Z         ensure further processing in a data parallel fashion. ("" in list means the
2025-07-17T07:05:39.1331870Z         root module).
2025-07-17T07:05:39.1331930Z         Default: None
2025-07-17T07:05:39.1331970Z Example:
2025-07-17T07:05:39.1332150Z   Suppose we want to shard a module with two linear layers and then run it with DDP, we also
2025-07-17T07:05:39.1332320Z   want to convert the output of the second linear layer back to DDP, we can do it as follows:
2025-07-17T07:05:39.1332470Z 
2025-07-17T07:05:39.1332580Z     >>> # xdoctest: +REQUIRES(module:torch._C._distributed_c10d)
2025-07-17T07:05:39.1332640Z     >>> class MyModule(nn.Module):
2025-07-17T07:05:39.1332710Z     >>>     def __init__(self) -> None:
2025-07-17T07:05:39.1332790Z     >>>        super().__init__()
2025-07-17T07:05:39.1332850Z     >>>        self.fc1 = nn.Linear()
2025-07-17T07:05:39.1332910Z     >>>        self.gelu = nn.GELU()
2025-07-17T07:05:39.1332970Z     >>>        self.fc2 = nn.Linear()
2025-07-17T07:05:39.1333030Z     >>>        self.relu = nn.Linear()
2025-07-17T07:05:39.1333070Z     >>>
2025-07-17T07:05:39.1333130Z     >>>     def forward(self, input):
2025-07-17T07:05:39.1333240Z     >>>         return self.relu(self.fc2(self.gelu(self.fc1(input))))
2025-07-17T07:05:39.1333240Z 
2025-07-17T07:05:39.1333240Z 
2025-07-17T07:05:39.1333320Z     >>> # xdoctest: +SKIP("Undefined spec1, spec2)
2025-07-17T07:05:39.1333420Z     >>> sharding_plan = ShardingPlan(
2025-07-17T07:05:39.1333490Z     >>>    plan={
2025-07-17T07:05:39.1333550Z     >>>        "fc1.weight": spec1,
2025-07-17T07:05:39.1333610Z     >>>        "fc2.weight": spec2
2025-07-17T07:05:39.1333650Z     >>>    },
2025-07-17T07:05:39.1333710Z     >>>    output_plan={
2025-07-17T07:05:39.1333760Z     >>>        "fc2": output_spec
2025-07-17T07:05:39.1333810Z     >>>    },
2025-07-17T07:05:39.1333870Z     >>>    return_local_tensor=["fc2"]
2025-07-17T07:05:39.1333920Z     >>> )
2025-07-17T07:05:39.1333920Z 
2025-07-17T07:05:39.1334070Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.1334080Z 
2025-07-17T07:05:39.1334570Z msg = Cannot scrape callname=register_sharding in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/tensor/experimental/_register_sharding.py line=25.
2025-07-17T07:05:39.1334730Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.1334730Z 
2025-07-17T07:05:39.1334900Z :meth:`register_sharding` is an experimental API that allows users to register sharding
2025-07-17T07:05:39.1335040Z strategies for an operator when the tensor inputs and outputs are DTensor.
2025-07-17T07:05:39.1335190Z It can be useful when: (1) there doesn't exist a default sharding strategy for ``op``,
2025-07-17T07:05:39.1335340Z e.g. when ``op`` is a custom operator that is not supported by :class:`DTensor`; (2)
2025-07-17T07:05:39.1335510Z when users would like to overwrite default sharding strategies of existing operators.
2025-07-17T07:05:39.1335510Z 
2025-07-17T07:05:39.1335550Z Args:
2025-07-17T07:05:39.1335630Z     op (Union[OpOverload, List[OpOverload]]):
2025-07-17T07:05:39.1335750Z         An op or a list of ops to register the customized sharding function.
2025-07-17T07:05:39.1335750Z 
2025-07-17T07:05:39.1335790Z Returns:
2025-07-17T07:05:39.1335950Z     A function decorator which can be used to wrap a function that defines the sharding
2025-07-17T07:05:39.1336120Z     strategy for the operator specified in ``op``. The defined sharding strategy will be
2025-07-17T07:05:39.1336290Z     registered to DTensor and will override the default sharding strategy if DTensor has
2025-07-17T07:05:39.1336460Z     already implemented the operator. The customized sharding function takes the same inputs
2025-07-17T07:05:39.1336620Z     as the original op (except that if an arg is a :class:`torch.Tensor`, it will be
2025-07-17T07:05:39.1336770Z     replaced by a tensor-like object that DTensor uses internally). The function should
2025-07-17T07:05:39.1336940Z     return a sequence of 2-tuples, each specifying acceptable output placements and its
2025-07-17T07:05:39.1337010Z     corresponding intput placements.
2025-07-17T07:05:39.1337010Z 
2025-07-17T07:05:39.1337060Z Example:
2025-07-17T07:05:39.1337120Z     >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:39.1337200Z     >>> @register_sharding(aten._softmax.default)
2025-07-17T07:05:39.1337290Z     >>> def custom_softmax_sharding(x, dim, half_to_float):
2025-07-17T07:05:39.1337430Z     >>>     softmax_dim = dim if dim >= 0 else dim + x.ndim
2025-07-17T07:05:39.1337490Z     >>>     acceptable_shardings = []
2025-07-17T07:05:39.1337530Z     >>>
2025-07-17T07:05:39.1337710Z     >>>     all_replicate = ([Replicate()], [Replicate(), None, None])
2025-07-17T07:05:39.1337800Z     >>>     acceptable_shardings.append(all_replicate)
2025-07-17T07:05:39.1337850Z     >>>
2025-07-17T07:05:39.1337920Z     >>>     for sharding_dim in range(x.ndim):
2025-07-17T07:05:39.1337990Z     >>>         if sharding_dim != softmax_dim:
2025-07-17T07:05:39.1338040Z     >>>             all_sharded = (
2025-07-17T07:05:39.1338110Z     >>>                 [Shard(sharding_dim)],
2025-07-17T07:05:39.1338190Z     >>>                 [Shard(sharding_dim), None, None],
2025-07-17T07:05:39.1338240Z     >>>             )
2025-07-17T07:05:39.1338320Z     >>>             acceptable_shardings.append(all_sharded)
2025-07-17T07:05:39.1338400Z     >>>
2025-07-17T07:05:39.1338480Z     >>>     return acceptable_shardings
2025-07-17T07:05:39.1338480Z 
2025-07-17T07:05:39.1338620Z .. note:: This API is currently experimental and subject to change
2025-07-17T07:05:39.1338620Z 
2025-07-17T07:05:39.1338770Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.1338780Z 
2025-07-17T07:05:39.1339210Z msg = Cannot scrape callname=local_map in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/tensor/experimental/_func_map.py line=35.
2025-07-17T07:05:39.1339370Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.1339370Z 
2025-07-17T07:05:39.1339530Z :meth:`local_map` is an experimental API that allows users to pass :class:`DTensor` s
2025-07-17T07:05:39.1339700Z to a function that is written to be applied on ``torch.Tensor`` s. It is done by extracting
2025-07-17T07:05:39.1339860Z the local components of :class:`DTensor`, call the function, and wrap the outputs to
2025-07-17T07:05:39.1339960Z :class:`DTensor` according to the ``out_placements``.
2025-07-17T07:05:39.1339960Z 
2025-07-17T07:05:39.1340000Z Args:
2025-07-17T07:05:39.1340130Z     func (Callable): the function to be applied on each local shard of
2025-07-17T07:05:39.1340180Z         :class:`DTensor` s.
2025-07-17T07:05:39.1340320Z     out_placements (Union[`PlacementType`, Tuple[`PlacementType`, ...]]):
2025-07-17T07:05:39.1340470Z         the desired placements of the :class:`DTensor` s in ``func``'s flattened output.
2025-07-17T07:05:39.1340620Z         If the flattened ``output`` is a single value, the ``out_placements`` should be
2025-07-17T07:05:39.1340760Z         of type `PlacementType`. Otherwise if the flattened ``output`` has multiple
2025-07-17T07:05:39.1340910Z         values, the ``out_placements`` should be a tuple of `PlacementType` values 1:1
2025-07-17T07:05:39.1340980Z         mapping to the flattened ``output``.
2025-07-17T07:05:39.1341110Z         Besides, for :class:`Tensor` output, we use `PlacementType` as its
2025-07-17T07:05:39.1341270Z         placements (a `Tuple[Placement]` value). For non-Tensor output, the `PlacementType`
2025-07-17T07:05:39.1341330Z         should be `None`.
2025-07-17T07:05:39.1341470Z         Note that the only exception is when no :class:`DTensor` argument is passed
2025-07-17T07:05:39.1341610Z         in. In this case, even if `out_placements` is not `None`, the result function
2025-07-17T07:05:39.1341760Z         should ignore the desired placements because the function is not running with
2025-07-17T07:05:39.1341820Z         :class:`DTensor` s.
2025-07-17T07:05:39.1341910Z     in_placements (Tuple[`PlacementType`, ...], optional):
2025-07-17T07:05:39.1342080Z         the required placements of the :class:`DTensor` s in the flattened inputs of ``func``.
2025-07-17T07:05:39.1342220Z         If ``in_placements`` is specified, :meth:`local_map` would examine whether the
2025-07-17T07:05:39.1342360Z         placements of each :class:`DTensor` argument is the same as the required
2025-07-17T07:05:39.1342500Z         placements or not. If the placements are not the same and
2025-07-17T07:05:39.1342650Z         ``redistribute_inputs`` is ``False``, an exception will be raised. Otherwise if
2025-07-17T07:05:39.1342820Z         ``redistribute_inputs`` is ``True``, the argument will be first redistributed to
2025-07-17T07:05:39.1342970Z         the required sharding placements before passing its local tensor to ``func``.
2025-07-17T07:05:39.1343100Z         The only exception is when required placements are not ``None`` and the
2025-07-17T07:05:39.1343250Z         argument is a :class:`torch.Tensor`. In this case, the placements examination
2025-07-17T07:05:39.1343380Z         will be skipped and the argument will be directly passed to ``func``.
2025-07-17T07:05:39.1343510Z         If ``in_placements`` is ``None``, no placements examination will be performed.
2025-07-17T07:05:39.1343590Z         Default: None
2025-07-17T07:05:39.1343730Z     in_grad_placements (Tuple[`PlacementType`, ...], optional):
2025-07-17T07:05:39.1343860Z         the placements hint of the :class:`DTensor` s gradient corresponds
2025-07-17T07:05:39.1343980Z         to the flattened input DTensor. This argument is the hint that user
2025-07-17T07:05:39.1344100Z         can give to :meth:`to_local` in case the gradient layout of the
2025-07-17T07:05:39.1344230Z         local tensor input does not match its :class:`DTensor` input layout.
2025-07-17T07:05:39.1344350Z         If not specified, we will assume the gradient layout of the local
2025-07-17T07:05:39.1344480Z         tensor input remains the same as the original :class:`DTensor` input
2025-07-17T07:05:39.1344590Z         and use that for gradient computation. Default: None.
2025-07-17T07:05:39.1344670Z     device_mesh (:class:`DeviceMesh`, optional):
2025-07-17T07:05:39.1344800Z         the device mesh that the output :class:`DTensor` s are placed on. If not
2025-07-17T07:05:39.1344950Z         specified, this will be inferred from the first input :class:`DTensor`'s device
2025-07-17T07:05:39.1345010Z         mesh. Default: None.
2025-07-17T07:05:39.1345010Z 
2025-07-17T07:05:39.1345060Z Keyword Args:
2025-07-17T07:05:39.1351290Z     redistribute_inputs (bool, optional):
2025-07-17T07:05:39.1351470Z         the bool value indicating whether to reshard the input :class:`DTensor` s when
2025-07-17T07:05:39.1351620Z         their placements are different from the required input placements. If this
2025-07-17T07:05:39.1351760Z         value is ``False`` and some :class:`DTensor` input has a different placement,
2025-07-17T07:05:39.1351840Z         an exception will be raised. Default: False.
2025-07-17T07:05:39.1351850Z 
2025-07-17T07:05:39.1351900Z Returns:
2025-07-17T07:05:39.1352050Z     A ``Callable`` that applies ``func`` to each local shard of the input :class:`DTensor`
2025-07-17T07:05:39.1352190Z     and returns a :class:`DTensor` constructed from the return value of ``func``.
2025-07-17T07:05:39.1352200Z 
2025-07-17T07:05:39.1352240Z Raises:
2025-07-17T07:05:39.1352390Z     AssertionError: For any non-DTensor output, we require its corresponding
2025-07-17T07:05:39.1352540Z         output placement in ``out_placements`` be None. An AssertionError will be raised
2025-07-17T07:05:39.1352600Z         if this is not the case.
2025-07-17T07:05:39.1352610Z 
2025-07-17T07:05:39.1352760Z     ValueError: If ``redistribute_inputs=False`` but the input :class:`DTensor` needs
2025-07-17T07:05:39.1352850Z         a redistribution according to ``in_placements``.
2025-07-17T07:05:39.1352850Z 
2025-07-17T07:05:39.1352900Z Example:
2025-07-17T07:05:39.1352960Z     >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:39.1353040Z     >>> def mm_allreduce_forward(device_mesh, W, X):
2025-07-17T07:05:39.1353110Z     >>>     partial_sum_tensor = torch.mm(W, X)
2025-07-17T07:05:39.1353270Z     >>>     reduced_tensor = funcol.all_reduce(partial_sum_tensor, "sum", device_mesh)
2025-07-17T07:05:39.1353320Z     >>>     return reduced_tensor
2025-07-17T07:05:39.1353370Z     >>>
2025-07-17T07:05:39.1353510Z     >>> W = torch.randn(12, 8, requires_grad=False)
2025-07-17T07:05:39.1353590Z     >>> X = torch.randn(8, 16, requires_grad=False)
2025-07-17T07:05:39.1353640Z     >>> Y = torch.mm(W, X)
2025-07-17T07:05:39.1353800Z     >>> row_wise = [Shard(0)]  # row-wise sharding placements on 1-d mesh
2025-07-17T07:05:39.1353920Z     >>> col_wise = [Shard(1)]  # col-wise sharding placements on 1-d mesh
2025-07-17T07:05:39.1353960Z     >>>
2025-07-17T07:05:39.1354130Z     >>> # local_mm_allreduce_forward is the function wrapped with DTensor/Tensor convertion
2025-07-17T07:05:39.1354200Z     >>> local_mm_allreduce_forward = local_map(
2025-07-17T07:05:39.1354260Z     >>>     mm_allreduce_forward,
2025-07-17T07:05:39.1354320Z     >>>     out_placements=[Replicate()],
2025-07-17T07:05:39.1354390Z     >>>     in_placements=[col_wise, row_wise],
2025-07-17T07:05:39.1354450Z     >>>     device_mesh=device_mesh,
2025-07-17T07:05:39.1354520Z     >>> )
2025-07-17T07:05:39.1354580Z     >>>
2025-07-17T07:05:39.1354640Z     >>> W_dt = distribute_tensor(
2025-07-17T07:05:39.1354700Z     ...     W, device_mesh, (col_wise)
2025-07-17T07:05:39.1354770Z     ... )  # col-wisely sharded W tensor
2025-07-17T07:05:39.1354820Z     >>> X_dt = distribute_tensor(
2025-07-17T07:05:39.1354880Z     ...     X, device_mesh, (row_wise)
2025-07-17T07:05:39.1354940Z     ... )  # row-wisely sharded X tensor
2025-07-17T07:05:39.1355010Z     >>> Y_dt = local_mm_allreduce_forward(
2025-07-17T07:05:39.1355060Z     ...     device_mesh, W_dt, X_dt
2025-07-17T07:05:39.1355150Z     ... )  # apply local_mm_allreduce_forward to DTensors
2025-07-17T07:05:39.1355150Z 
2025-07-17T07:05:39.1355270Z .. note:: This API is currently experimental and subject to change
2025-07-17T07:05:39.1355280Z 
2025-07-17T07:05:39.1355430Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.1671710Z 
2025-07-17T07:05:39.1672390Z msg = Cannot scrape callname=PrepareModuleInput in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py line=428.
2025-07-17T07:05:39.1672580Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.1672580Z 
2025-07-17T07:05:39.1672820Z Configure the nn.Module's inputs to convert the input tensors of the nn.Module to DTensors at runtime according to
2025-07-17T07:05:39.1673020Z ``input_layouts``, and perform layout redistribution according to the ``desired_input_layouts``.
2025-07-17T07:05:39.1673020Z 
2025-07-17T07:05:39.1673070Z Keyword Args:
2025-07-17T07:05:39.1673200Z     input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-07-17T07:05:39.1673400Z         The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to
2025-07-17T07:05:39.1673620Z         DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified
2025-07-17T07:05:39.1673690Z         as a placeholder. default: None.
2025-07-17T07:05:39.1673830Z     desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-07-17T07:05:39.1674070Z         The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-07-17T07:05:39.1674310Z         have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None.
2025-07-17T07:05:39.1674390Z     input_kwarg_layouts (Dict[str, Placement]):
2025-07-17T07:05:39.1674620Z         The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors.
2025-07-17T07:05:39.1674670Z         default: None
2025-07-17T07:05:39.1674780Z     desired_input_kwarg_layouts: (Dict[str, Placement]):
2025-07-17T07:05:39.1675000Z         The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-07-17T07:05:39.1675090Z         have the desired DTensor layouts. default: None.
2025-07-17T07:05:39.1675280Z     use_local_output (bool, optional):
2025-07-17T07:05:39.1675500Z         Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False.
2025-07-17T07:05:39.1675580Z Returns:
2025-07-17T07:05:39.1675770Z     A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs.
2025-07-17T07:05:39.1675770Z 
2025-07-17T07:05:39.1675820Z Example::
2025-07-17T07:05:39.1675880Z     >>> # xdoctest: +SKIP(failing)
2025-07-17T07:05:39.1676070Z     >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInput
2025-07-17T07:05:39.1676190Z     >>> from torch.distributed.device_mesh import init_device_mesh
2025-07-17T07:05:39.1676230Z     >>> ...
2025-07-17T07:05:39.1676420Z     >>> block = TransformerBlock(...)  # block is a nn.Module that contains an "attn" Attention submodule
2025-07-17T07:05:39.1676520Z     >>> tp_mesh = init_device_mesh("cuda", (8,))
2025-07-17T07:05:39.1676600Z     >>>
2025-07-17T07:05:39.1676800Z     >>> # According to the style specified below, the first input of attn will be annotated to Sharded DTensor
2025-07-17T07:05:39.1676890Z     >>> # and then redistributed to Replicated DTensor.
2025-07-17T07:05:39.1676950Z     >>> parallelize_module(
2025-07-17T07:05:39.1677030Z     >>>     block, # this can be a submodule or module
2025-07-17T07:05:39.1677070Z     >>>     tp_mesh,
2025-07-17T07:05:39.1677130Z     >>>     parallelize_plan={
2025-07-17T07:05:39.1677200Z     >>>         "attn": PrepareModuleInput(
2025-07-17T07:05:39.1677280Z     >>>             input_layouts=(Shard(0), None, None, ...),
2025-07-17T07:05:39.1677390Z     >>>             desired_input_layouts=(Replicate(), None, None, ...)
2025-07-17T07:05:39.1677440Z     >>>         ),
2025-07-17T07:05:39.1677480Z     >>>     }
2025-07-17T07:05:39.1677530Z     >>> )
2025-07-17T07:05:39.1677530Z 
2025-07-17T07:05:39.1677680Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.1677680Z 
2025-07-17T07:05:39.1678130Z msg = Cannot scrape callname=PrepareModuleOutput in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py line=597.
2025-07-17T07:05:39.1678290Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.1678300Z 
2025-07-17T07:05:39.1678530Z Configure the nn.Module's outputs to convert the output tensors of the nn.Module to DTensors at runtime according to
2025-07-17T07:05:39.1678730Z ``output_layouts``, and perform layout redistribution according to the ``desired_output_layouts``.
2025-07-17T07:05:39.1678730Z 
2025-07-17T07:05:39.1678770Z Keyword Args:
2025-07-17T07:05:39.1678870Z     output_layouts (Union[Placement, Tuple[Placement]]):
2025-07-17T07:05:39.1679080Z         The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to
2025-07-17T07:05:39.1679310Z         DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors,
2025-07-17T07:05:39.1679390Z         ``None`` need to be specified as a placeholder.
2025-07-17T07:05:39.1679510Z     desired_output_layouts (Union[Placement, Tuple[Placement]]):
2025-07-17T07:05:39.1679740Z         The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module
2025-07-17T07:05:39.1679810Z         have the desired DTensor layouts.
2025-07-17T07:05:39.1679870Z     use_local_output (bool, optional):
2025-07-17T07:05:39.1680090Z         Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True.
2025-07-17T07:05:39.1680130Z Returns:
2025-07-17T07:05:39.1680310Z     A ParallelStyle object that prepares the sharding layouts of the nn.Module's outputs.
2025-07-17T07:05:39.1680310Z 
2025-07-17T07:05:39.1680350Z Example::
2025-07-17T07:05:39.1680420Z     >>> # xdoctest: +SKIP(failing)
2025-07-17T07:05:39.1680630Z     >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleOutput
2025-07-17T07:05:39.1680750Z     >>> from torch.distributed.device_mesh import init_device_mesh
2025-07-17T07:05:39.1680790Z     >>> ...
2025-07-17T07:05:39.1681030Z     >>> block = TransformerBlock(...)  # block is a nn.Module that contains an "attn" Attention submodule
2025-07-17T07:05:39.1681110Z     >>> tp_mesh = init_device_mesh("cuda", (8,))
2025-07-17T07:05:39.1681150Z     >>>
2025-07-17T07:05:39.1681390Z     >>> # According to the style specified below, the output of the TransformerBlock will be converted to Replicated DTensor
2025-07-17T07:05:39.1681470Z     >>> # and then redistributed to Sharded DTensor.
2025-07-17T07:05:39.1681530Z     >>> parallelize_module(
2025-07-17T07:05:39.1681610Z     >>>     block, # this can be a submodule or module
2025-07-17T07:05:39.1681650Z     >>>     tp_mesh,
2025-07-17T07:05:39.1681750Z     >>>     parallelize_plan = PrepareModuleOutput(
2025-07-17T07:05:39.1681840Z     >>>         output_layouts=Replicate(),
2025-07-17T07:05:39.1681910Z     >>>         desired_output_layouts=Shard(0)
2025-07-17T07:05:39.1681950Z     >>>     )
2025-07-17T07:05:39.1681990Z     >>> )
2025-07-17T07:05:39.1681990Z 
2025-07-17T07:05:39.1682140Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.1682150Z 
2025-07-17T07:05:39.1682610Z msg = Cannot scrape callname=PrepareModuleInputOutput in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py line=705.
2025-07-17T07:05:39.1682770Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.1682770Z 
2025-07-17T07:05:39.1683020Z Configure the nn.Module's inputs (and outputs) to convert the input tensors (and output tensors, respectively) of the nn.Module
2025-07-17T07:05:39.1683270Z to DTensors at runtime according to ``input_layouts`` (and output_layouts, respectively), and perform layout redistribution
2025-07-17T07:05:39.1683500Z according to the ``desired_input_layouts`` (and ``desired_output_layouts``, respectively). This is a combination of
2025-07-17T07:05:39.1683630Z :class:`PrepareModuleInput` and :class:`PrepareModuleOutput`.
2025-07-17T07:05:39.1683630Z 
2025-07-17T07:05:39.1683680Z Keyword Args:
2025-07-17T07:05:39.1683800Z     input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-07-17T07:05:39.1684000Z         The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to
2025-07-17T07:05:39.1684210Z         DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified
2025-07-17T07:05:39.1684280Z         as a placeholder. default: None.
2025-07-17T07:05:39.1684410Z     desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-07-17T07:05:39.1684640Z         The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-07-17T07:05:39.1684870Z         have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None.
2025-07-17T07:05:39.1684950Z     input_kwarg_layouts (Dict[str, Placement]):
2025-07-17T07:05:39.1685170Z         The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors.
2025-07-17T07:05:39.1685220Z         default: None
2025-07-17T07:05:39.1685310Z     desired_input_kwarg_layouts: (Dict[str, Placement]):
2025-07-17T07:05:39.1685530Z         The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-07-17T07:05:39.1685620Z         have the desired DTensor layouts. default: None.
2025-07-17T07:05:39.1685690Z     use_local_input (bool, optional):
2025-07-17T07:05:39.1685900Z         Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False.
2025-07-17T07:05:39.1686020Z     output_layouts (Union[Placement, Tuple[Placement]]):
2025-07-17T07:05:39.1686220Z         The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to
2025-07-17T07:05:39.1686450Z         DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors,
2025-07-17T07:05:39.1686560Z         ``None`` need to be specified as a placeholder.
2025-07-17T07:05:39.1686680Z     desired_output_layouts (Union[Placement, Tuple[Placement]]):
2025-07-17T07:05:39.1686910Z         The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module
2025-07-17T07:05:39.1686980Z         have the desired DTensor layouts.
2025-07-17T07:05:39.1687040Z     use_local_output (bool, optional):
2025-07-17T07:05:39.1687250Z         Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True.
2025-07-17T07:05:39.1687330Z Returns:
2025-07-17T07:05:39.1687580Z     A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs and outputs.
2025-07-17T07:05:39.1687590Z 
2025-07-17T07:05:39.1687630Z Example::
2025-07-17T07:05:39.1687690Z     >>> # xdoctest: +SKIP(failing)
2025-07-17T07:05:39.1687900Z     >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInputOutput
2025-07-17T07:05:39.1688020Z     >>> from torch.distributed.device_mesh import init_device_mesh
2025-07-17T07:05:39.1688060Z     >>> ...
2025-07-17T07:05:39.1688240Z     >>> block = TransformerBlock(...)  # block is a nn.Module that contains an "attn" Attention submodule
2025-07-17T07:05:39.1688310Z     >>> tp_mesh = init_device_mesh("cuda", (8,))
2025-07-17T07:05:39.1688360Z     >>>
2025-07-17T07:05:39.1688560Z     >>> # According to the style specified below, the first input of attn will be annotated as Sharded DTensor
2025-07-17T07:05:39.1688770Z     >>> # and then redistributed to Replicated DTensor, and the output of the TransformerBlock will be annotated
2025-07-17T07:05:39.1688900Z     >>> # as Replicated DTensor and then redistributed to Sharded DTensor.
2025-07-17T07:05:39.1688950Z     >>> parallelize_module(
2025-07-17T07:05:39.1689040Z     >>>     block, # this can be a submodule or module
2025-07-17T07:05:39.1689080Z     >>>     tp_mesh,
2025-07-17T07:05:39.1689140Z     >>>     parallelize_plan={
2025-07-17T07:05:39.1689220Z     >>>         "attn": PrepareModuleInputOutput(
2025-07-17T07:05:39.1689340Z     >>>             input_layouts=(Shard(0), None, None, ...),
2025-07-17T07:05:39.1689440Z     >>>             desired_input_layouts=(Replicate(), None, None, ...),
2025-07-17T07:05:39.1689540Z     >>>             output_layouts=Replicate(),
2025-07-17T07:05:39.1689610Z     >>>             desired_output_layouts=Shard(0),
2025-07-17T07:05:39.1689690Z     >>>         ),
2025-07-17T07:05:39.1689730Z     >>>     }
2025-07-17T07:05:39.1689770Z     >>> )
2025-07-17T07:05:39.1689820Z 
2025-07-17T07:05:39.1689970Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.3509550Z 
2025-07-17T07:05:39.3510150Z msg = Cannot scrape callname=async_execution in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/rpc/functions.py line=6.
2025-07-17T07:05:39.3510870Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.3511110Z 
2025-07-17T07:05:39.3511260Z A decorator for a function indicating that the return value of the function
2025-07-17T07:05:39.3511610Z is guaranteed to be a :class:`~torch.futures.Future` object and this
2025-07-17T07:05:39.3511960Z function can run asynchronously on the RPC callee. More specifically, the
2025-07-17T07:05:39.3512320Z callee extracts the :class:`~torch.futures.Future` returned by the wrapped
2025-07-17T07:05:39.3512680Z function and installs subsequent processing steps as a callback to that
2025-07-17T07:05:39.3513050Z :class:`~torch.futures.Future`. The installed callback will read the value
2025-07-17T07:05:39.3513510Z from the :class:`~torch.futures.Future` when completed and send the
2025-07-17T07:05:39.3513830Z value back as the RPC response. That also means the returned
2025-07-17T07:05:39.3514260Z :class:`~torch.futures.Future` only exists on the callee side and is never
2025-07-17T07:05:39.3514610Z sent through RPC. This decorator is useful when the wrapped function's
2025-07-17T07:05:39.3514940Z (``fn``) execution needs to pause and resume due to, e.g., containing
2025-07-17T07:05:39.3515260Z :meth:`~torch.distributed.rpc.rpc_async` or waiting for other signals.
2025-07-17T07:05:39.3515460Z 
2025-07-17T07:05:39.3515600Z .. note:: To enable asynchronous execution, applications must pass the
2025-07-17T07:05:39.3515930Z     function object returned by this decorator to RPC APIs. If RPC detected
2025-07-17T07:05:39.3516280Z     attributes installed by this decorator, it knows that this function
2025-07-17T07:05:39.3516830Z     returns a ``Future`` object and will handle that accordingly.
2025-07-17T07:05:39.3517230Z     However, this does not mean this decorator has to be outmost one when
2025-07-17T07:05:39.3517560Z     defining a function. For example, when combined with ``@staticmethod``
2025-07-17T07:05:39.3517890Z     or ``@classmethod``, ``@rpc.functions.async_execution`` needs to be the
2025-07-17T07:05:39.3518220Z     inner decorator to allow the target function be recognized as a static
2025-07-17T07:05:39.3518560Z     or class function. This target function can still execute asynchronously
2025-07-17T07:05:39.3518910Z     because, when accessed, the static or class method preserves attributes
2025-07-17T07:05:39.3519210Z     installed by ``@rpc.functions.async_execution``.
2025-07-17T07:05:39.3519370Z 
2025-07-17T07:05:39.3519370Z 
2025-07-17T07:05:39.3519420Z Example::
2025-07-17T07:05:39.3519610Z     The returned :class:`~torch.futures.Future` object can come from
2025-07-17T07:05:39.3519910Z     :meth:`~torch.distributed.rpc.rpc_async`,
2025-07-17T07:05:39.3520190Z     :meth:`~torch.futures.Future.then`, or :class:`~torch.futures.Future`
2025-07-17T07:05:39.3520510Z     constructor. The example below shows directly using the
2025-07-17T07:05:39.3520760Z     :class:`~torch.futures.Future` returned by
2025-07-17T07:05:39.3520970Z     :meth:`~torch.futures.Future.then`.
2025-07-17T07:05:39.3521100Z 
2025-07-17T07:05:39.3521180Z     >>> from torch.distributed import rpc
2025-07-17T07:05:39.3521350Z     >>>
2025-07-17T07:05:39.3521480Z     >>> # omitting setup and shutdown RPC
2025-07-17T07:05:39.3521650Z     >>>
2025-07-17T07:05:39.3521760Z     >>> # On all workers
2025-07-17T07:05:39.3521920Z     >>> @rpc.functions.async_execution
2025-07-17T07:05:39.3522110Z     >>> def async_add_chained(to, x, y, z):
2025-07-17T07:05:39.3522360Z     >>>     # This function runs on "worker1" and returns immediately when
2025-07-17T07:05:39.3522660Z     >>>     # the callback is installed through the `then(cb)` API. In the
2025-07-17T07:05:39.3522970Z     >>>     # mean time, the `rpc_async` to "worker2" can run concurrently.
2025-07-17T07:05:39.3523240Z     >>>     # When the return value of that `rpc_async` arrives at
2025-07-17T07:05:39.3523520Z     >>>     # "worker1", "worker1" will run the lambda function accordingly
2025-07-17T07:05:39.3523810Z     >>>     # and set the value for the previously returned `Future`, which
2025-07-17T07:05:39.3524110Z     >>>     # will then trigger RPC to send the result back to "worker0".
2025-07-17T07:05:39.3524390Z     >>>     return rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-07-17T07:05:39.3524620Z     >>>         lambda fut: fut.wait() + z
2025-07-17T07:05:39.3524800Z     >>>     )
2025-07-17T07:05:39.3524920Z     >>>
2025-07-17T07:05:39.3525020Z     >>> # On worker0
2025-07-17T07:05:39.3525170Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:39.3525320Z     >>> ret = rpc.rpc_sync(
2025-07-17T07:05:39.3525470Z     >>>     "worker1",
2025-07-17T07:05:39.3525610Z     >>>     async_add_chained,
2025-07-17T07:05:39.3525850Z     >>>     args=("worker2", torch.ones(2), 1, 1)
2025-07-17T07:05:39.3526030Z     >>> )
2025-07-17T07:05:39.3526160Z     >>> print(ret)  # prints tensor([3., 3.])
2025-07-17T07:05:39.3526300Z 
2025-07-17T07:05:39.3526430Z     When combined with TorchScript decorators, this decorator must be the
2025-07-17T07:05:39.3526710Z     outmost one.
2025-07-17T07:05:39.3526790Z 
2025-07-17T07:05:39.3526850Z     >>> from torch import Tensor
2025-07-17T07:05:39.3527030Z     >>> from torch.futures import Future
2025-07-17T07:05:39.3527230Z     >>> from torch.distributed import rpc
2025-07-17T07:05:39.3527400Z     >>>
2025-07-17T07:05:39.3527520Z     >>> # omitting setup and shutdown RPC
2025-07-17T07:05:39.3527700Z     >>>
2025-07-17T07:05:39.3527810Z     >>> # On all workers
2025-07-17T07:05:39.3527960Z     >>> @torch.jit.script
2025-07-17T07:05:39.3528150Z     >>> def script_add(x: Tensor, y: Tensor) -> Tensor:
2025-07-17T07:05:39.3528350Z     >>>     return x + y
2025-07-17T07:05:39.3528510Z     >>>
2025-07-17T07:05:39.3528670Z     >>> @rpc.functions.async_execution
2025-07-17T07:05:39.3528850Z     >>> @torch.jit.script
2025-07-17T07:05:39.3529070Z     >>> def async_add(to: str, x: Tensor, y: Tensor) -> Future[Tensor]:
2025-07-17T07:05:39.3529340Z     >>>     return rpc.rpc_async(to, script_add, (x, y))
2025-07-17T07:05:39.3529540Z     >>>
2025-07-17T07:05:39.3529640Z     >>> # On worker0
2025-07-17T07:05:39.3529790Z     >>> ret = rpc.rpc_sync(
2025-07-17T07:05:39.3529930Z     >>>     "worker1",
2025-07-17T07:05:39.3530070Z     >>>     async_add,
2025-07-17T07:05:39.3530250Z     >>>     args=("worker2", torch.ones(2), 1)
2025-07-17T07:05:39.3530430Z     >>> )
2025-07-17T07:05:39.3530560Z     >>> print(ret)  # prints tensor([2., 2.])
2025-07-17T07:05:39.3530690Z 
2025-07-17T07:05:39.3530820Z     When combined with static or class method, this decorator must be the
2025-07-17T07:05:39.3531060Z     inner one.
2025-07-17T07:05:39.3531140Z 
2025-07-17T07:05:39.3531200Z     >>> from torch.distributed import rpc
2025-07-17T07:05:39.3531380Z     >>>
2025-07-17T07:05:39.3531510Z     >>> # omitting setup and shutdown RPC
2025-07-17T07:05:39.3531680Z     >>>
2025-07-17T07:05:39.3531790Z     >>> # On all workers
2025-07-17T07:05:39.3531950Z     >>> class AsyncExecutionClass:
2025-07-17T07:05:39.3532110Z     >>>
2025-07-17T07:05:39.3532220Z     >>>     @staticmethod
2025-07-17T07:05:39.3532380Z     >>>     @rpc.functions.async_execution
2025-07-17T07:05:39.3532580Z     >>>     def static_async_add(to, x, y, z):
2025-07-17T07:05:39.3532820Z     >>>         return rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-07-17T07:05:39.3533060Z     >>>             lambda fut: fut.wait() + z
2025-07-17T07:05:39.3533230Z     >>>         )
2025-07-17T07:05:39.3533350Z     >>>
2025-07-17T07:05:39.3533460Z     >>>     @classmethod
2025-07-17T07:05:39.3533630Z     >>>     @rpc.functions.async_execution
2025-07-17T07:05:39.3533840Z     >>>     def class_async_add(cls, to, x, y, z):
2025-07-17T07:05:39.3534050Z     >>>         ret_fut = torch.futures.Future()
2025-07-17T07:05:39.3534280Z     >>>         rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-07-17T07:05:39.3534530Z     >>>             lambda fut: ret_fut.set_result(fut.wait() + z)
2025-07-17T07:05:39.3534730Z     >>>         )
2025-07-17T07:05:39.3534870Z     >>>         return ret_fut
2025-07-17T07:05:39.3535020Z     >>>
2025-07-17T07:05:39.3535150Z     >>>     @rpc.functions.async_execution
2025-07-17T07:05:39.3535360Z     >>>     def bound_async_add(self, to, x, y, z):
2025-07-17T07:05:39.3535600Z     >>>         return rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-07-17T07:05:39.3535830Z     >>>             lambda fut: fut.wait() + z
2025-07-17T07:05:39.3536010Z     >>>         )
2025-07-17T07:05:39.3536130Z     >>>
2025-07-17T07:05:39.3536230Z     >>> # On worker0
2025-07-17T07:05:39.3536370Z     >>> ret = rpc.rpc_sync(
2025-07-17T07:05:39.3536510Z     >>>     "worker1",
2025-07-17T07:05:39.3536680Z     >>>     AsyncExecutionClass.static_async_add,
2025-07-17T07:05:39.3536900Z     >>>     args=("worker2", torch.ones(2), 1, 2)
2025-07-17T07:05:39.3537100Z     >>> )
2025-07-17T07:05:39.3537240Z     >>> print(ret)  # prints tensor([4., 4.])
2025-07-17T07:05:39.3537410Z     >>>
2025-07-17T07:05:39.3537530Z     >>> ret = rpc.rpc_sync(
2025-07-17T07:05:39.3537720Z     >>>     "worker1",
2025-07-17T07:05:39.3537890Z     >>>     AsyncExecutionClass.class_async_add,
2025-07-17T07:05:39.3538100Z     >>>     args=("worker2", torch.ones(2), 1, 2)
2025-07-17T07:05:39.3538280Z     >>> )
2025-07-17T07:05:39.3538420Z     >>> print(ret)  # prints tensor([4., 4.])
2025-07-17T07:05:39.3538550Z 
2025-07-17T07:05:39.3538650Z     This decorator also works with RRef helpers, i.e., .
2025-07-17T07:05:39.3538900Z     :meth:`torch.distributed.rpc.RRef.rpc_sync`,
2025-07-17T07:05:39.3539130Z     :meth:`torch.distributed.rpc.RRef.rpc_async`, and
2025-07-17T07:05:39.3539370Z     :meth:`torch.distributed.rpc.RRef.remote`.
2025-07-17T07:05:39.3539510Z 
2025-07-17T07:05:39.3539600Z     >>> from torch.distributed import rpc
2025-07-17T07:05:39.3539790Z     >>>
2025-07-17T07:05:39.3539940Z     >>> # reuse the AsyncExecutionClass class above
2025-07-17T07:05:39.3540180Z     >>> rref = rpc.remote("worker1", AsyncExecutionClass)
2025-07-17T07:05:39.3540460Z     >>> ret = rref.rpc_sync().static_async_add("worker2", torch.ones(2), 1, 2)
2025-07-17T07:05:39.3540730Z     >>> print(ret)  # prints tensor([4., 4.])
2025-07-17T07:05:39.3540900Z     >>>
2025-07-17T07:05:39.3541060Z     >>> rref = rpc.remote("worker1", AsyncExecutionClass)
2025-07-17T07:05:39.3541350Z     >>> ret = rref.rpc_async().static_async_add("worker2", torch.ones(2), 1, 2).wait()
2025-07-17T07:05:39.3541630Z     >>> print(ret)  # prints tensor([4., 4.])
2025-07-17T07:05:39.3541800Z     >>>
2025-07-17T07:05:39.3541950Z     >>> rref = rpc.remote("worker1", AsyncExecutionClass)
2025-07-17T07:05:39.3542240Z     >>> ret = rref.remote().static_async_add("worker2", torch.ones(2), 1, 2).to_here()
2025-07-17T07:05:39.3542520Z     >>> print(ret)  # prints tensor([4., 4.])
2025-07-17T07:05:39.3542650Z 
2025-07-17T07:05:39.3542810Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.3543030Z 
2025-07-17T07:05:39.3543510Z msg = Cannot scrape callname=TensorPipeRpcBackendOptions.set_device_map in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/rpc/options.py line=113.
2025-07-17T07:05:39.3544190Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.3544410Z 
2025-07-17T07:05:39.3544540Z Set device mapping between each RPC caller and callee pair. This
2025-07-17T07:05:39.3544830Z function can be called multiple times to incrementally add
2025-07-17T07:05:39.3545070Z device placement configurations.
2025-07-17T07:05:39.3545190Z 
2025-07-17T07:05:39.3545230Z Args:
2025-07-17T07:05:39.3545350Z     to (str): Callee name.
2025-07-17T07:05:39.3545570Z     device_map (Dict of int, str, or torch.device): Device placement
2025-07-17T07:05:39.3545870Z         mappings from this worker to the callee. This map must be
2025-07-17T07:05:39.3546090Z         invertible.
2025-07-17T07:05:39.3546180Z 
2025-07-17T07:05:39.3552540Z Example:
2025-07-17T07:05:39.3552690Z     >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:39.3552870Z     >>> # both workers
2025-07-17T07:05:39.3553010Z     >>> def add(x, y):
2025-07-17T07:05:39.3553180Z     >>>     print(x)  # tensor([1., 1.], device='cuda:1')
2025-07-17T07:05:39.3553390Z     >>>     return x + y, (x + y).to(2)
2025-07-17T07:05:39.3553560Z     >>>
2025-07-17T07:05:39.3553670Z     >>> # on worker 0
2025-07-17T07:05:39.3553840Z     >>> options = TensorPipeRpcBackendOptions(
2025-07-17T07:05:39.3554040Z     >>>     num_worker_threads=8,
2025-07-17T07:05:39.3554220Z     >>>     device_maps={"worker1": {0: 1}}
2025-07-17T07:05:39.3554430Z     >>> # maps worker0's cuda:0 to worker1's cuda:1
2025-07-17T07:05:39.3554610Z     >>> )
2025-07-17T07:05:39.3554760Z     >>> options.set_device_map("worker1", {1: 2})
2025-07-17T07:05:39.3555040Z     >>> # maps worker0's cuda:1 to worker1's cuda:2
2025-07-17T07:05:39.3555240Z     >>>
2025-07-17T07:05:39.3555350Z     >>> rpc.init_rpc(
2025-07-17T07:05:39.3555490Z     >>>     "worker0",
2025-07-17T07:05:39.3555620Z     >>>     rank=0,
2025-07-17T07:05:39.3555800Z     >>>     world_size=2,
2025-07-17T07:05:39.3555970Z     >>>     backend=rpc.BackendType.TENSORPIPE,
2025-07-17T07:05:39.3556180Z     >>>     rpc_backend_options=options
2025-07-17T07:05:39.3556340Z     >>> )
2025-07-17T07:05:39.3556450Z     >>>
2025-07-17T07:05:39.3556570Z     >>> x = torch.ones(2)
2025-07-17T07:05:39.3556760Z     >>> rets = rpc.rpc_sync("worker1", add, args=(x.to(0), 1))
2025-07-17T07:05:39.3557050Z     >>> # The first argument will be moved to cuda:1 on worker1. When
2025-07-17T07:05:39.3557340Z     >>> # sending the return value back, it will follow the invert of
2025-07-17T07:05:39.3557690Z     >>> # the device map, and hence will be moved back to cuda:0 and
2025-07-17T07:05:39.3557950Z     >>> # cuda:1 on worker0
2025-07-17T07:05:39.3558140Z     >>> print(rets[0])  # tensor([2., 2.], device='cuda:0')
2025-07-17T07:05:39.3558380Z     >>> print(rets[1])  # tensor([2., 2.], device='cuda:1')
2025-07-17T07:05:39.3558540Z 
2025-07-17T07:05:39.3558690Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.5345690Z 
2025-07-17T07:05:39.5346450Z msg = Cannot scrape callname=_server_process_global_profile in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/rpc/server_process_global_profiler.py line=19.
2025-07-17T07:05:39.5347230Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.5347470Z 
2025-07-17T07:05:39.5347710Z It has the same API as ``torch.autograd.profiler.profile`` class,
2025-07-17T07:05:39.5348100Z except that it enables profiling on all threads running RPC server request callbacks.
2025-07-17T07:05:39.5348360Z 
2025-07-17T07:05:39.5348540Z Context manager that manages autograd profiler state and holds a summary of results.
2025-07-17T07:05:39.5348930Z Under the hood it just records events of functions being executed in C++ and
2025-07-17T07:05:39.5349290Z exposes those events to Python. You can wrap any code into it and it will
2025-07-17T07:05:39.5349590Z only report runtime of PyTorch functions.
2025-07-17T07:05:39.5349900Z Note: profiler is thread local and is automatically propagated into the async tasks
2025-07-17T07:05:39.5350140Z 
2025-07-17T07:05:39.5350180Z Args:
2025-07-17T07:05:39.5350410Z     enabled (bool, optional): Setting this to False makes this context manager a no-op.
2025-07-17T07:05:39.5350740Z         Default: ``True``.
2025-07-17T07:05:39.5350850Z 
2025-07-17T07:05:39.5351030Z     use_cuda (bool, optional): Enables timing of CUDA events as well using the cudaEvent API.
2025-07-17T07:05:39.5351410Z         Adds approximately 4us of overhead to each tensor operation.
2025-07-17T07:05:39.5351660Z         Default: ``False``
2025-07-17T07:05:39.5351770Z 
2025-07-17T07:05:39.5351920Z     record_shapes (bool, optional): If shapes recording is set, information
2025-07-17T07:05:39.5352270Z         about input dimensions will be collected. This allows one to see which
2025-07-17T07:05:39.5352600Z         dimensions have been used under the hood and further group by them
2025-07-17T07:05:39.5352930Z         using prof.key_averages(group_by_input_shape=True). Please note that
2025-07-17T07:05:39.5353430Z         shape recording might skew your profiling data. It is recommended to
2025-07-17T07:05:39.5353780Z         use separate runs with and without shape recording to validate the timing.
2025-07-17T07:05:39.5354130Z         Most likely the skew will be negligible for bottom most events (in a case
2025-07-17T07:05:39.5354470Z         of nested function calls). But for higher level functions the total
2025-07-17T07:05:39.5354780Z         self cpu time might be artificially increased because of the shape
2025-07-17T07:05:39.5355030Z         collection.
2025-07-17T07:05:39.5355110Z 
2025-07-17T07:05:39.5355520Z     profile_memory (bool, optional): Whether to report memory usage, default: ``False``
2025-07-17T07:05:39.5355750Z 
2025-07-17T07:05:39.5355820Z .. warning::
2025-07-17T07:05:39.5356140Z     Enabling memory profiling incurs additional profiler overhead
2025-07-17T07:05:39.5356330Z 
2025-07-17T07:05:39.5356370Z .. warning::
2025-07-17T07:05:39.5356620Z     Due to some CUDA multiprocessing limitations (see :ref:`multiprocessing-cuda-note`),
2025-07-17T07:05:39.5356980Z     one cannot use the profiler with ``use_cuda = True`` to benchmark
2025-07-17T07:05:39.5357310Z     DataLoaders with ``num_workers > 0``. If you wish to benchmark data loading,
2025-07-17T07:05:39.5357610Z     please use ``use_cuda = False`` or ``num_workers = 0``.
2025-07-17T07:05:39.5357770Z 
2025-07-17T07:05:39.5357810Z Example:
2025-07-17T07:05:39.5357940Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:39.5358170Z     >>> # On worker 0:
2025-07-17T07:05:39.5358360Z     >>> import torch
2025-07-17T07:05:39.5358520Z     >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:39.5358750Z     >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-07-17T07:05:39.5358980Z     >>> x, y = torch.tensor(1), torch.tensor(2)
2025-07-17T07:05:39.5359180Z     >>> outer_profile_rref = rpc.remote(
2025-07-17T07:05:39.5359410Z     ...     dst_worker_name, rpc._server_process_global_profile
2025-07-17T07:05:39.5359620Z     ... )
2025-07-17T07:05:39.5359760Z     >>> outer_profile_rref.rpc_sync().__enter__()
2025-07-17T07:05:39.5360000Z     >>> rpc.rpc_sync(dst_worker_name, torch.add, (x, y))
2025-07-17T07:05:39.5360210Z     >>> inner_profile_rref = rpc.remote(
2025-07-17T07:05:39.5360440Z     ...     dst_worker_name, rpc._server_process_global_profile
2025-07-17T07:05:39.5360640Z     ... )
2025-07-17T07:05:39.5360780Z     >>> inner_profile_rref.rpc_sync().__enter__()
2025-07-17T07:05:39.5361010Z     >>> rpc.rpc_sync(dst_worker_name, torch.sub, (x, y))
2025-07-17T07:05:39.5361270Z     >>> inner_profile_rref.rpc_sync().__exit__(None, None, None)
2025-07-17T07:05:39.5361550Z     >>> outer_profile_rref.rpc_sync().__exit__(None, None, None)
2025-07-17T07:05:39.5361810Z     >>> print(inner_profile_rref.rpc_sync().key_averages())
2025-07-17T07:05:39.5362130Z     ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-07-17T07:05:39.5362540Z     Name       Self CPU total %  Self CPU total   CPU total %      CPU total        CPU time avg     Number of Calls
2025-07-17T07:05:39.5362930Z     ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-07-17T07:05:39.5363270Z     sub        85.06%           76.275us         100.00%          89.667us         89.667us         1
2025-07-17T07:05:39.5363570Z     empty      14.94%           13.392us         14.94%           13.392us         13.392us         1
2025-07-17T07:05:39.5363900Z     ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-07-17T07:05:39.5364180Z     Self CPU time total: 89.667us
2025-07-17T07:05:39.5364390Z     >>> print(outer_profile_rref.rpc_sync().key_averages())
2025-07-17T07:05:39.5364690Z     ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-07-17T07:05:39.5365090Z     Name       Self CPU total %  Self CPU total   CPU total %      CPU total        CPU time avg     Number of Calls
2025-07-17T07:05:39.5365480Z     ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-07-17T07:05:39.5365800Z     sub        35.65%           76.275us         41.91%           89.667us         89.667us         1
2025-07-17T07:05:39.5366100Z     empty      12.67%           27.101us         12.67%           27.101us         13.551us         2
2025-07-17T07:05:39.5366400Z     add        51.68%           110.550us        58.09%           124.259us        124.259us        1
2025-07-17T07:05:39.5366780Z     ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-07-17T07:05:39.5367050Z     Self CPU time total: 213.926us
2025-07-17T07:05:39.5367250Z     >>> rpc.shutdown()
2025-07-17T07:05:39.5367350Z 
2025-07-17T07:05:39.5367400Z     >>> # On worker 1:
2025-07-17T07:05:39.5367560Z     >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:39.5367780Z     >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-07-17T07:05:39.5368030Z     >>> # wait for worker 0 to finish work, and then shutdown.
2025-07-17T07:05:39.5368240Z     >>> rpc.shutdown()
2025-07-17T07:05:39.5368330Z 
2025-07-17T07:05:39.5368480Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.5368700Z 
2025-07-17T07:05:39.5369120Z msg = Cannot scrape callname=record_function in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/profiler.py line=734.
2025-07-17T07:05:39.5369750Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.5370200Z Context manager/function decorator that adds a label to a code block/function when running autograd profiler.
2025-07-17T07:05:39.5370600Z     Label will only appear if CPU activity tracing is enabled.
2025-07-17T07:05:39.5370780Z 
2025-07-17T07:05:39.5370860Z     It is useful when tracing the code profile.
2025-07-17T07:05:39.5371000Z 
2025-07-17T07:05:39.5371050Z     Args:
2025-07-17T07:05:39.5371200Z         name (str): Label assigned to the block of code.
2025-07-17T07:05:39.5371460Z         node_id (int): ID of node, for distributed profiling. Unset in
2025-07-17T07:05:39.5371700Z         non-distributed cases.
2025-07-17T07:05:39.5371810Z 
2025-07-17T07:05:39.5371860Z     Example:
2025-07-17T07:05:39.5372040Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_AUTOGRAD_PROFILER)
2025-07-17T07:05:39.5372290Z         >>> x = torch.randn((1, 1), requires_grad=True)
2025-07-17T07:05:39.5372530Z         >>> with torch.autograd.profiler.profile() as prof:
2025-07-17T07:05:39.5372740Z         ...     y = x**2
2025-07-17T07:05:39.5372940Z         ...     with torch.autograd.profiler.record_function(
2025-07-17T07:05:39.5373160Z         ...         "label-z"
2025-07-17T07:05:39.5373320Z         ...     ):  # label the block
2025-07-17T07:05:39.5373520Z         ...         z = y**3
2025-07-17T07:05:39.5373670Z         ...     y.backward()
2025-07-17T07:05:39.5373830Z         >>> # xdoctest: +IGNORE_WANT
2025-07-17T07:05:39.5374030Z         >>> # NOTE: some columns were removed for brevity
2025-07-17T07:05:39.5374300Z         >>> print(prof.key_averages().table(sort_by="self_cpu_time_total"))
2025-07-17T07:05:39.5374610Z         -----------------------------------  ---------------  ---------------  ---------------
2025-07-17T07:05:39.5374920Z         Name                                 Self CPU total %  CPU time avg     Number of Calls
2025-07-17T07:05:39.5375230Z         -----------------------------------  ---------------  ---------------  ---------------
2025-07-17T07:05:39.5375500Z         pow                                  60.77%           47.470us         3
2025-07-17T07:05:39.5375730Z         mul                                  21.73%           25.465us         2
2025-07-17T07:05:39.5376000Z         PowBackward0                         12.03%           121.891us        1
2025-07-17T07:05:39.5376300Z         torch::autograd::AccumulateGrad      2.70%            6.324us          1
2025-07-17T07:05:39.5376580Z         label-z                              2.13%            12.421us         1
2025-07-17T07:05:39.5376860Z         torch::autograd::GraphRoot           0.64%            1.503us          1
2025-07-17T07:05:39.5377160Z         -----------------------------------  ---------------  ---------------  ---------------
2025-07-17T07:05:39.5377410Z         Self CPU time total: 234.344us
2025-07-17T07:05:39.5377600Z         CUDA time total: 0.000us
2025-07-17T07:05:39.5377710Z 
2025-07-17T07:05:39.5377760Z     
2025-07-17T07:05:39.5377990Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.5378220Z 
2025-07-17T07:05:39.5378670Z msg = Cannot scrape callname=assoc_in in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=245.
2025-07-17T07:05:39.5379370Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.5379710Z Return a new dict with new, potentially nested, key value pair
2025-07-17T07:05:39.5379890Z 
2025-07-17T07:05:39.5379930Z     >>> purchase = {
2025-07-17T07:05:39.5380080Z     ...     "name": "Alice",
2025-07-17T07:05:39.5380300Z     ...     "order": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]},
2025-07-17T07:05:39.5380550Z     ...     "credit card": "5555-1234-1234-1234",
2025-07-17T07:05:39.5380730Z     ... }
2025-07-17T07:05:39.5380970Z     >>> assoc_in(purchase, ["order", "costs"], [0.25, 1.00])  # doctest: +SKIP
2025-07-17T07:05:39.5381240Z     {'credit card': '5555-1234-1234-1234',
2025-07-17T07:05:39.5381420Z      'name': 'Alice',
2025-07-17T07:05:39.5381610Z      'order': {'costs': [0.25, 1.00], 'items': ['Apple', 'Orange']}}
2025-07-17T07:05:39.5381820Z     
2025-07-17T07:05:39.5382040Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.5382260Z 
2025-07-17T07:05:39.5382710Z msg = Cannot scrape callname=update_in in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=261.
2025-07-17T07:05:39.5383380Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.5383680Z Update value in a (potentially) nested dictionary
2025-07-17T07:05:39.5383840Z 
2025-07-17T07:05:39.5383890Z     inputs:
2025-07-17T07:05:39.5384030Z     d - dictionary on which to operate
2025-07-17T07:05:39.5384290Z     keys - list or tuple giving the location of the value to be changed in d
2025-07-17T07:05:39.5384560Z     func - function to operate on that value
2025-07-17T07:05:39.5384690Z 
2025-07-17T07:05:39.5384820Z     If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the
2025-07-17T07:05:39.5385140Z     original dictionary with v replaced by func(v), but does not mutate the
2025-07-17T07:05:39.5385390Z     original dictionary.
2025-07-17T07:05:39.5385490Z 
2025-07-17T07:05:39.5385620Z     If k0 is not a key in d, update_in creates nested dictionaries to the depth
2025-07-17T07:05:39.5385940Z     specified by the keys, with the innermost value set to func(default).
2025-07-17T07:05:39.5386140Z 
2025-07-17T07:05:39.5386190Z     >>> inc = lambda x: x + 1
2025-07-17T07:05:39.5386360Z     >>> update_in({"a": 0}, ["a"], inc)
2025-07-17T07:05:39.5386530Z     {'a': 1}
2025-07-17T07:05:39.5386600Z 
2025-07-17T07:05:39.5386650Z     >>> transaction = {
2025-07-17T07:05:39.5386800Z     ...     "name": "Alice",
2025-07-17T07:05:39.5387050Z     ...     "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]},
2025-07-17T07:05:39.5387300Z     ...     "credit card": "5555-1234-1234-1234",
2025-07-17T07:05:39.5387470Z     ... }
2025-07-17T07:05:39.5387670Z     >>> update_in(transaction, ["purchase", "costs"], sum)  # doctest: +SKIP
2025-07-17T07:05:39.5387930Z     {'credit card': '5555-1234-1234-1234',
2025-07-17T07:05:39.5388100Z      'name': 'Alice',
2025-07-17T07:05:39.5388280Z      'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}}
2025-07-17T07:05:39.5388450Z 
2025-07-17T07:05:39.5388520Z     >>> # updating a value when k0 is not in d
2025-07-17T07:05:39.5388740Z     >>> update_in({}, [1, 2, 3], str, default="bar")
2025-07-17T07:05:39.5388930Z     {1: {2: {3: 'bar'}}}
2025-07-17T07:05:39.5389090Z     >>> update_in({1: "foo"}, [2, 3, 4], inc, 0)
2025-07-17T07:05:39.5389270Z     {1: 'foo', 2: {3: {4: 1}}}
2025-07-17T07:05:39.5389420Z     
2025-07-17T07:05:39.5389650Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.5504140Z 
2025-07-17T07:05:39.5504810Z msg = Cannot scrape callname=get_in in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=320.
2025-07-17T07:05:39.5505640Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.5506030Z Returns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys.
2025-07-17T07:05:39.5506200Z 
2025-07-17T07:05:39.5506320Z     If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless
2025-07-17T07:05:39.5506630Z     ``no_default`` is specified, then it raises KeyError or IndexError.
2025-07-17T07:05:39.5506830Z 
2025-07-17T07:05:39.5506960Z     ``get_in`` is a generalization of ``operator.getitem`` for nested data
2025-07-17T07:05:39.5507240Z     structures such as dictionaries and lists.
2025-07-17T07:05:39.5507390Z 
2025-07-17T07:05:39.5507490Z     >>> transaction = {
2025-07-17T07:05:39.5507690Z     ...     "name": "Alice",
2025-07-17T07:05:39.5507920Z     ...     "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]},
2025-07-17T07:05:39.5508180Z     ...     "credit card": "5555-1234-1234-1234",
2025-07-17T07:05:39.5508360Z     ... }
2025-07-17T07:05:39.5508510Z     >>> get_in(["purchase", "items", 0], transaction)
2025-07-17T07:05:39.5508710Z     'Apple'
2025-07-17T07:05:39.5508840Z     >>> get_in(["name"], transaction)
2025-07-17T07:05:39.5509000Z     'Alice'
2025-07-17T07:05:39.5509140Z     >>> get_in(["purchase", "total"], transaction)
2025-07-17T07:05:39.5509380Z     >>> get_in(["purchase", "items", "apple"], transaction)
2025-07-17T07:05:39.5509620Z     >>> get_in(["purchase", "items", 10], transaction)
2025-07-17T07:05:39.5509840Z     >>> get_in(["purchase", "total"], transaction, 0)
2025-07-17T07:05:39.5510030Z     0
2025-07-17T07:05:39.5510160Z     >>> get_in(["y"], {}, no_default=True)
2025-07-17T07:05:39.5510360Z     Traceback (most recent call last):
2025-07-17T07:05:39.5510530Z         ...
2025-07-17T07:05:39.5510640Z     KeyError: 'y'
2025-07-17T07:05:39.5510730Z 
2025-07-17T07:05:39.5510770Z     See Also:
2025-07-17T07:05:39.5510890Z         itertoolz.get
2025-07-17T07:05:39.5511040Z         operator.getitem
2025-07-17T07:05:39.5511180Z     
2025-07-17T07:05:39.5511390Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.5511600Z 
2025-07-17T07:05:39.5512060Z msg = Cannot scrape callname=groupby in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=373.
2025-07-17T07:05:39.5512710Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.5513000Z Group a collection by a key function
2025-07-17T07:05:39.5513120Z 
2025-07-17T07:05:39.5513230Z     >>> names = ["Alice", "Bob", "Charlie", "Dan", "Edith", "Frank"]
2025-07-17T07:05:39.5513480Z     >>> groupby(len, names)  # doctest: +SKIP
2025-07-17T07:05:39.5513720Z     {3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']}
2025-07-17T07:05:39.5513890Z 
2025-07-17T07:05:39.5513950Z     >>> iseven = lambda x: x % 2 == 0
2025-07-17T07:05:39.5514170Z     >>> groupby(iseven, [1, 2, 3, 4, 5, 6, 7, 8])  # doctest: +SKIP
2025-07-17T07:05:39.5514410Z     {False: [1, 3, 5, 7], True: [2, 4, 6, 8]}
2025-07-17T07:05:39.5514550Z 
2025-07-17T07:05:39.5514630Z     Non-callable keys imply grouping on a member.
2025-07-17T07:05:39.5514790Z 
2025-07-17T07:05:39.5514830Z     >>> groupby(
2025-07-17T07:05:39.5514960Z     ...     "gender",
2025-07-17T07:05:39.5515090Z     ...     [
2025-07-17T07:05:39.5515220Z     ...         {"name": "Alice", "gender": "F"},
2025-07-17T07:05:39.5515430Z     ...         {"name": "Bob", "gender": "M"},
2025-07-17T07:05:39.5515630Z     ...         {"name": "Charlie", "gender": "M"},
2025-07-17T07:05:39.5515820Z     ...     ],
2025-07-17T07:05:39.5515940Z     ... )  # doctest:+SKIP
2025-07-17T07:05:39.5516140Z     {'F': [{'gender': 'F', 'name': 'Alice'}],
2025-07-17T07:05:39.5516340Z      'M': [{'gender': 'M', 'name': 'Bob'},
2025-07-17T07:05:39.5516530Z            {'gender': 'M', 'name': 'Charlie'}]}
2025-07-17T07:05:39.5516670Z 
2025-07-17T07:05:39.5516800Z     Not to be confused with ``itertools.groupby``
2025-07-17T07:05:39.5516950Z 
2025-07-17T07:05:39.5516990Z     See Also:
2025-07-17T07:05:39.5517110Z         countby
2025-07-17T07:05:39.5517230Z     
2025-07-17T07:05:39.5517440Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.5517660Z 
2025-07-17T07:05:39.5518040Z msg = Cannot scrape callname=SequentialLR in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=808.
2025-07-17T07:05:39.5518640Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.5519090Z Contains a list of schedulers expected to be called sequentially during the optimization process.
2025-07-17T07:05:39.5519380Z 
2025-07-17T07:05:39.5519600Z     Specifically, the schedulers will be called according to the milestone points, which should provide exact
2025-07-17T07:05:39.5520010Z     intervals by which each scheduler should be called at a given epoch.
2025-07-17T07:05:39.5520210Z 
2025-07-17T07:05:39.5520260Z     Args:
2025-07-17T07:05:39.5520400Z         optimizer (Optimizer): Wrapped optimizer.
2025-07-17T07:05:39.5520640Z         schedulers (list): List of chained schedulers.
2025-07-17T07:05:39.5520920Z         milestones (list): List of integers that reflects milestone points.
2025-07-17T07:05:39.5521220Z         last_epoch (int): The index of last epoch. Default: -1.
2025-07-17T07:05:39.5521390Z 
2025-07-17T07:05:39.5521440Z     Example:
2025-07-17T07:05:39.5521570Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:39.5528810Z         >>> # Assuming optimizer uses lr = 0.05 for all groups
2025-07-17T07:05:39.5529060Z         >>> # lr = 0.005     if epoch == 0
2025-07-17T07:05:39.5529250Z         >>> # lr = 0.005     if epoch == 1
2025-07-17T07:05:39.5529440Z         >>> # lr = 0.005     if epoch == 2
2025-07-17T07:05:39.5529600Z         >>> # ...
2025-07-17T07:05:39.5529740Z         >>> # lr = 0.05      if epoch == 20
2025-07-17T07:05:39.5529940Z         >>> # lr = 0.045     if epoch == 21
2025-07-17T07:05:39.5530120Z         >>> # lr = 0.0405    if epoch == 22
2025-07-17T07:05:39.5530370Z         >>> scheduler1 = ConstantLR(optimizer, factor=0.1, total_iters=20)
2025-07-17T07:05:39.5530650Z         >>> scheduler2 = ExponentialLR(optimizer, gamma=0.9)
2025-07-17T07:05:39.5530880Z         >>> scheduler = SequentialLR(
2025-07-17T07:05:39.5531060Z         ...     optimizer,
2025-07-17T07:05:39.5531240Z         ...     schedulers=[scheduler1, scheduler2],
2025-07-17T07:05:39.5531440Z         ...     milestones=[20],
2025-07-17T07:05:39.5531590Z         ... )
2025-07-17T07:05:39.5531720Z         >>> for epoch in range(100):
2025-07-17T07:05:39.5531890Z         >>>     train(...)
2025-07-17T07:05:39.5532040Z         >>>     validate(...)
2025-07-17T07:05:39.5532210Z         >>>     scheduler.step()
2025-07-17T07:05:39.5532320Z 
2025-07-17T07:05:39.5532430Z     .. image:: ../scripts/lr_scheduler_images/SequentialLR.png
2025-07-17T07:05:39.5532650Z     
2025-07-17T07:05:39.5532860Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:39.5533080Z 
2025-07-17T07:05:39.5533480Z msg = Cannot scrape callname=ReduceLROnPlateau in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1233.
2025-07-17T07:05:39.5534100Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:39.5534420Z Reduce learning rate when a metric has stopped improving.
2025-07-17T07:05:39.5534590Z 
2025-07-17T07:05:39.5534710Z     Models often benefit from reducing the learning rate by a factor
2025-07-17T07:05:39.5535020Z     of 2-10 once learning stagnates. This scheduler reads a metrics
2025-07-17T07:05:39.5535400Z     quantity and if no improvement is seen for a 'patience' number
2025-07-17T07:05:39.5535660Z     of epochs, the learning rate is reduced.
2025-07-17T07:05:39.5535800Z 
2025-07-17T07:05:39.5535840Z     Args:
2025-07-17T07:05:39.5536010Z         optimizer (Optimizer): Wrapped optimizer.
2025-07-17T07:05:39.5536260Z         mode (str): One of `min`, `max`. In `min` mode, lr will
2025-07-17T07:05:39.5536520Z             be reduced when the quantity monitored has stopped
2025-07-17T07:05:39.5536780Z             decreasing; in `max` mode it will be reduced when the
2025-07-17T07:05:39.5537060Z             quantity monitored has stopped increasing. Default: 'min'.
2025-07-17T07:05:39.5537370Z         factor (float): Factor by which the learning rate will be
2025-07-17T07:05:39.5537630Z             reduced. new_lr = lr * factor. Default: 0.1.
2025-07-17T07:05:39.5537960Z         patience (int): The number of allowed epochs with no improvement after
2025-07-17T07:05:39.5538260Z             which the learning rate will be reduced.
2025-07-17T07:05:39.5538550Z             For example, consider the case of having no patience (`patience = 0`).
2025-07-17T07:05:39.5538970Z             In the first epoch, a baseline is established and is always considered good as there's no previous baseline.
2025-07-17T07:05:39.5539370Z             In the second epoch, if the performance is worse than the baseline,
2025-07-17T07:05:39.5539660Z             we have what is considered an intolerable epoch.
2025-07-17T07:05:39.5539970Z             Since the count of intolerable epochs (1) is greater than the patience level (0),
2025-07-17T07:05:39.5540300Z             the learning rate is reduced at the end of this epoch.
2025-07-17T07:05:39.5540660Z             From the third epoch onwards, the learning rate continues to be reduced at the end of each epoch
2025-07-17T07:05:39.5541100Z             if the performance is worse than the baseline. If the performance improves or remains the same,
2025-07-17T07:05:39.5541430Z             the learning rate is not adjusted.
2025-07-17T07:05:39.5541610Z             Default: 10.
2025-07-17T07:05:39.5541830Z         threshold (float): Threshold for measuring the new optimum,
2025-07-17T07:05:39.5542100Z             to only focus on significant changes. Default: 1e-4.
2025-07-17T07:05:39.5542370Z         threshold_mode (str): One of `rel`, `abs`. In `rel` mode,
2025-07-17T07:05:39.5542630Z             dynamic_threshold = best * ( 1 + threshold ) in 'max'
2025-07-17T07:05:39.5542880Z             mode or best * ( 1 - threshold ) in `min` mode.
2025-07-17T07:05:39.5543130Z             In `abs` mode, dynamic_threshold = best + threshold in
2025-07-17T07:05:39.5543390Z             `max` mode or best - threshold in `min` mode. Default: 'rel'.
2025-07-17T07:05:39.5543670Z         cooldown (int): Number of epochs to wait before resuming
2025-07-17T07:05:39.5543950Z             normal operation after lr has been reduced. Default: 0.
2025-07-17T07:05:39.5544220Z         min_lr (float or list): A scalar or a list of scalars. A
2025-07-17T07:05:39.5544480Z             lower bound on the learning rate of all param groups
2025-07-17T07:05:39.5544720Z             or each group respectively. Default: 0.
2025-07-17T07:05:39.5544980Z         eps (float): Minimal decay applied to lr. If the difference
2025-07-17T07:05:39.5545260Z             between new and old lr is smaller than eps, the update is
2025-07-17T07:05:39.5545490Z             ignored. Default: 1e-8.
2025-07-17T07:05:39.5545620Z 
2025-07-17T07:05:39.5545660Z     Example:
2025-07-17T07:05:39.5545790Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:39.5546030Z         >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)
2025-07-17T07:05:39.5546330Z         >>> scheduler = ReduceLROnPlateau(optimizer, "min")
2025-07-17T07:05:39.5546550Z         >>> for epoch in range(10):
2025-07-17T07:05:39.5546720Z         >>>     train(...)
2025-07-17T07:05:39.5546880Z         >>>     val_loss = validate(...)
2025-07-17T07:05:39.5547120Z         >>> # Note that step should be called after validate()
2025-07-17T07:05:39.5547340Z         >>>     scheduler.step(val_loss)
2025-07-17T07:05:39.5547470Z 
2025-07-17T07:05:39.5547590Z     .. image:: ../scripts/lr_scheduler_images/ReduceLROnPlateau.png
2025-07-17T07:05:39.5547880Z     
2025-07-17T07:05:39.5548190Z Original Error: IndentationError('unexpected indent', ('<source_block>', 8, 4, '    scheduler.step(val_loss)\n', 8, -1))
2025-07-17T07:05:39.5548490Z 
2025-07-17T07:05:39.5548550Z     scheduler.step(val_loss)
2025-07-17T07:05:39.5548700Z    ^
2025-07-17T07:05:39.5549140Z msg = Cannot scrape callname=CyclicLR in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1430.
2025-07-17T07:05:39.5549720Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:39.5550150Z Sets the learning rate of each parameter group according to cyclical learning rate policy (CLR).
2025-07-17T07:05:39.5550420Z 
2025-07-17T07:05:39.5550590Z     The policy cycles the learning rate between two boundaries with a constant frequency,
2025-07-17T07:05:39.5550980Z     as detailed in the paper `Cyclical Learning Rates for Training Neural Networks`_.
2025-07-17T07:05:39.5551340Z     The distance between the two boundaries can be scaled on a per-iteration
2025-07-17T07:05:39.5551600Z     or per-cycle basis.
2025-07-17T07:05:39.5551690Z 
2025-07-17T07:05:39.5551840Z     Cyclical learning rate policy changes the learning rate after every batch.
2025-07-17T07:05:39.5552170Z     `step` should be called after a batch has been used for training.
2025-07-17T07:05:39.5552170Z 
2025-07-17T07:05:39.5552300Z     This class has three built-in policies, as put forth in the paper:
2025-07-17T07:05:39.5552310Z 
2025-07-17T07:05:39.5552430Z     * "triangular": A basic triangular cycle without amplitude scaling.
2025-07-17T07:05:39.5552610Z     * "triangular2": A basic triangular cycle that scales initial amplitude by half each cycle.
2025-07-17T07:05:39.5552800Z     * "exp_range": A cycle that scales initial amplitude by :math:`\text{gamma}^{\text{cycle iterations}}`
2025-07-17T07:05:39.5552860Z       at each cycle iteration.
2025-07-17T07:05:39.5552860Z 
2025-07-17T07:05:39.5553010Z     This implementation was adapted from the github repo: `bckenstler/CLR`_
2025-07-17T07:05:39.5553010Z 
2025-07-17T07:05:39.5553060Z     Args:
2025-07-17T07:05:39.5553130Z         optimizer (Optimizer): Wrapped optimizer.
2025-07-17T07:05:39.5553250Z         base_lr (float or list): Initial learning rate which is the
2025-07-17T07:05:39.5553350Z             lower boundary in the cycle for each parameter group.
2025-07-17T07:05:39.5553470Z         max_lr (float or list): Upper learning rate boundaries in the cycle
2025-07-17T07:05:39.5553550Z             for each parameter group. Functionally,
2025-07-17T07:05:39.5553640Z             it defines the cycle amplitude (max_lr - base_lr).
2025-07-17T07:05:39.5553720Z             The lr at any cycle is the sum of base_lr
2025-07-17T07:05:39.5553800Z             and some scaling of the amplitude; therefore
2025-07-17T07:05:39.5553900Z             max_lr may not actually be reached depending on
2025-07-17T07:05:39.5553950Z             scaling function.
2025-07-17T07:05:39.5554050Z         step_size_up (int): Number of training iterations in the
2025-07-17T07:05:39.5554130Z             increasing half of a cycle. Default: 2000
2025-07-17T07:05:39.5554240Z         step_size_down (int): Number of training iterations in the
2025-07-17T07:05:39.5554330Z             decreasing half of a cycle. If step_size_down is None,
2025-07-17T07:05:39.5554420Z             it is set to step_size_up. Default: None
2025-07-17T07:05:39.5554520Z         mode (str): One of {triangular, triangular2, exp_range}.
2025-07-17T07:05:39.5554610Z             Values correspond to policies detailed above.
2025-07-17T07:05:39.5554690Z             If scale_fn is not None, this argument is ignored.
2025-07-17T07:05:39.5554760Z             Default: 'triangular'
2025-07-17T07:05:39.5554880Z         gamma (float): Constant in 'exp_range' scaling function:
2025-07-17T07:05:39.5554940Z             gamma**(cycle iterations)
2025-07-17T07:05:39.5554990Z             Default: 1.0
2025-07-17T07:05:39.5555130Z         scale_fn (function): Custom scaling policy defined by a single
2025-07-17T07:05:39.5555200Z             argument lambda function, where
2025-07-17T07:05:39.5555270Z             0 <= scale_fn(x) <= 1 for all x >= 0.
2025-07-17T07:05:39.5555340Z             If specified, then 'mode' is ignored.
2025-07-17T07:05:39.5555390Z             Default: None
2025-07-17T07:05:39.5555460Z         scale_mode (str): {'cycle', 'iterations'}.
2025-07-17T07:05:39.5555540Z             Defines whether scale_fn is evaluated on
2025-07-17T07:05:39.5555620Z             cycle number or cycle iterations (training
2025-07-17T07:05:39.5555690Z             iterations since start of cycle).
2025-07-17T07:05:39.5555770Z             Default: 'cycle'
2025-07-17T07:05:39.5555920Z         cycle_momentum (bool): If ``True``, momentum is cycled inversely
2025-07-17T07:05:39.5556030Z             to learning rate between 'base_momentum' and 'max_momentum'.
2025-07-17T07:05:39.5556080Z             Default: True
2025-07-17T07:05:39.5556210Z         base_momentum (float or list): Lower momentum boundaries in the cycle
2025-07-17T07:05:39.5556340Z             for each parameter group. Note that momentum is cycled inversely
2025-07-17T07:05:39.5556440Z             to learning rate; at the peak of a cycle, momentum is
2025-07-17T07:05:39.5556520Z             'base_momentum' and learning rate is 'max_lr'.
2025-07-17T07:05:39.5556570Z             Default: 0.8
2025-07-17T07:05:39.5556700Z         max_momentum (float or list): Upper momentum boundaries in the cycle
2025-07-17T07:05:39.5556780Z             for each parameter group. Functionally,
2025-07-17T07:05:39.5556890Z             it defines the cycle amplitude (max_momentum - base_momentum).
2025-07-17T07:05:39.5557010Z             The momentum at any cycle is the difference of max_momentum
2025-07-17T07:05:39.5557090Z             and some scaling of the amplitude; therefore
2025-07-17T07:05:39.5557200Z             base_momentum may not actually be reached depending on
2025-07-17T07:05:39.5557310Z             scaling function. Note that momentum is cycled inversely
2025-07-17T07:05:39.5557440Z             to learning rate; at the start of a cycle, momentum is 'max_momentum'
2025-07-17T07:05:39.5557500Z             and learning rate is 'base_lr'
2025-07-17T07:05:39.5557550Z             Default: 0.9
2025-07-17T07:05:39.5557690Z         last_epoch (int): The index of the last batch. This parameter is used when
2025-07-17T07:05:39.5557810Z             resuming a training job. Since `step()` should be invoked after each
2025-07-17T07:05:39.5557940Z             batch instead of after each epoch, this number represents the total
2025-07-17T07:05:39.5558080Z             number of *batches* computed, not the total number of epochs computed.
2025-07-17T07:05:39.5558210Z             When last_epoch=-1, the schedule is started from the beginning.
2025-07-17T07:05:39.5558260Z             Default: -1
2025-07-17T07:05:39.5558260Z 
2025-07-17T07:05:39.5558310Z     Example:
2025-07-17T07:05:39.5558360Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:39.5558500Z         >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)
2025-07-17T07:05:39.5558590Z         >>> scheduler = torch.optim.lr_scheduler.CyclicLR(
2025-07-17T07:05:39.5558640Z         ...     optimizer,
2025-07-17T07:05:39.5558690Z         ...     base_lr=0.01,
2025-07-17T07:05:39.5558740Z         ...     max_lr=0.1,
2025-07-17T07:05:39.5558800Z         ...     step_size_up=10,
2025-07-17T07:05:39.5558840Z         ... )
2025-07-17T07:05:39.5558930Z         >>> data_loader = torch.utils.data.DataLoader(...)
2025-07-17T07:05:39.5558990Z         >>> for epoch in range(10):
2025-07-17T07:05:39.5559050Z         >>>     for batch in data_loader:
2025-07-17T07:05:39.5559110Z         >>>         train_batch(...)
2025-07-17T07:05:39.5559180Z         >>>         scheduler.step()
2025-07-17T07:05:39.5559190Z 
2025-07-17T07:05:39.5559280Z     .. image:: ../scripts/lr_scheduler_images/CyclicLR.png
2025-07-17T07:05:39.5559290Z 
2025-07-17T07:05:39.5559500Z     .. _Cyclical Learning Rates for Training Neural Networks: https://arxiv.org/abs/1506.01186
2025-07-17T07:05:39.5559600Z     .. _bckenstler/CLR: https://github.com/bckenstler/CLR
2025-07-17T07:05:39.5559640Z     
2025-07-17T07:05:39.5559790Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.4652880Z 
2025-07-17T07:05:40.4653520Z msg = Cannot scrape callname=CosineAnnealingWarmRestarts in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1713.
2025-07-17T07:05:40.4654260Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.4654770Z Set the learning rate of each parameter group using a cosine annealing schedule.
2025-07-17T07:05:40.4655040Z 
2025-07-17T07:05:40.4655170Z     The :math:`\eta_{max}` is set to the initial lr, :math:`T_{cur}`
2025-07-17T07:05:40.4655500Z     is the number of epochs since the last restart and :math:`T_{i}` is the number
2025-07-17T07:05:40.4655810Z     of epochs between two warm restarts in SGDR:
2025-07-17T07:05:40.4655960Z 
2025-07-17T07:05:40.4656020Z     .. math::
2025-07-17T07:05:40.4656210Z         \eta_t = \eta_{min} + \frac{1}{2}(\eta_{max} - \eta_{min})\left(1 +
2025-07-17T07:05:40.4656490Z         \cos\left(\frac{T_{cur}}{T_{i}}\pi\right)\right)
2025-07-17T07:05:40.4656650Z 
2025-07-17T07:05:40.4656760Z     When :math:`T_{cur}=T_{i}`, set :math:`\eta_t = \eta_{min}`.
2025-07-17T07:05:40.4657050Z     When :math:`T_{cur}=0` after restart, set :math:`\eta_t=\eta_{max}`.
2025-07-17T07:05:40.4657240Z 
2025-07-17T07:05:40.4657300Z     It has been proposed in
2025-07-17T07:05:40.4657520Z     `SGDR: Stochastic Gradient Descent with Warm Restarts`_.
2025-07-17T07:05:40.4657690Z 
2025-07-17T07:05:40.4657750Z     Args:
2025-07-17T07:05:40.4657900Z         optimizer (Optimizer): Wrapped optimizer.
2025-07-17T07:05:40.4658150Z         T_0 (int): Number of iterations until the first restart.
2025-07-17T07:05:40.4658490Z         T_mult (int, optional): A factor by which :math:`T_{i}` increases after a restart. Default: 1.
2025-07-17T07:05:40.4658850Z         eta_min (float, optional): Minimum learning rate. Default: 0.
2025-07-17T07:05:40.4659160Z         last_epoch (int, optional): The index of the last epoch. Default: -1.
2025-07-17T07:05:40.4659350Z 
2025-07-17T07:05:40.4659460Z     .. _SGDR\: Stochastic Gradient Descent with Warm Restarts:
2025-07-17T07:05:40.4659700Z         https://arxiv.org/abs/1608.03983
2025-07-17T07:05:40.4659840Z 
2025-07-17T07:05:40.4659880Z     Example:
2025-07-17T07:05:40.4660010Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:40.4660230Z         >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.05)
2025-07-17T07:05:40.4660560Z         >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingWarmRestarts(
2025-07-17T07:05:40.4660830Z         ...     optimizer, T_0=20
2025-07-17T07:05:40.4660990Z         ... )
2025-07-17T07:05:40.4661120Z         >>> for epoch in range(100):
2025-07-17T07:05:40.4661290Z         >>>     train(...)
2025-07-17T07:05:40.4661440Z         >>>     validate(...)
2025-07-17T07:05:40.4661600Z         >>>     scheduler.step()
2025-07-17T07:05:40.4661710Z 
2025-07-17T07:05:40.4661850Z     .. image:: ../scripts/lr_scheduler_images/CosineAnnealingWarmRestarts.png
2025-07-17T07:05:40.4662100Z     
2025-07-17T07:05:40.4662320Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.4662540Z 
2025-07-17T07:05:40.4662920Z msg = Cannot scrape callname=OneCycleLR in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1863.
2025-07-17T07:05:40.4663510Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.4663990Z Sets the learning rate of each parameter group according to the 1cycle learning rate policy.
2025-07-17T07:05:40.4664240Z 
2025-07-17T07:05:40.4664420Z     The 1cycle policy anneals the learning rate from an initial learning rate to some maximum
2025-07-17T07:05:40.4664880Z     learning rate and then from that maximum learning rate to some minimum learning rate much
2025-07-17T07:05:40.4665190Z     lower than the initial learning rate.
2025-07-17T07:05:40.4665460Z     This policy was initially described in the paper `Super-Convergence:
2025-07-17T07:05:40.4665790Z     Very Fast Training of Neural Networks Using Large Learning Rates`_.
2025-07-17T07:05:40.4665980Z 
2025-07-17T07:05:40.4666130Z     The 1cycle learning rate policy changes the learning rate after every batch.
2025-07-17T07:05:40.4666460Z     `step` should be called after a batch has been used for training.
2025-07-17T07:05:40.4666640Z 
2025-07-17T07:05:40.4666730Z     This scheduler is not chainable.
2025-07-17T07:05:40.4666880Z 
2025-07-17T07:05:40.4667030Z     Note also that the total number of steps in the cycle can be determined in one
2025-07-17T07:05:40.4667320Z     of two ways (listed in order of precedence):
2025-07-17T07:05:40.4667480Z 
2025-07-17T07:05:40.4667570Z     #. A value for total_steps is explicitly provided.
2025-07-17T07:05:40.4667840Z     #. A number of epochs (epochs) and a number of steps per epoch
2025-07-17T07:05:40.4668080Z        (steps_per_epoch) are provided.
2025-07-17T07:05:40.4668310Z        In this case, the number of total steps is inferred by
2025-07-17T07:05:40.4668540Z        total_steps = epochs * steps_per_epoch
2025-07-17T07:05:40.4668680Z 
2025-07-17T07:05:40.4668820Z     You must either provide a value for total_steps or provide a value for both
2025-07-17T07:05:40.4669090Z     epochs and steps_per_epoch.
2025-07-17T07:05:40.4669210Z 
2025-07-17T07:05:40.4669400Z     The default behaviour of this scheduler follows the fastai implementation of 1cycle, which
2025-07-17T07:05:40.4669830Z     claims that "unpublished work has shown even better results by using only two phases". To
2025-07-17T07:05:40.4670250Z     mimic the behaviour of the original paper instead, set ``three_phase=True``.
2025-07-17T07:05:40.4670460Z 
2025-07-17T07:05:40.4670500Z     Args:
2025-07-17T07:05:40.4670650Z         optimizer (Optimizer): Wrapped optimizer.
2025-07-17T07:05:40.4670920Z         max_lr (float or list): Upper learning rate boundaries in the cycle
2025-07-17T07:05:40.4671180Z             for each parameter group.
2025-07-17T07:05:40.4671430Z         total_steps (int): The total number of steps in the cycle. Note that
2025-07-17T07:05:40.4671750Z             if a value is not provided here, then it must be inferred by providing
2025-07-17T07:05:40.4672060Z             a value for epochs and steps_per_epoch.
2025-07-17T07:05:40.4672260Z             Default: None
2025-07-17T07:05:40.4672480Z         epochs (int): The number of epochs to train for. This is used along
2025-07-17T07:05:40.4672830Z             with steps_per_epoch in order to infer the total number of steps in the cycle
2025-07-17T07:05:40.4673170Z             if a value for total_steps is not provided.
2025-07-17T07:05:40.4673370Z             Default: None
2025-07-17T07:05:40.4673600Z         steps_per_epoch (int): The number of steps per epoch to train for. This is
2025-07-17T07:05:40.4673950Z             used along with epochs in order to infer the total number of steps in the
2025-07-17T07:05:40.4674250Z             cycle if a value for total_steps is not provided.
2025-07-17T07:05:40.4674460Z             Default: None
2025-07-17T07:05:40.4674700Z         pct_start (float): The percentage of the cycle (in number of steps) spent
2025-07-17T07:05:40.4674970Z             increasing the learning rate.
2025-07-17T07:05:40.4675140Z             Default: 0.3
2025-07-17T07:05:40.4675310Z         anneal_strategy (str): {'cos', 'linear'}
2025-07-17T07:05:40.4675600Z             Specifies the annealing strategy: "cos" for cosine annealing, "linear" for
2025-07-17T07:05:40.4675900Z             linear annealing.
2025-07-17T07:05:40.4676060Z             Default: 'cos'
2025-07-17T07:05:40.4676280Z         cycle_momentum (bool): If ``True``, momentum is cycled inversely
2025-07-17T07:05:40.4676650Z             to learning rate between 'base_momentum' and 'max_momentum'.
2025-07-17T07:05:40.4676880Z             Default: True
2025-07-17T07:05:40.4677110Z         base_momentum (float or list): Lower momentum boundaries in the cycle
2025-07-17T07:05:40.4677460Z             for each parameter group. Note that momentum is cycled inversely
2025-07-17T07:05:40.4677760Z             to learning rate; at the peak of a cycle, momentum is
2025-07-17T07:05:40.4678010Z             'base_momentum' and learning rate is 'max_lr'.
2025-07-17T07:05:40.4678210Z             Default: 0.85
2025-07-17T07:05:40.4678440Z         max_momentum (float or list): Upper momentum boundaries in the cycle
2025-07-17T07:05:40.4678730Z             for each parameter group. Functionally,
2025-07-17T07:05:40.4679010Z             it defines the cycle amplitude (max_momentum - base_momentum).
2025-07-17T07:05:40.4679270Z             Note that momentum is cycled inversely
2025-07-17T07:05:40.4679530Z             to learning rate; at the start of a cycle, momentum is 'max_momentum'
2025-07-17T07:05:40.4679790Z             and learning rate is 'base_lr'
2025-07-17T07:05:40.4679970Z             Default: 0.95
2025-07-17T07:05:40.4680180Z         div_factor (float): Determines the initial learning rate via
2025-07-17T07:05:40.4680420Z             initial_lr = max_lr/div_factor
2025-07-17T07:05:40.4680590Z             Default: 25
2025-07-17T07:05:40.4680810Z         final_div_factor (float): Determines the minimum learning rate via
2025-07-17T07:05:40.4681070Z             min_lr = initial_lr/final_div_factor
2025-07-17T07:05:40.4681250Z             Default: 1e4
2025-07-17T07:05:40.4681500Z         three_phase (bool): If ``True``, use a third phase of the schedule to annihilate the
2025-07-17T07:05:40.4681880Z             learning rate according to 'final_div_factor' instead of modifying the second
2025-07-17T07:05:40.4682250Z             phase (the first two phases will be symmetrical about the step indicated by
2025-07-17T07:05:40.4682530Z             'pct_start').
2025-07-17T07:05:40.4682880Z         last_epoch (int): The index of the last batch. This parameter is used when
2025-07-17T07:05:40.4683240Z             resuming a training job. Since `step()` should be invoked after each
2025-07-17T07:05:40.4683620Z             batch instead of after each epoch, this number represents the total
2025-07-17T07:05:40.4690110Z             number of *batches* computed, not the total number of epochs computed.
2025-07-17T07:05:40.4690440Z             When last_epoch=-1, the schedule is started from the beginning.
2025-07-17T07:05:40.4690670Z             Default: -1
2025-07-17T07:05:40.4690760Z 
2025-07-17T07:05:40.4690810Z     Example:
2025-07-17T07:05:40.4690940Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:40.4691160Z         >>> data_loader = torch.utils.data.DataLoader(...)
2025-07-17T07:05:40.4691460Z         >>> optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9)
2025-07-17T07:05:40.4691770Z         >>> scheduler = torch.optim.lr_scheduler.OneCycleLR(
2025-07-17T07:05:40.4692070Z         ...     optimizer, max_lr=0.01, steps_per_epoch=len(data_loader), epochs=10
2025-07-17T07:05:40.4692300Z         ... )
2025-07-17T07:05:40.4692440Z         >>> for epoch in range(10):
2025-07-17T07:05:40.4692630Z         >>>     for batch in data_loader:
2025-07-17T07:05:40.4692810Z         >>>         train_batch(...)
2025-07-17T07:05:40.4692990Z         >>>         optimizer.step()
2025-07-17T07:05:40.4693160Z         >>>         scheduler.step()
2025-07-17T07:05:40.4693280Z 
2025-07-17T07:05:40.4693380Z     .. image:: ../scripts/lr_scheduler_images/OneCycleLR.png
2025-07-17T07:05:40.4693550Z 
2025-07-17T07:05:40.4693730Z     .. _Super-Convergence\: Very Fast Training of Neural Networks Using Large Learning Rates:
2025-07-17T07:05:40.4694140Z         https://arxiv.org/abs/1708.07120
2025-07-17T07:05:40.4694320Z     
2025-07-17T07:05:40.4694540Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.4694780Z 
2025-07-17T07:05:40.4695170Z msg = Cannot scrape callname=AveragedModel in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/swa_utils.py line=120.
2025-07-17T07:05:40.4695760Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.4696200Z Implements averaged model for Stochastic Weight Averaging (SWA) and Exponential Moving Average (EMA).
2025-07-17T07:05:40.4696490Z 
2025-07-17T07:05:40.4696640Z     Stochastic Weight Averaging was proposed in `Averaging Weights Leads to
2025-07-17T07:05:40.4696980Z     Wider Optima and Better Generalization`_ by Pavel Izmailov, Dmitrii
2025-07-17T07:05:40.4697350Z     Podoprikhin, Timur Garipov, Dmitry Vetrov and Andrew Gordon Wilson
2025-07-17T07:05:40.4697630Z     (UAI 2018).
2025-07-17T07:05:40.4697700Z 
2025-07-17T07:05:40.4697830Z     Exponential Moving Average is a variation of `Polyak averaging`_,
2025-07-17T07:05:40.4698170Z     but using exponential weights instead of equal weights across iterations.
2025-07-17T07:05:40.4698380Z 
2025-07-17T07:05:40.4698520Z     AveragedModel class creates a copy of the provided module :attr:`model`
2025-07-17T07:05:40.4698870Z     on the device :attr:`device` and allows to compute running averages of the
2025-07-17T07:05:40.4699140Z     parameters of the :attr:`model`.
2025-07-17T07:05:40.4699280Z 
2025-07-17T07:05:40.4699320Z     Args:
2025-07-17T07:05:40.4699480Z         model (torch.nn.Module): model to use with SWA/EMA
2025-07-17T07:05:40.4699780Z         device (torch.device, optional): if provided, the averaged model will be
2025-07-17T07:05:40.4700050Z             stored on the :attr:`device`
2025-07-17T07:05:40.4700300Z         avg_fn (function, optional): the averaging function used to update
2025-07-17T07:05:40.4700620Z             parameters; the function must take in the current value of the
2025-07-17T07:05:40.4700950Z             :class:`AveragedModel` parameter, the current value of :attr:`model`
2025-07-17T07:05:40.4701260Z             parameter, and the number of models already averaged; if None,
2025-07-17T07:05:40.4701550Z             an equally weighted average is used (default: None)
2025-07-17T07:05:40.4701850Z         multi_avg_fn (function, optional): the averaging function used to update
2025-07-17T07:05:40.4702190Z             parameters inplace; the function must take in the current values of the
2025-07-17T07:05:40.4702570Z             :class:`AveragedModel` parameters as a list, the current values of :attr:`model`
2025-07-17T07:05:40.4702940Z             parameters as a list, and the number of models already averaged; if None,
2025-07-17T07:05:40.4703240Z             an equally weighted average is used (default: None)
2025-07-17T07:05:40.4703530Z         use_buffers (bool): if ``True``, it will compute running averages for
2025-07-17T07:05:40.4703860Z             both the parameters and the buffers of the model. (default: ``False``)
2025-07-17T07:05:40.4704070Z 
2025-07-17T07:05:40.4704110Z     Example:
2025-07-17T07:05:40.4704270Z         >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:40.4704490Z         >>> loader, optimizer, model, loss_fn = ...
2025-07-17T07:05:40.4704740Z         >>> swa_model = torch.optim.swa_utils.AveragedModel(model)
2025-07-17T07:05:40.4705040Z         >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer,
2025-07-17T07:05:40.4705310Z         >>>                                     T_max=300)
2025-07-17T07:05:40.4705500Z         >>> swa_start = 160
2025-07-17T07:05:40.4705690Z         >>> swa_scheduler = SWALR(optimizer, swa_lr=0.05)
2025-07-17T07:05:40.4705900Z         >>> for i in range(300):
2025-07-17T07:05:40.4706080Z         >>>      for input, target in loader:
2025-07-17T07:05:40.4706280Z         >>>          optimizer.zero_grad()
2025-07-17T07:05:40.4706540Z         >>>          loss_fn(model(input), target).backward()
2025-07-17T07:05:40.4706750Z         >>>          optimizer.step()
2025-07-17T07:05:40.4706930Z         >>>      if i > swa_start:
2025-07-17T07:05:40.4707140Z         >>>          swa_model.update_parameters(model)
2025-07-17T07:05:40.4707340Z         >>>          swa_scheduler.step()
2025-07-17T07:05:40.4707520Z         >>>      else:
2025-07-17T07:05:40.4707670Z         >>>          scheduler.step()
2025-07-17T07:05:40.4707830Z         >>>
2025-07-17T07:05:40.4707990Z         >>> # Update bn statistics for the swa_model at the end
2025-07-17T07:05:40.4708250Z         >>> torch.optim.swa_utils.update_bn(loader, swa_model)
2025-07-17T07:05:40.4708410Z 
2025-07-17T07:05:40.4708590Z     You can also use custom averaging functions with the `avg_fn` or `multi_avg_fn` parameters.
2025-07-17T07:05:40.4709120Z     If no averaging function is provided, the default is to compute
2025-07-17T07:05:40.4709480Z     equally-weighted average of the weights (SWA).
2025-07-17T07:05:40.4709630Z 
2025-07-17T07:05:40.4709680Z     Example:
2025-07-17T07:05:40.4709830Z         >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:40.4710100Z         >>> # Compute exponential moving averages of the weights and buffers
2025-07-17T07:05:40.4710390Z         >>> ema_model = torch.optim.swa_utils.AveragedModel(model,
2025-07-17T07:05:40.4710690Z         >>>             torch.optim.swa_utils.get_ema_multi_avg_fn(0.9), use_buffers=True)
2025-07-17T07:05:40.4710890Z 
2025-07-17T07:05:40.4710940Z     .. note::
2025-07-17T07:05:40.4711150Z         When using SWA/EMA with models containing Batch Normalization you may
2025-07-17T07:05:40.4711470Z         need to update the activation statistics for Batch Normalization.
2025-07-17T07:05:40.4711810Z         This can be done either by using the :meth:`torch.optim.swa_utils.update_bn`
2025-07-17T07:05:40.4712150Z         or by setting :attr:`use_buffers` to `True`. The first approach updates the
2025-07-17T07:05:40.4712500Z         statistics in a post-training step by passing data through the model. The
2025-07-17T07:05:40.4712850Z         second does it during the parameter update phase by averaging all buffers.
2025-07-17T07:05:40.4713220Z         Empirical evidence has shown that updating the statistics in normalization
2025-07-17T07:05:40.4713570Z         layers increases accuracy, but you may wish to empirically test which
2025-07-17T07:05:40.4713870Z         approach yields the best results in your problem.
2025-07-17T07:05:40.4714030Z 
2025-07-17T07:05:40.4714080Z     .. note::
2025-07-17T07:05:40.4714300Z         :attr:`avg_fn` and `multi_avg_fn` are not saved in the :meth:`state_dict` of the model.
2025-07-17T07:05:40.4714520Z 
2025-07-17T07:05:40.4714560Z     .. note::
2025-07-17T07:05:40.4714760Z         When :meth:`update_parameters` is called for the first time (i.e.
2025-07-17T07:05:40.4715060Z         :attr:`n_averaged` is `0`) the parameters of `model` are copied
2025-07-17T07:05:40.4715370Z         to the parameters of :class:`AveragedModel`. For every subsequent
2025-07-17T07:05:40.4715680Z         call of :meth:`update_parameters` the function `avg_fn` is used
2025-07-17T07:05:40.4715910Z         to update the parameters.
2025-07-17T07:05:40.4716030Z 
2025-07-17T07:05:40.4716170Z     .. _Averaging Weights Leads to Wider Optima and Better Generalization:
2025-07-17T07:05:40.4716440Z         https://arxiv.org/abs/1803.05407
2025-07-17T07:05:40.4716710Z     .. _There Are Many Consistent Explanations of Unlabeled Data: Why You Should
2025-07-17T07:05:40.4716970Z         Average:
2025-07-17T07:05:40.4717110Z         https://arxiv.org/abs/1806.05594
2025-07-17T07:05:40.4717360Z     .. _SWALP: Stochastic Weight Averaging in Low-Precision Training:
2025-07-17T07:05:40.4717610Z         https://arxiv.org/abs/1904.11943
2025-07-17T07:05:40.4717870Z     .. _Stochastic Weight Averaging in Parallel: Large-Batch Training That
2025-07-17T07:05:40.4718130Z         Generalizes Well:
2025-07-17T07:05:40.4718360Z         https://arxiv.org/abs/2001.02312
2025-07-17T07:05:40.4718540Z     .. _Polyak averaging:
2025-07-17T07:05:40.4718740Z         https://paperswithcode.com/method/polyak-averaging
2025-07-17T07:05:40.4718980Z     
2025-07-17T07:05:40.4719190Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.5018330Z 
2025-07-17T07:05:40.5018830Z msg = Cannot scrape callname=SWALR in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/swa_utils.py line=375.
2025-07-17T07:05:40.5019420Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.5019790Z Anneals the learning rate in each parameter group to a fixed value.
2025-07-17T07:05:40.5019990Z 
2025-07-17T07:05:40.5020140Z     This learning rate scheduler is meant to be used with Stochastic Weight
2025-07-17T07:05:40.5020620Z     Averaging (SWA) method (see `torch.optim.swa_utils.AveragedModel`).
2025-07-17T07:05:40.5020860Z 
2025-07-17T07:05:40.5020910Z     Args:
2025-07-17T07:05:40.5021090Z         optimizer (torch.optim.Optimizer): wrapped optimizer
2025-07-17T07:05:40.5021390Z         swa_lrs (float or list): the learning rate value for all param groups
2025-07-17T07:05:40.5021670Z             together or separately for each group.
2025-07-17T07:05:40.5021940Z         annealing_epochs (int): number of epochs in the annealing phase
2025-07-17T07:05:40.5022190Z             (default: 10)
2025-07-17T07:05:40.5022420Z         annealing_strategy (str): "cos" or "linear"; specifies the annealing
2025-07-17T07:05:40.5022750Z             strategy: "cos" for cosine annealing, "linear" for linear annealing
2025-07-17T07:05:40.5023020Z             (default: "cos")
2025-07-17T07:05:40.5023240Z         last_epoch (int): the index of the last epoch (default: -1)
2025-07-17T07:05:40.5023410Z 
2025-07-17T07:05:40.5023520Z     The :class:`SWALR` scheduler can be used together with other
2025-07-17T07:05:40.5023830Z     schedulers to switch to a constant learning rate late in the training
2025-07-17T07:05:40.5024090Z     as in the example below.
2025-07-17T07:05:40.5024210Z 
2025-07-17T07:05:40.5024250Z     Example:
2025-07-17T07:05:40.5024400Z         >>> # xdoctest: +SKIP("Undefined variables")
2025-07-17T07:05:40.5024610Z         >>> loader, optimizer, model = ...
2025-07-17T07:05:40.5024810Z         >>> lr_lambda = lambda epoch: 0.9
2025-07-17T07:05:40.5025070Z         >>> scheduler = torch.optim.lr_scheduler.MultiplicativeLR(optimizer,
2025-07-17T07:05:40.5025330Z         >>>        lr_lambda=lr_lambda)
2025-07-17T07:05:40.5025560Z         >>> swa_scheduler = torch.optim.swa_utils.SWALR(optimizer,
2025-07-17T07:05:40.5025840Z         >>>        anneal_strategy="linear", anneal_epochs=20, swa_lr=0.05)
2025-07-17T07:05:40.5026070Z         >>> swa_start = 160
2025-07-17T07:05:40.5026230Z         >>> for i in range(300):
2025-07-17T07:05:40.5026410Z         >>>      for input, target in loader:
2025-07-17T07:05:40.5026610Z         >>>          optimizer.zero_grad()
2025-07-17T07:05:40.5026820Z         >>>          loss_fn(model(input), target).backward()
2025-07-17T07:05:40.5027030Z         >>>          optimizer.step()
2025-07-17T07:05:40.5027210Z         >>>      if i > swa_start:
2025-07-17T07:05:40.5027380Z         >>>          swa_scheduler.step()
2025-07-17T07:05:40.5027560Z         >>>      else:
2025-07-17T07:05:40.5027710Z         >>>          scheduler.step()
2025-07-17T07:05:40.5027830Z 
2025-07-17T07:05:40.5027960Z     .. _Averaging Weights Leads to Wider Optima and Better Generalization:
2025-07-17T07:05:40.5028220Z         https://arxiv.org/abs/1803.05407
2025-07-17T07:05:40.5028400Z     
2025-07-17T07:05:40.5028610Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.5028830Z 
2025-07-17T07:05:40.5029230Z msg = Cannot scrape callname=Optimizer.load_state_dict in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/optimizer.py line=867.
2025-07-17T07:05:40.5029940Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.5030230Z Load the optimizer state.
2025-07-17T07:05:40.5030330Z 
2025-07-17T07:05:40.5030450Z         Args:
2025-07-17T07:05:40.5030640Z             state_dict (dict): optimizer state. Should be an object returned
2025-07-17T07:05:40.5030900Z                 from a call to :meth:`state_dict`.
2025-07-17T07:05:40.5031040Z 
2025-07-17T07:05:40.5031100Z         .. warning::
2025-07-17T07:05:40.5031390Z             Make sure this method is called after initializing :class:`torch.optim.lr_scheduler.LRScheduler`,
2025-07-17T07:05:40.5031780Z             as calling it beforehand will overwrite the loaded learning rates.
2025-07-17T07:05:40.5031970Z 
2025-07-17T07:05:40.5032020Z         .. note::
2025-07-17T07:05:40.5032300Z             The names of the parameters (if they exist under the "param_names" key of each param group
2025-07-17T07:05:40.5032690Z             in :meth:`state_dict`) will not affect the loading process.
2025-07-17T07:05:40.5033080Z             To use the parameters' names for custom cases (such as when the parameters in the loaded state dict
2025-07-17T07:05:40.5033450Z             differ from those initialized in the optimizer),
2025-07-17T07:05:40.5033810Z             a custom ``register_load_state_dict_pre_hook`` should be implemented to adapt the loaded dict
2025-07-17T07:05:40.5034120Z             accordingly.
2025-07-17T07:05:40.5034400Z             If ``param_names`` exist in loaded state dict ``param_groups`` they will be saved and override
2025-07-17T07:05:40.5034850Z             the current names, if present, in the optimizer state. If they do not exist in loaded state dict,
2025-07-17T07:05:40.5035210Z             the optimizer ``param_names`` will remain unchanged.
2025-07-17T07:05:40.5035380Z 
2025-07-17T07:05:40.5035430Z         Example:
2025-07-17T07:05:40.5035570Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:40.5035770Z             >>> model = torch.nn.Linear(10, 10)
2025-07-17T07:05:40.5036020Z             >>> optim = torch.optim.SGD(model.parameters(), lr=3e-4)
2025-07-17T07:05:40.5036290Z             >>> scheduler1 = torch.optim.lr_scheduler.LinearLR(
2025-07-17T07:05:40.5036500Z             ...     optim,
2025-07-17T07:05:40.5036660Z             ...     start_factor=0.1,
2025-07-17T07:05:40.5036830Z             ...     end_factor=1,
2025-07-17T07:05:40.5036990Z             ...     total_iters=20,
2025-07-17T07:05:40.5037150Z             ... )
2025-07-17T07:05:40.5037350Z             >>> scheduler2 = torch.optim.lr_scheduler.CosineAnnealingLR(
2025-07-17T07:05:40.5037580Z             ...     optim,
2025-07-17T07:05:40.5037720Z             ...     T_max=80,
2025-07-17T07:05:40.5037880Z             ...     eta_min=3e-5,
2025-07-17T07:05:40.5038030Z             ... )
2025-07-17T07:05:40.5038200Z             >>> lr = torch.optim.lr_scheduler.SequentialLR(
2025-07-17T07:05:40.5038400Z             ...     optim,
2025-07-17T07:05:40.5038580Z             ...     schedulers=[scheduler1, scheduler2],
2025-07-17T07:05:40.5038780Z             ...     milestones=[20],
2025-07-17T07:05:40.5038940Z             ... )
2025-07-17T07:05:40.5039110Z             >>> lr.load_state_dict(torch.load("./save_seq.pt"))
2025-07-17T07:05:40.5039390Z             >>> # now load the optimizer checkpoint after loading the LRScheduler
2025-07-17T07:05:40.5039680Z             >>> optim.load_state_dict(torch.load("./save_optim.pt"))
2025-07-17T07:05:40.5039850Z 
2025-07-17T07:05:40.5039890Z         
2025-07-17T07:05:40.5040100Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.5040320Z 
2025-07-17T07:05:40.5040740Z msg = Cannot scrape callname=SelectiveCheckpointContext in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/checkpoint.py line=1218.
2025-07-17T07:05:40.5041400Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.5041620Z 
2025-07-17T07:05:40.5041810Z Context passed to policy function during selective checkpointing.
2025-07-17T07:05:40.5042010Z 
2025-07-17T07:05:40.5042150Z This class is used to pass relevant metadata to the policy function during
2025-07-17T07:05:40.5042530Z selective checkpointing. The metadata includes whether the current invocation
2025-07-17T07:05:40.5042850Z of the policy function is during recomputation or not.
2025-07-17T07:05:40.5043020Z 
2025-07-17T07:05:40.5043060Z Example:
2025-07-17T07:05:40.5043190Z     >>> # xdoctest: +SKIP(stub)
2025-07-17T07:05:40.5043340Z     >>>
2025-07-17T07:05:40.5043470Z     >>> def policy_fn(ctx, op, *args, **kwargs):
2025-07-17T07:05:40.5043680Z     >>>    print(ctx.is_recompute)
2025-07-17T07:05:40.5043840Z     >>>
2025-07-17T07:05:40.5044060Z     >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn)
2025-07-17T07:05:40.5044330Z     >>>
2025-07-17T07:05:40.5044530Z     >>> out = torch.utils.checkpoint.checkpoint(
2025-07-17T07:05:40.5044760Z     >>>     fn, x, y,
2025-07-17T07:05:40.5044910Z     >>>     use_reentrant=False,
2025-07-17T07:05:40.5045080Z     >>>     context_fn=context_fn,
2025-07-17T07:05:40.5045240Z     >>> )
2025-07-17T07:05:40.5045300Z 
2025-07-17T07:05:40.5045460Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.5045670Z 
2025-07-17T07:05:40.5046110Z msg = Cannot scrape callname=create_selective_checkpoint_contexts in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/checkpoint.py line=1358.
2025-07-17T07:05:40.5046770Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.5046990Z 
2025-07-17T07:05:40.5047130Z Helper to avoid recomputing certain ops during activation checkpointing.
2025-07-17T07:05:40.5047340Z 
2025-07-17T07:05:40.5047470Z Use this with `torch.utils.checkpoint.checkpoint` to control which
2025-07-17T07:05:40.5047760Z operations are recomputed during the backward pass.
2025-07-17T07:05:40.5047920Z 
2025-07-17T07:05:40.5047970Z Args:
2025-07-17T07:05:40.5048100Z     policy_fn_or_list (Callable or List):
2025-07-17T07:05:40.5048330Z       - If a policy function is provided, it should accept a
2025-07-17T07:05:40.5048640Z         :class:`SelectiveCheckpointContext`, the :class:`OpOverload`, args and
2025-07-17T07:05:40.5048980Z         kwargs to the op, and return a :class:`CheckpointPolicy` enum value
2025-07-17T07:05:40.5049310Z         indicating whether the execution of the op should be recomputed or not.
2025-07-17T07:05:40.5049650Z       - If a list of operations is provided, it is equivalent to a policy
2025-07-17T07:05:40.5049960Z         returning `CheckpointPolicy.MUST_SAVE` for the specified
2025-07-17T07:05:40.5050270Z         operations and `CheckpointPolicy.PREFER_RECOMPUTE` for all other
2025-07-17T07:05:40.5050510Z         operations.
2025-07-17T07:05:40.5050720Z     allow_cache_entry_mutation (bool, optional): By default, an error is
2025-07-17T07:05:40.5051050Z         raised if any tensors cached by selective activation checkpoint are
2025-07-17T07:05:40.5051370Z         mutated in order to ensure correctness. If set to `True`, this check
2025-07-17T07:05:40.5051620Z         is disabled.
2025-07-17T07:05:40.5051750Z Returns:
2025-07-17T07:05:40.5051870Z     A tuple of two context managers.
2025-07-17T07:05:40.5052000Z 
2025-07-17T07:05:40.5052040Z Example:
2025-07-17T07:05:40.5052160Z     >>> # xdoctest: +REQUIRES(LINUX)
2025-07-17T07:05:40.5052340Z     >>> import functools
2025-07-17T07:05:40.5052480Z     >>>
2025-07-17T07:05:40.5052610Z     >>> x = torch.rand(10, 10, requires_grad=True)
2025-07-17T07:05:40.5052820Z     >>> y = torch.rand(10, 10, requires_grad=True)
2025-07-17T07:05:40.5053000Z     >>>
2025-07-17T07:05:40.5053110Z     >>> ops_to_save = [
2025-07-17T07:05:40.5053270Z     >>>    torch.ops.aten.mm.default,
2025-07-17T07:05:40.5053440Z     >>> ]
2025-07-17T07:05:40.5053550Z     >>>
2025-07-17T07:05:40.5053680Z     >>> def policy_fn(ctx, op, *args, **kwargs):
2025-07-17T07:05:40.5053920Z     >>>    if op in ops_to_save:
2025-07-17T07:05:40.5054120Z     >>>        return CheckpointPolicy.MUST_SAVE
2025-07-17T07:05:40.5054300Z     >>>    else:
2025-07-17T07:05:40.5054520Z     >>>        return CheckpointPolicy.PREFER_RECOMPUTE
2025-07-17T07:05:40.5054710Z     >>>
2025-07-17T07:05:40.5054940Z     >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn)
2025-07-17T07:05:40.5055210Z     >>>
2025-07-17T07:05:40.5055320Z     >>> # or equivalently
2025-07-17T07:05:40.5055580Z     >>> context_fn = functools.partial(create_selective_checkpoint_contexts, ops_to_save)
2025-07-17T07:05:40.5055850Z     >>>
2025-07-17T07:05:40.5055960Z     >>> def fn(x, y):
2025-07-17T07:05:40.5056160Z     >>>     return torch.sigmoid(torch.matmul(torch.matmul(x, y), y)) * y
2025-07-17T07:05:40.5062670Z     >>>
2025-07-17T07:05:40.5062840Z     >>> out = torch.utils.checkpoint.checkpoint(
2025-07-17T07:05:40.5063120Z     >>>     fn, x, y,
2025-07-17T07:05:40.5063290Z     >>>     use_reentrant=False,
2025-07-17T07:05:40.5063470Z     >>>     context_fn=context_fn,
2025-07-17T07:05:40.5063630Z     >>> )
2025-07-17T07:05:40.5063690Z 
2025-07-17T07:05:40.5063840Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.5064060Z 
2025-07-17T07:05:40.5064490Z msg = Cannot scrape callname=ThroughputBenchmark in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/throughput_benchmark.py line=61.
2025-07-17T07:05:40.5065130Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.5065350Z 
2025-07-17T07:05:40.5065530Z This class is a wrapper around a c++ component throughput_benchmark::ThroughputBenchmark.
2025-07-17T07:05:40.5065770Z 
2025-07-17T07:05:40.5065950Z This wrapper on the throughput_benchmark::ThroughputBenchmark component is responsible
2025-07-17T07:05:40.5066330Z for executing a PyTorch module (nn.Module or ScriptModule) under an inference
2025-07-17T07:05:40.5066690Z server like load. It can emulate multiple calling threads to a single module
2025-07-17T07:05:40.5067040Z provided. In the future we plan to enhance this component to support inter and
2025-07-17T07:05:40.5067400Z intra-op parallelism as well as multiple models running in a single process.
2025-07-17T07:05:40.5067610Z 
2025-07-17T07:05:40.5067760Z Please note that even though nn.Module is supported, it might incur an overhead
2025-07-17T07:05:40.5068110Z from the need to hold GIL every time we execute Python code or pass around
2025-07-17T07:05:40.5068450Z inputs as Python objects. As soon as you have a ScriptModule version of your
2025-07-17T07:05:40.5068800Z model for inference deployment it is better to switch to using it in this
2025-07-17T07:05:40.5069050Z benchmark.
2025-07-17T07:05:40.5069120Z 
2025-07-17T07:05:40.5069160Z Example::
2025-07-17T07:05:40.5069230Z 
2025-07-17T07:05:40.5069300Z     >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:40.5069510Z     >>> from torch.utils import ThroughputBenchmark
2025-07-17T07:05:40.5069740Z     >>> bench = ThroughputBenchmark(my_module)
2025-07-17T07:05:40.5069980Z     >>> # Pre-populate benchmark's data set with the inputs
2025-07-17T07:05:40.5070200Z     >>> for input in inputs:
2025-07-17T07:05:40.5070440Z     ...     # Both args and kwargs work, same as any PyTorch Module / ScriptModule
2025-07-17T07:05:40.5070710Z     ...     bench.add_input(input[0], x2=input[1])
2025-07-17T07:05:40.5070970Z     >>> # Inputs supplied above are randomly used during the execution
2025-07-17T07:05:40.5071210Z     >>> stats = bench.benchmark(
2025-07-17T07:05:40.5071390Z     ...     num_calling_threads=4,
2025-07-17T07:05:40.5071560Z     ...     num_warmup_iters = 100,
2025-07-17T07:05:40.5071740Z     ...     num_iters = 1000,
2025-07-17T07:05:40.5071890Z     ... )
2025-07-17T07:05:40.5072060Z     >>> print("Avg latency (ms): {}".format(stats.latency_avg_ms))
2025-07-17T07:05:40.5072400Z     >>> print("Number of iterations: {}".format(stats.num_iters))
2025-07-17T07:05:40.5072580Z 
2025-07-17T07:05:40.5072740Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.5072990Z 
2025-07-17T07:05:40.5073380Z msg = Cannot scrape callname=register_pytree_node in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py line=134.
2025-07-17T07:05:40.5074010Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.5074310Z Register a container-like type as pytree node.
2025-07-17T07:05:40.5074460Z 
2025-07-17T07:05:40.5074510Z     Args:
2025-07-17T07:05:40.5074690Z         cls (type): A Python type to treat as an internal pytree node.
2025-07-17T07:05:40.5075040Z         flatten_fn (callable): A function to be used during flattening, taking an instance of
2025-07-17T07:05:40.5075440Z             ``cls`` and returning a pair, with (1) an iterable for the children to be flattened
2025-07-17T07:05:40.5075860Z             recursively, and (2) some hashable auxiliary data to be stored in the treespec and to be
2025-07-17T07:05:40.5076160Z             passed to the ``unflatten_fn``.
2025-07-17T07:05:40.5076460Z         unflatten_fn (callable): A function taking two arguments: the auxiliary data that was
2025-07-17T07:05:40.5076850Z             returned by ``flatten_fn`` and stored in the treespec, and the unflattened children.
2025-07-17T07:05:40.5077170Z             The function should return an instance of ``cls``.
2025-07-17T07:05:40.5077490Z         serialized_type_name (str, optional): A keyword argument used to specify the fully
2025-07-17T07:05:40.5077830Z             qualified name used when serializing the tree spec.
2025-07-17T07:05:40.5078170Z         to_dumpable_context (callable, optional): An optional keyword argument to custom specify how
2025-07-17T07:05:40.5078580Z             to convert the context of the pytree to a custom json dumpable representation. This is
2025-07-17T07:05:40.5078990Z             used for json serialization, which is being used in :mod:`torch.export` right now.
2025-07-17T07:05:40.5079400Z         from_dumpable_context (callable, optional): An optional keyword argument to custom specify
2025-07-17T07:05:40.5079810Z             how to convert the custom json dumpable representation of the context back to the
2025-07-17T07:05:40.5080180Z             original context. This is used for json deserialization, which is being used in
2025-07-17T07:05:40.5080470Z             :mod:`torch.export` right now.
2025-07-17T07:05:40.5080610Z 
2025-07-17T07:05:40.5080660Z     Example::
2025-07-17T07:05:40.5080730Z 
2025-07-17T07:05:40.5080790Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:40.5080980Z         >>> # Registry a Python type with lambda functions
2025-07-17T07:05:40.5081190Z         >>> register_pytree_node(
2025-07-17T07:05:40.5081350Z         ...     set,
2025-07-17T07:05:40.5081510Z         ...     lambda s: (sorted(s), None, None),
2025-07-17T07:05:40.5081720Z         ...     lambda children, _: set(children),
2025-07-17T07:05:40.5081910Z         ... )
2025-07-17T07:05:40.5082020Z     
2025-07-17T07:05:40.5082230Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.5082450Z 
2025-07-17T07:05:40.5082840Z msg = Cannot scrape callname=CppExtension in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1147.
2025-07-17T07:05:40.5083440Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.5083860Z 
2025-07-17T07:05:40.5083940Z Create a :class:`setuptools.Extension` for C++.
2025-07-17T07:05:40.5084090Z 
2025-07-17T07:05:40.5084240Z Convenience method that creates a :class:`setuptools.Extension` with the
2025-07-17T07:05:40.5084580Z bare minimum (but often sufficient) arguments to build a C++ extension.
2025-07-17T07:05:40.5084780Z 
2025-07-17T07:05:40.5084900Z All arguments are forwarded to the :class:`setuptools.Extension`
2025-07-17T07:05:40.5085200Z constructor. Full list arguments can be found at
2025-07-17T07:05:40.5085550Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference
2025-07-17T07:05:40.5085850Z 
2025-07-17T07:05:40.5085900Z .. warning::
2025-07-17T07:05:40.5086120Z     The PyTorch python API (as provided in libtorch_python) cannot be built
2025-07-17T07:05:40.5086450Z     with the flag ``py_limited_api=True``.  When this flag is passed, it is
2025-07-17T07:05:40.5086770Z     the user's responsibility in their library to not use APIs from
2025-07-17T07:05:40.5087090Z     libtorch_python (in particular pytorch/python bindings) and to only use
2025-07-17T07:05:40.5087640Z     APIs from libtorch (aten objects, operators and the dispatcher). For
2025-07-17T07:05:40.5087970Z     example, to give access to custom ops from python, the library should
2025-07-17T07:05:40.5088250Z     register the ops through the dispatcher.
2025-07-17T07:05:40.5088490Z 
2025-07-17T07:05:40.5088640Z     Contrary to CPython setuptools, who does not define -DPy_LIMITED_API
2025-07-17T07:05:40.5088960Z     as a compile flag when py_limited_api is specified as an option for
2025-07-17T07:05:40.5089280Z     the "bdist_wheel" command in ``setup``, PyTorch does! We will specify
2025-07-17T07:05:40.5089610Z     -DPy_LIMITED_API=min_supported_cpython to best enforce consistency,
2025-07-17T07:05:40.5089930Z     safety, and sanity in order to encourage best practices. To target a
2025-07-17T07:05:40.5090250Z     different version, set min_supported_cpython to the hexcode of the
2025-07-17T07:05:40.5090500Z     CPython version of choice.
2025-07-17T07:05:40.5090610Z 
2025-07-17T07:05:40.5090660Z Example:
2025-07-17T07:05:40.5090780Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:40.5090960Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-07-17T07:05:40.5091180Z     >>> from setuptools import setup
2025-07-17T07:05:40.5091430Z     >>> from torch.utils.cpp_extension import BuildExtension, CppExtension
2025-07-17T07:05:40.5091680Z     >>> setup(
2025-07-17T07:05:40.5091810Z     ...     name='extension',
2025-07-17T07:05:40.5091960Z     ...     ext_modules=[
2025-07-17T07:05:40.5092120Z     ...         CppExtension(
2025-07-17T07:05:40.5092280Z     ...             name='extension',
2025-07-17T07:05:40.5092470Z     ...             sources=['extension.cpp'],
2025-07-17T07:05:40.5092680Z     ...             extra_compile_args=['-g'],
2025-07-17T07:05:40.5092900Z     ...             extra_link_args=['-Wl,--no-as-needed', '-lm'])
2025-07-17T07:05:40.5093110Z     ...     ],
2025-07-17T07:05:40.5093230Z     ...     cmdclass={
2025-07-17T07:05:40.5093380Z     ...         'build_ext': BuildExtension
2025-07-17T07:05:40.5093550Z     ...     })
2025-07-17T07:05:40.5093630Z 
2025-07-17T07:05:40.5093780Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.5093990Z 
2025-07-17T07:05:40.5094380Z msg = Cannot scrape callname=CUDAExtension in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1217.
2025-07-17T07:05:40.5094990Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.5095210Z 
2025-07-17T07:05:40.5095300Z Create a :class:`setuptools.Extension` for CUDA/C++.
2025-07-17T07:05:40.5095460Z 
2025-07-17T07:05:40.5095600Z Convenience method that creates a :class:`setuptools.Extension` with the
2025-07-17T07:05:40.5095930Z bare minimum (but often sufficient) arguments to build a CUDA/C++
2025-07-17T07:05:40.5096250Z extension. This includes the CUDA include path, library path and runtime
2025-07-17T07:05:40.5096490Z library.
2025-07-17T07:05:40.5096560Z 
2025-07-17T07:05:40.5096680Z All arguments are forwarded to the :class:`setuptools.Extension`
2025-07-17T07:05:40.5096950Z constructor. Full list arguments can be found at
2025-07-17T07:05:40.5097290Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference
2025-07-17T07:05:40.5097550Z 
2025-07-17T07:05:40.5097620Z .. warning::
2025-07-17T07:05:40.5097830Z     The PyTorch python API (as provided in libtorch_python) cannot be built
2025-07-17T07:05:40.5098160Z     with the flag ``py_limited_api=True``.  When this flag is passed, it is
2025-07-17T07:05:40.5098490Z     the user's responsibility in their library to not use APIs from
2025-07-17T07:05:40.5098810Z     libtorch_python (in particular pytorch/python bindings) and to only use
2025-07-17T07:05:40.5099140Z     APIs from libtorch (aten objects, operators and the dispatcher). For
2025-07-17T07:05:40.5099460Z     example, to give access to custom ops from python, the library should
2025-07-17T07:05:40.5099730Z     register the ops through the dispatcher.
2025-07-17T07:05:40.5099870Z 
2025-07-17T07:05:40.5100000Z     Contrary to CPython setuptools, who does not define -DPy_LIMITED_API
2025-07-17T07:05:40.5100370Z     as a compile flag when py_limited_api is specified as an option for
2025-07-17T07:05:40.5100750Z     the "bdist_wheel" command in ``setup``, PyTorch does! We will specify
2025-07-17T07:05:40.5101070Z     -DPy_LIMITED_API=min_supported_cpython to best enforce consistency,
2025-07-17T07:05:40.5101390Z     safety, and sanity in order to encourage best practices. To target a
2025-07-17T07:05:40.5101710Z     different version, set min_supported_cpython to the hexcode of the
2025-07-17T07:05:40.5101960Z     CPython version of choice.
2025-07-17T07:05:40.5102070Z 
2025-07-17T07:05:40.5102120Z Example:
2025-07-17T07:05:40.5102230Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:40.5102420Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-07-17T07:05:40.5102630Z     >>> from setuptools import setup
2025-07-17T07:05:40.5102890Z     >>> from torch.utils.cpp_extension import BuildExtension, CUDAExtension
2025-07-17T07:05:40.5103130Z     >>> setup(
2025-07-17T07:05:40.5103260Z     ...     name='cuda_extension',
2025-07-17T07:05:40.5103430Z     ...     ext_modules=[
2025-07-17T07:05:40.5103580Z     ...         CUDAExtension(
2025-07-17T07:05:40.5103760Z     ...                 name='cuda_extension',
2025-07-17T07:05:40.5104020Z     ...                 sources=['extension.cpp', 'extension_kernel.cu'],
2025-07-17T07:05:40.5104270Z     ...                 extra_compile_args={'cxx': ['-g'],
2025-07-17T07:05:40.5104490Z     ...                                     'nvcc': ['-O2']},
2025-07-17T07:05:40.5104720Z     ...                 extra_link_args=['-Wl,--no-as-needed', '-lcuda'])
2025-07-17T07:05:40.5104920Z     ...     ],
2025-07-17T07:05:40.5105040Z     ...     cmdclass={
2025-07-17T07:05:40.5105190Z     ...         'build_ext': BuildExtension
2025-07-17T07:05:40.5105360Z     ...     })
2025-07-17T07:05:40.5105440Z 
2025-07-17T07:05:40.5105490Z Compute capabilities:
2025-07-17T07:05:40.5105580Z 
2025-07-17T07:05:40.5105760Z By default the extension will be compiled to run on all archs of the cards visible during the
2025-07-17T07:05:40.5106180Z building process of the extension, plus PTX. If down the road a new card is installed the
2025-07-17T07:05:40.5106590Z extension may need to be recompiled. If a visible card has a compute capability (CC) that's
2025-07-17T07:05:40.5107010Z newer than the newest version for which your nvcc can build fully-compiled binaries, PyTorch
2025-07-17T07:05:40.5107430Z will make nvcc fall back to building kernels with the newest version of PTX your nvcc does
2025-07-17T07:05:40.5107730Z support (see below for details on PTX).
2025-07-17T07:05:40.5107860Z 
2025-07-17T07:05:40.5108050Z You can override the default behavior using `TORCH_CUDA_ARCH_LIST` to explicitly specify which
2025-07-17T07:05:40.5108360Z CCs you want the extension to support:
2025-07-17T07:05:40.5108490Z 
2025-07-17T07:05:40.5108600Z ``TORCH_CUDA_ARCH_LIST="6.1 8.6" python build_my_extension.py``
2025-07-17T07:05:40.5108920Z ``TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" python build_my_extension.py``
2025-07-17T07:05:40.5109140Z 
2025-07-17T07:05:40.5109330Z The +PTX option causes extension kernel binaries to include PTX instructions for the specified
2025-07-17T07:05:40.5109810Z CC. PTX is an intermediate representation that allows kernels to runtime-compile for any CC >=
2025-07-17T07:05:40.5110240Z the specified CC (for example, 8.6+PTX generates PTX that can runtime-compile for any GPU with
2025-07-17T07:05:40.5110680Z CC >= 8.6). This improves your binary's forward compatibility. However, relying on older PTX to
2025-07-17T07:05:40.5111110Z provide forward compat by runtime-compiling for newer CCs can modestly reduce performance on
2025-07-17T07:05:40.5111530Z those newer CCs. If you know exact CC(s) of the GPUs you want to target, you're always better
2025-07-17T07:05:40.5111950Z off specifying them individually. For example, if you want your extension to run on 8.0 and 8.6,
2025-07-17T07:05:40.5112380Z "8.0+PTX" would work functionally because it includes PTX that can runtime-compile for 8.6, but
2025-07-17T07:05:40.5112680Z "8.0 8.6" would be better.
2025-07-17T07:05:40.5112800Z 
2025-07-17T07:05:40.5113010Z Note that while it's possible to include all supported archs, the more archs get included the
2025-07-17T07:05:40.5113430Z slower the building process will be, as it will build a separate kernel image for each arch.
2025-07-17T07:05:40.5113660Z 
2025-07-17T07:05:40.5113860Z Note that CUDA-11.5 nvcc will hit internal compiler error while parsing torch/extension.h on Windows.
2025-07-17T07:05:40.5114250Z To workaround the issue, move python binding logic to pure C++ file.
2025-07-17T07:05:40.5114440Z 
2025-07-17T07:05:40.5114490Z Example use:
2025-07-17T07:05:40.5114610Z     #include <ATen/ATen.h>
2025-07-17T07:05:40.5114800Z     at::Tensor SigmoidAlphaBlendForwardCuda(....)
2025-07-17T07:05:40.5114950Z 
2025-07-17T07:05:40.5115000Z Instead of:
2025-07-17T07:05:40.5115120Z     #include <torch/extension.h>
2025-07-17T07:05:40.5115330Z     torch::Tensor SigmoidAlphaBlendForwardCuda(...)
2025-07-17T07:05:40.5115490Z 
2025-07-17T07:05:40.5115650Z Currently open issue for nvcc bug: https://github.com/pytorch/pytorch/issues/69460
2025-07-17T07:05:40.5116180Z Complete workaround code example: https://github.com/facebookresearch/pytorch3d/commit/cb170ac024a949f1f9614ffe6af1c38d972f7d48
2025-07-17T07:05:40.5116530Z 
2025-07-17T07:05:40.5116590Z Relocatable device code linking:
2025-07-17T07:05:40.5116710Z 
2025-07-17T07:05:40.5116880Z If you want to reference device symbols across compilation units (across object files),
2025-07-17T07:05:40.5117270Z the object files need to be built with `relocatable device code` (-rdc=true or -dc).
2025-07-17T07:05:40.5117700Z An exception to this rule is "dynamic parallelism" (nested kernel launches)  which is not used a lot anymore.
2025-07-17T07:05:40.5118180Z `Relocatable device code` is less optimized so it needs to be used only on object files that need it.
2025-07-17T07:05:40.5118690Z Using `-dlto` (Device Link Time Optimization) at the device code compilation step and `dlink` step
2025-07-17T07:05:40.5119050Z helps reduce the protentional perf degradation of `-rdc`.
2025-07-17T07:05:40.5119320Z Note that it needs to be used at both steps to be useful.
2025-07-17T07:05:40.5119480Z 
2025-07-17T07:05:40.5119700Z If you have `rdc` objects you need to have an extra `-dlink` (device linking) step before the CPU symbol linking step.
2025-07-17T07:05:40.5120080Z There is also a case where `-dlink` is used without `-rdc`:
2025-07-17T07:05:40.5120400Z when an extension is linked against a static lib containing rdc-compiled objects
2025-07-17T07:05:40.5120740Z like the [NVSHMEM library](https://developer.nvidia.com/nvshmem).
2025-07-17T07:05:40.5120940Z 
2025-07-17T07:05:40.5121060Z Note: Ninja is required to build a CUDA Extension with RDC linking.
2025-07-17T07:05:40.5121240Z 
2025-07-17T07:05:40.5121290Z Example:
2025-07-17T07:05:40.5121400Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:40.5121590Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-07-17T07:05:40.5121790Z     >>> CUDAExtension(
2025-07-17T07:05:40.5121940Z     ...        name='cuda_extension',
2025-07-17T07:05:40.5122210Z     ...        sources=['extension.cpp', 'extension_kernel.cu'],
2025-07-17T07:05:40.5122430Z     ...        dlink=True,
2025-07-17T07:05:40.5122590Z     ...        dlink_libraries=["dlink_lib"],
2025-07-17T07:05:40.5122800Z     ...        extra_compile_args={'cxx': ['-g'],
2025-07-17T07:05:40.5123030Z     ...                            'nvcc': ['-O2', '-rdc=true']})
2025-07-17T07:05:40.5123180Z 
2025-07-17T07:05:40.5123330Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.6895850Z 
2025-07-17T07:05:40.6896510Z msg = Cannot scrape callname=SyclExtension in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1408.
2025-07-17T07:05:40.6897180Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.6897420Z 
2025-07-17T07:05:40.6897530Z Creates a :class:`setuptools.Extension` for SYCL/C++.
2025-07-17T07:05:40.6897920Z 
2025-07-17T07:05:40.6898120Z Convenience method that creates a :class:`setuptools.Extension` with the
2025-07-17T07:05:40.6898480Z bare minimum (but often sufficient) arguments to build a SYCL/C++
2025-07-17T07:05:40.6898720Z extension.
2025-07-17T07:05:40.6898790Z 
2025-07-17T07:05:40.6898930Z All arguments are forwarded to the :class:`setuptools.Extension`
2025-07-17T07:05:40.6899170Z constructor.
2025-07-17T07:05:40.6899250Z 
2025-07-17T07:05:40.6899310Z .. warning::
2025-07-17T07:05:40.6899530Z     The PyTorch python API (as provided in libtorch_python) cannot be built
2025-07-17T07:05:40.6899870Z     with the flag ``py_limited_api=True``.  When this flag is passed, it is
2025-07-17T07:05:40.6900190Z     the user's responsibility in their library to not use APIs from
2025-07-17T07:05:40.6900520Z     libtorch_python (in particular pytorch/python bindings) and to only use
2025-07-17T07:05:40.6900860Z     APIs from libtorch (aten objects, operators and the dispatcher). For
2025-07-17T07:05:40.6901200Z     example, to give access to custom ops from python, the library should
2025-07-17T07:05:40.6901470Z     register the ops through the dispatcher.
2025-07-17T07:05:40.6901610Z 
2025-07-17T07:05:40.6901740Z     Contrary to CPython setuptools, who does not define -DPy_LIMITED_API
2025-07-17T07:05:40.6902070Z     as a compile flag when py_limited_api is specified as an option for
2025-07-17T07:05:40.6902380Z     the "bdist_wheel" command in ``setup``, PyTorch does! We will specify
2025-07-17T07:05:40.6902710Z     -DPy_LIMITED_API=min_supported_cpython to best enforce consistency,
2025-07-17T07:05:40.6903040Z     safety, and sanity in order to encourage best practices. To target a
2025-07-17T07:05:40.6903360Z     different version, set min_supported_cpython to the hexcode of the
2025-07-17T07:05:40.6903610Z     CPython version of choice.
2025-07-17T07:05:40.6903730Z 
2025-07-17T07:05:40.6903770Z Example:
2025-07-17T07:05:40.6903890Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:40.6904090Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-07-17T07:05:40.6904380Z     >>> from torch.utils.cpp_extension import BuildExtension, SyclExtension
2025-07-17T07:05:40.6904630Z     >>> setup(
2025-07-17T07:05:40.6904770Z     ...     name='xpu_extension',
2025-07-17T07:05:40.6904940Z     ...     ext_modules=[
2025-07-17T07:05:40.6905140Z     ...     SyclExtension(
2025-07-17T07:05:40.6905310Z     ...                 name='xpu_extension',
2025-07-17T07:05:40.6905550Z     ...                 sources=['extension.cpp', 'extension_kernel.cpp'],
2025-07-17T07:05:40.6905830Z     ...                 extra_compile_args={'cxx': ['-g', '-std=c++20', '-fPIC']})
2025-07-17T07:05:40.6906060Z     ...     ],
2025-07-17T07:05:40.6906190Z     ...     cmdclass={
2025-07-17T07:05:40.6906340Z     ...         'build_ext': BuildExtension
2025-07-17T07:05:40.6906510Z     ...     })
2025-07-17T07:05:40.6906580Z 
2025-07-17T07:05:40.6906770Z By default the extension will be compiled to run on all archs of the cards visible during the
2025-07-17T07:05:40.6907260Z building process of the extension. If down the road a new card is installed the
2025-07-17T07:05:40.6907640Z extension may need to be recompiled. You can override the default behavior using
2025-07-17T07:05:40.6908040Z `TORCH_XPU_ARCH_LIST` to explicitly specify which device architectures you want the extension
2025-07-17T07:05:40.6908430Z to support:
2025-07-17T07:05:40.6908500Z 
2025-07-17T07:05:40.6908630Z ``TORCH_XPU_ARCH_LIST="pvc,xe-lpg" python build_my_extension.py``
2025-07-17T07:05:40.6908820Z 
2025-07-17T07:05:40.6909000Z Note that while it's possible to include all supported archs, the more archs get included the
2025-07-17T07:05:40.6909420Z slower the building process will be, as it will build a separate kernel image for each arch.
2025-07-17T07:05:40.6909660Z 
2025-07-17T07:05:40.6909740Z Note: Ninja is required to build SyclExtension.
2025-07-17T07:05:40.6909900Z 
2025-07-17T07:05:40.6910100Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.6910350Z 
2025-07-17T07:05:40.6910720Z msg = Cannot scrape callname=load in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1585.
2025-07-17T07:05:40.6911310Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.6911530Z 
2025-07-17T07:05:40.6911610Z Load a PyTorch C++ extension just-in-time (JIT).
2025-07-17T07:05:40.6918530Z 
2025-07-17T07:05:40.6918680Z To load an extension, a Ninja build file is emitted, which is used to
2025-07-17T07:05:40.6919000Z compile the given sources into a dynamic library. This library is
2025-07-17T07:05:40.6919320Z subsequently loaded into the current Python process as a module and
2025-07-17T07:05:40.6919590Z returned from this function, ready for use.
2025-07-17T07:05:40.6919730Z 
2025-07-17T07:05:40.6919860Z By default, the directory to which the build file is emitted and the
2025-07-17T07:05:40.6920190Z resulting library compiled to is ``<tmp>/torch_extensions/<name>``, where
2025-07-17T07:05:40.6920530Z ``<tmp>`` is the temporary folder on the current platform and ``<name>``
2025-07-17T07:05:40.6920850Z the name of the extension. This location can be overridden in two ways.
2025-07-17T07:05:40.6921170Z First, if the ``TORCH_EXTENSIONS_DIR`` environment variable is set, it
2025-07-17T07:05:40.6921500Z replaces ``<tmp>/torch_extensions`` and all extensions will be compiled
2025-07-17T07:05:40.6921840Z into subfolders of this directory. Second, if the ``build_directory``
2025-07-17T07:05:40.6922170Z argument to this function is supplied, it overrides the entire path, i.e.
2025-07-17T07:05:40.6922470Z the library will be compiled into that folder directly.
2025-07-17T07:05:40.6922630Z 
2025-07-17T07:05:40.6922760Z To compile the sources, the default system compiler (``c++``) is used,
2025-07-17T07:05:40.6923100Z which can be overridden by setting the ``CXX`` environment variable. To pass
2025-07-17T07:05:40.6923460Z additional arguments to the compilation process, ``extra_cflags`` or
2025-07-17T07:05:40.6923800Z ``extra_ldflags`` can be provided. For example, to compile your extension
2025-07-17T07:05:40.6924140Z with optimizations, pass ``extra_cflags=['-O3']``. You can also use
2025-07-17T07:05:40.6924430Z ``extra_cflags`` to pass further include directories.
2025-07-17T07:05:40.6924590Z 
2025-07-17T07:05:40.6924740Z CUDA support with mixed compilation is provided. Simply pass CUDA source
2025-07-17T07:05:40.6925050Z files (``.cu`` or ``.cuh``) along with other sources. Such files will be
2025-07-17T07:05:40.6925370Z detected and compiled with nvcc rather than the C++ compiler. This includes
2025-07-17T07:05:40.6925720Z passing the CUDA lib64 directory as a library directory, and linking
2025-07-17T07:05:40.6926000Z ``cudart``. You can pass additional flags to nvcc via
2025-07-17T07:05:40.6926280Z ``extra_cuda_cflags``, just like with ``extra_cflags`` for C++. Various
2025-07-17T07:05:40.6926600Z heuristics for finding the CUDA install directory are used, which usually
2025-07-17T07:05:40.6927030Z work fine. If not, setting the ``CUDA_HOME`` environment variable is the
2025-07-17T07:05:40.6927270Z safest option.
2025-07-17T07:05:40.6927350Z 
2025-07-17T07:05:40.6927490Z SYCL support with mixed compilation is provided. Simply pass SYCL source
2025-07-17T07:05:40.6927850Z files (``.sycl``) along with other sources. Such files will be detected
2025-07-17T07:05:40.6928170Z and compiled with SYCL compiler (such as Intel DPC++ Compiler) rather
2025-07-17T07:05:40.6928490Z than the C++ compiler. You can pass additional flags to SYCL compiler
2025-07-17T07:05:40.6928800Z via ``extra_sycl_cflags``, just like with ``extra_cflags`` for C++.
2025-07-17T07:05:40.6929110Z SYCL compiler is expected to be found via system PATH environment
2025-07-17T07:05:40.6929340Z variable.
2025-07-17T07:05:40.6929410Z 
2025-07-17T07:05:40.6929460Z Args:
2025-07-17T07:05:40.6929650Z     name: The name of the extension to build. This MUST be the same as the
2025-07-17T07:05:40.6929950Z         name of the pybind11 module!
2025-07-17T07:05:40.6930240Z     sources: A list of relative or absolute paths to C++ source files.
2025-07-17T07:05:40.6930560Z     extra_cflags: optional list of compiler flags to forward to the build.
2025-07-17T07:05:40.6930890Z     extra_cuda_cflags: optional list of compiler flags to forward to nvcc
2025-07-17T07:05:40.6931150Z         when building CUDA sources.
2025-07-17T07:05:40.6931410Z     extra_sycl_cflags: optional list of compiler flags to forward to SYCL
2025-07-17T07:05:40.6931680Z         compiler when building SYCL sources.
2025-07-17T07:05:40.6931950Z     extra_ldflags: optional list of linker flags to forward to the build.
2025-07-17T07:05:40.6932280Z     extra_include_paths: optional list of include directories to forward
2025-07-17T07:05:40.6932520Z         to the build.
2025-07-17T07:05:40.6932720Z     build_directory: optional path to use as build workspace.
2025-07-17T07:05:40.6933000Z     verbose: If ``True``, turns on verbose logging of load steps.
2025-07-17T07:05:40.6933310Z     with_cuda: Determines whether CUDA headers and libraries are added to
2025-07-17T07:05:40.6933600Z         the build. If set to ``None`` (default), this value is
2025-07-17T07:05:40.6933890Z         automatically determined based on the existence of ``.cu`` or
2025-07-17T07:05:40.6934190Z         ``.cuh`` in ``sources``. Set it to `True`` to force CUDA headers
2025-07-17T07:05:40.6934420Z         and libraries to be included.
2025-07-17T07:05:40.6934680Z     with_sycl: Determines whether SYCL headers and libraries are added to
2025-07-17T07:05:40.6934970Z         the build. If set to ``None`` (default), this value is
2025-07-17T07:05:40.6935260Z         automatically determined based on the existence of ``.sycl`` in
2025-07-17T07:05:40.6935550Z         ``sources``. Set it to `True`` to force SYCL headers and
2025-07-17T07:05:40.6935770Z         libraries to be included.
2025-07-17T07:05:40.6936010Z     is_python_module: If ``True`` (default), imports the produced shared
2025-07-17T07:05:40.6936310Z         library as a Python module. If ``False``, behavior depends on
2025-07-17T07:05:40.6936540Z         ``is_standalone``.
2025-07-17T07:05:40.6936760Z     is_standalone: If ``False`` (default) loads the constructed extension
2025-07-17T07:05:40.6937080Z         into the process as a plain dynamic library. If ``True``, build a
2025-07-17T07:05:40.6937330Z         standalone executable.
2025-07-17T07:05:40.6937440Z 
2025-07-17T07:05:40.6937480Z Returns:
2025-07-17T07:05:40.6937600Z     If ``is_python_module`` is ``True``:
2025-07-17T07:05:40.6937830Z         Returns the loaded PyTorch extension as a Python module.
2025-07-17T07:05:40.6938000Z 
2025-07-17T07:05:40.6938130Z     If ``is_python_module`` is ``False`` and ``is_standalone`` is ``False``:
2025-07-17T07:05:40.6938450Z         Returns nothing. (The shared library is loaded into the process as
2025-07-17T07:05:40.6938690Z         a side effect.)
2025-07-17T07:05:40.6938780Z 
2025-07-17T07:05:40.6938850Z     If ``is_standalone`` is ``True``.
2025-07-17T07:05:40.6939110Z         Return the path to the executable. (On Windows, TORCH_LIB_PATH is
2025-07-17T07:05:40.6939410Z         added to the PATH environment variable as a side effect.)
2025-07-17T07:05:40.6939580Z 
2025-07-17T07:05:40.6939620Z Example:
2025-07-17T07:05:40.6939770Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:40.6939950Z     >>> from torch.utils.cpp_extension import load
2025-07-17T07:05:40.6940150Z     >>> module = load(
2025-07-17T07:05:40.6940300Z     ...     name='extension',
2025-07-17T07:05:40.6940500Z     ...     sources=['extension.cpp', 'extension_kernel.cu'],
2025-07-17T07:05:40.6940720Z     ...     extra_cflags=['-O2'],
2025-07-17T07:05:40.6940880Z     ...     verbose=True)
2025-07-17T07:05:40.6940980Z 
2025-07-17T07:05:40.6941140Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.6941350Z 
2025-07-17T07:05:40.6941770Z msg = Cannot scrape callname=load_inline in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1890.
2025-07-17T07:05:40.6942390Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.6942610Z 
2025-07-17T07:05:40.6942740Z Load a PyTorch C++ extension just-in-time (JIT) from string sources.
2025-07-17T07:05:40.6942930Z 
2025-07-17T07:05:40.6943070Z This function behaves exactly like :func:`load`, but takes its sources as
2025-07-17T07:05:40.6943410Z strings rather than filenames. These strings are stored to files in the
2025-07-17T07:05:40.6943740Z build directory, after which the behavior of :func:`load_inline` is
2025-07-17T07:05:40.6943990Z identical to :func:`load`.
2025-07-17T07:05:40.6944090Z 
2025-07-17T07:05:40.6944140Z See `the
2025-07-17T07:05:40.6944410Z tests <https://github.com/pytorch/pytorch/blob/master/test/test_cpp_extensions_jit.py>`_
2025-07-17T07:05:40.6944730Z for good examples of using this function.
2025-07-17T07:05:40.6944870Z 
2025-07-17T07:05:40.6945010Z Sources may omit two required parts of a typical non-inline C++ extension:
2025-07-17T07:05:40.6945360Z the necessary header includes, as well as the (pybind11) binding code. More
2025-07-17T07:05:40.6945710Z precisely, strings passed to ``cpp_sources`` are first concatenated into a
2025-07-17T07:05:40.6946040Z single ``.cpp`` file. This file is then prepended with ``#include
2025-07-17T07:05:40.6946260Z <torch/extension.h>``
2025-07-17T07:05:40.6946360Z 
2025-07-17T07:05:40.6946490Z Furthermore, if the ``functions`` argument is supplied, bindings will be
2025-07-17T07:05:40.6946830Z automatically generated for each function specified. ``functions`` can
2025-07-17T07:05:40.6947170Z either be a list of function names, or a dictionary mapping from function
2025-07-17T07:05:40.6947500Z names to docstrings. If a list is given, the name of each function is used
2025-07-17T07:05:40.6947740Z as its docstring.
2025-07-17T07:05:40.6947830Z 
2025-07-17T07:05:40.6947960Z The sources in ``cuda_sources`` are concatenated into a separate ``.cu``
2025-07-17T07:05:40.6948270Z file and  prepended with ``torch/types.h``, ``cuda.h`` and
2025-07-17T07:05:40.6948560Z ``cuda_runtime.h`` includes. The ``.cpp`` and ``.cu`` files are compiled
2025-07-17T07:05:40.6948890Z separately, but ultimately linked into a single library. Note that no
2025-07-17T07:05:40.6949220Z bindings are generated for functions in ``cuda_sources`` per se. To bind
2025-07-17T07:05:40.6949550Z to a CUDA kernel, you must create a C++ function that calls it, and either
2025-07-17T07:05:40.6949870Z declare or define this C++ function in one of the ``cpp_sources`` (and
2025-07-17T07:05:40.6950120Z include its name in ``functions``).
2025-07-17T07:05:40.6950240Z 
2025-07-17T07:05:40.6950380Z The sources in ``sycl_sources`` are concatenated into a separate ``.sycl``
2025-07-17T07:05:40.6950700Z file and  prepended with ``torch/types.h``, ``sycl/sycl.hpp`` includes.
2025-07-17T07:05:40.6951020Z The ``.cpp`` and ``.sycl`` files are compiled separately, but ultimately
2025-07-17T07:05:40.6951360Z linked into a single library. Note that no bindings are generated for
2025-07-17T07:05:40.6951690Z functions in ``sycl_sources`` per se. To bind to a SYCL kernel, you must
2025-07-17T07:05:40.6952010Z create a C++ function that calls it, and either declare or define this
2025-07-17T07:05:40.6952340Z C++ function in one of the ``cpp_sources`` (and include its name
2025-07-17T07:05:40.6952570Z in ``functions``).
2025-07-17T07:05:40.6952650Z 
2025-07-17T07:05:40.6952660Z 
2025-07-17T07:05:40.6952660Z 
2025-07-17T07:05:40.6952770Z See :func:`load` for a description of arguments omitted below.
2025-07-17T07:05:40.6952940Z 
2025-07-17T07:05:40.6952980Z Args:
2025-07-17T07:05:40.6953180Z     cpp_sources: A string, or list of strings, containing C++ source code.
2025-07-17T07:05:40.6953510Z     cuda_sources: A string, or list of strings, containing CUDA source code.
2025-07-17T07:05:40.6953850Z     sycl_sources: A string, or list of strings, containing SYCL source code.
2025-07-17T07:05:40.6954190Z     functions: A list of function names for which to generate function
2025-07-17T07:05:40.6954530Z         bindings. If a dictionary is given, it should map function names to
2025-07-17T07:05:40.6954840Z         docstrings (which are otherwise just the function names).
2025-07-17T07:05:40.6955150Z     with_cuda: Determines whether CUDA headers and libraries are added to
2025-07-17T07:05:40.6955450Z         the build. If set to ``None`` (default), this value is
2025-07-17T07:05:40.6955730Z         automatically determined based on whether ``cuda_sources`` is
2025-07-17T07:05:40.6956020Z         provided. Set it to ``True`` to force CUDA headers
2025-07-17T07:05:40.6956240Z         and libraries to be included.
2025-07-17T07:05:40.6956500Z     with_sycl: Determines whether SYCL headers and libraries are added to
2025-07-17T07:05:40.6956790Z         the build. If set to ``None`` (default), this value is
2025-07-17T07:05:40.6957080Z         automatically determined based on whether ``sycl_sources`` is
2025-07-17T07:05:40.6957360Z         provided. Set it to ``True`` to force SYCL headers
2025-07-17T07:05:40.6957570Z         and libraries to be included.
2025-07-17T07:05:40.6957820Z     with_pytorch_error_handling: Determines whether pytorch error and
2025-07-17T07:05:40.6958130Z         warning macros are handled by pytorch instead of pybind. To do
2025-07-17T07:05:40.6958450Z         this, each function ``foo`` is called via an intermediary ``_safe_foo``
2025-07-17T07:05:40.6958760Z         function. This redirection might cause issues in obscure cases
2025-07-17T07:05:40.6959070Z         of cpp. This flag should be set to ``False`` when this redirect
2025-07-17T07:05:40.6959290Z         causes issues.
2025-07-17T07:05:40.6959540Z     no_implicit_headers: If ``True``, skips automatically adding headers, most notably
2025-07-17T07:05:40.6959900Z         ``#include <torch/extension.h>`` and ``#include <torch/types.h>`` lines.
2025-07-17T07:05:40.6960190Z         Use this option to improve cold start times when you
2025-07-17T07:05:40.6960510Z         already include the necessary headers in your source code. Default: ``False``.
2025-07-17T07:05:40.6960730Z 
2025-07-17T07:05:40.6960780Z Example:
2025-07-17T07:05:40.6960930Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-07-17T07:05:40.6961180Z     >>> from torch.utils.cpp_extension import load_inline
2025-07-17T07:05:40.6961380Z     >>> source = """
2025-07-17T07:05:40.6961560Z     at::Tensor sin_add(at::Tensor x, at::Tensor y) {
2025-07-17T07:05:40.6961760Z       return x.sin() + y.sin();
2025-07-17T07:05:40.6961910Z     }
2025-07-17T07:05:40.6962010Z     """
2025-07-17T07:05:40.6962160Z     >>> module = load_inline(name='inline_extension',
2025-07-17T07:05:40.6962380Z     ...                      cpp_sources=[source],
2025-07-17T07:05:40.6962580Z     ...                      functions=['sin_add'])
2025-07-17T07:05:40.6962720Z 
2025-07-17T07:05:40.6962770Z .. note::
2025-07-17T07:05:40.6962980Z     Since load_inline will just-in-time compile the source code, please ensure
2025-07-17T07:05:40.6963350Z     that you have the right toolchains installed in the runtime. For example,
2025-07-17T07:05:40.6963690Z     when loading C++, make sure a C++ compiler is available. If you're loading
2025-07-17T07:05:40.6964030Z     a CUDA extension, you will need to additionally install the corresponding CUDA
2025-07-17T07:05:40.6964450Z     toolkit (nvcc and any other dependencies your code has). Compiling toolchains
2025-07-17T07:05:40.6964800Z     are not included when you install torch and must be additionally installed.
2025-07-17T07:05:40.6965010Z 
2025-07-17T07:05:40.6965170Z     During compiling, by default, the Ninja backend uses #CPUS + 2 workers to build
2025-07-17T07:05:40.6965520Z     the extension. This may use up too many resources on some systems. One
2025-07-17T07:05:40.6965850Z     can control the number of workers by setting the `MAX_JOBS` environment
2025-07-17T07:05:40.6966110Z     variable to a non-negative number.
2025-07-17T07:05:40.6966260Z 
2025-07-17T07:05:40.6966440Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.6966660Z 
2025-07-17T07:05:40.6967070Z msg = Cannot scrape callname=DistributedSampler in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/distributed.py line=18.
2025-07-17T07:05:40.6967700Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:40.6968040Z Sampler that restricts data loading to a subset of the dataset.
2025-07-17T07:05:40.6968230Z 
2025-07-17T07:05:40.6968310Z     It is especially useful in conjunction with
2025-07-17T07:05:40.6968610Z     :class:`torch.nn.parallel.DistributedDataParallel`. In such a case, each
2025-07-17T07:05:40.6968980Z     process can pass a :class:`~torch.utils.data.DistributedSampler` instance as a
2025-07-17T07:05:40.6969340Z     :class:`~torch.utils.data.DataLoader` sampler, and load a subset of the
2025-07-17T07:05:40.6969620Z     original dataset that is exclusive to it.
2025-07-17T07:05:40.6969760Z 
2025-07-17T07:05:40.6969810Z     .. note::
2025-07-17T07:05:40.6970030Z         Dataset is assumed to be of constant size and that any instance of it always
2025-07-17T07:05:40.6970320Z         returns the same elements in the same order.
2025-07-17T07:05:40.6970470Z 
2025-07-17T07:05:40.6970510Z     Args:
2025-07-17T07:05:40.6970640Z         dataset: Dataset used for sampling.
2025-07-17T07:05:40.6970910Z         num_replicas (int, optional): Number of processes participating in
2025-07-17T07:05:40.6971250Z             distributed training. By default, :attr:`world_size` is retrieved from the
2025-07-17T07:05:40.6971530Z             current distributed group.
2025-07-17T07:05:40.6971800Z         rank (int, optional): Rank of the current process within :attr:`num_replicas`.
2025-07-17T07:05:40.6972140Z             By default, :attr:`rank` is retrieved from the current distributed
2025-07-17T07:05:40.6972370Z             group.
2025-07-17T07:05:40.6972590Z         shuffle (bool, optional): If ``True`` (default), sampler will shuffle the
2025-07-17T07:05:40.6972840Z             indices.
2025-07-17T07:05:40.6973040Z         seed (int, optional): random seed used to shuffle the sampler if
2025-07-17T07:05:40.6973340Z             :attr:`shuffle=True`. This number should be identical across all
2025-07-17T07:05:40.6973630Z             processes in the distributed group. Default: ``0``.
2025-07-17T07:05:40.6973930Z         drop_last (bool, optional): if ``True``, then the sampler will drop the
2025-07-17T07:05:40.6974240Z             tail of the data to make it evenly divisible across the number of
2025-07-17T07:05:40.6974550Z             replicas. If ``False``, the sampler will add extra indices to make
2025-07-17T07:05:40.6974870Z             the data evenly divisible across the replicas. Default: ``False``.
2025-07-17T07:05:40.6975060Z 
2025-07-17T07:05:40.6975110Z     .. warning::
2025-07-17T07:05:40.6975300Z         In distributed mode, calling the :meth:`set_epoch` method at
2025-07-17T07:05:40.6975650Z         the beginning of each epoch **before** creating the :class:`DataLoader` iterator
2025-07-17T07:05:40.6976030Z         is necessary to make shuffling work properly across multiple epochs. Otherwise,
2025-07-17T07:05:40.6976350Z         the same ordering will be always used.
2025-07-17T07:05:40.6976490Z 
2025-07-17T07:05:40.6976540Z     Example::
2025-07-17T07:05:40.6976610Z 
2025-07-17T07:05:40.6976670Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:40.6976920Z         >>> sampler = DistributedSampler(dataset) if is_distributed else None
2025-07-17T07:05:40.6977220Z         >>> loader = DataLoader(dataset, shuffle=(sampler is None),
2025-07-17T07:05:40.6977460Z         ...                     sampler=sampler)
2025-07-17T07:05:40.6977670Z         >>> for epoch in range(start_epoch, n_epochs):
2025-07-17T07:05:40.6977880Z         ...     if is_distributed:
2025-07-17T07:05:40.6978060Z         ...         sampler.set_epoch(epoch)
2025-07-17T07:05:40.6978270Z         ...     train(loader)
2025-07-17T07:05:40.6978440Z     
2025-07-17T07:05:40.6978660Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:40.6978880Z 
2025-07-17T07:05:41.3805950Z msg = Cannot scrape callname=assert_close in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/testing/_comparison.py line=1331.
2025-07-17T07:05:41.3806620Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:41.3806940Z Asserts that ``actual`` and ``expected`` are close.
2025-07-17T07:05:41.3807110Z 
2025-07-17T07:05:41.3807340Z     If ``actual`` and ``expected`` are strided, non-quantized, real-valued, and finite, they are considered close if
2025-07-17T07:05:41.3807630Z 
2025-07-17T07:05:41.3807710Z     .. math::
2025-07-17T07:05:41.3807790Z 
2025-07-17T07:05:41.3808020Z         \lvert \text{actual} - \text{expected} \rvert \le \texttt{atol} + \texttt{rtol} \cdot \lvert \text{expected} \rvert
2025-07-17T07:05:41.3808310Z 
2025-07-17T07:05:41.3808550Z     Non-finite values (``-inf`` and ``inf``) are only considered close if and only if they are equal. ``NaN``'s are
2025-07-17T07:05:41.3808960Z     only considered equal to each other if ``equal_nan`` is ``True``.
2025-07-17T07:05:41.3809160Z 
2025-07-17T07:05:41.3809300Z     In addition, they are only considered close if they have the same
2025-07-17T07:05:41.3809500Z 
2025-07-17T07:05:41.3809630Z     - :attr:`~torch.Tensor.device` (if ``check_device`` is ``True``),
2025-07-17T07:05:41.3809900Z     - ``dtype`` (if ``check_dtype`` is ``True``),
2025-07-17T07:05:41.3810130Z     - ``layout`` (if ``check_layout`` is ``True``), and
2025-07-17T07:05:41.3810400Z     - stride (if ``check_stride`` is ``True``).
2025-07-17T07:05:41.3810550Z 
2025-07-17T07:05:41.3810730Z     If either ``actual`` or ``expected`` is a meta tensor, only the attribute checks will be performed.
2025-07-17T07:05:41.3810980Z 
2025-07-17T07:05:41.3811220Z     If ``actual`` and ``expected`` are sparse (either having COO, CSR, CSC, BSR, or BSC layout), their strided members are
2025-07-17T07:05:41.3811740Z     checked individually. Indices, namely ``indices`` for COO, ``crow_indices`` and ``col_indices`` for CSR and BSR,
2025-07-17T07:05:41.3812180Z     or ``ccol_indices``  and ``row_indices`` for CSC and BSC layouts, respectively,
2025-07-17T07:05:41.3812640Z     are always checked for equality whereas the values are checked for closeness according to the definition above.
2025-07-17T07:05:41.3812940Z 
2025-07-17T07:05:41.3813120Z     If ``actual`` and ``expected`` are quantized, they are considered close if they have the same
2025-07-17T07:05:41.3813570Z     :meth:`~torch.Tensor.qscheme` and the result of :meth:`~torch.Tensor.dequantize` is close according to the
2025-07-17T07:05:41.3813890Z     definition above.
2025-07-17T07:05:41.3813990Z 
2025-07-17T07:05:41.3814170Z     ``actual`` and ``expected`` can be :class:`~torch.Tensor`'s or any tensor-or-scalar-likes from which
2025-07-17T07:05:41.3814800Z     :class:`torch.Tensor`'s can be constructed with :func:`torch.as_tensor`. Except for Python scalars the input types
2025-07-17T07:05:41.3815340Z     have to be directly related. In addition, ``actual`` and ``expected`` can be :class:`~collections.abc.Sequence`'s
2025-07-17T07:05:41.3815970Z     or :class:`~collections.abc.Mapping`'s in which case they are considered close if their structure matches and all
2025-07-17T07:05:41.3816500Z     their elements are considered close according to the above definition.
2025-07-17T07:05:41.3822690Z 
2025-07-17T07:05:41.3822750Z     .. note::
2025-07-17T07:05:41.3822820Z 
2025-07-17T07:05:41.3823030Z         Python scalars are an exception to the type relation requirement, because their :func:`type`, i.e.
2025-07-17T07:05:41.3823500Z         :class:`int`, :class:`float`, and :class:`complex`, is equivalent to the ``dtype`` of a tensor-like. Thus,
2025-07-17T07:05:41.3824120Z         Python scalars of different types can be checked, but require ``check_dtype=False``.
2025-07-17T07:05:41.3824430Z 
2025-07-17T07:05:41.3824480Z     Args:
2025-07-17T07:05:41.3824600Z         actual (Any): Actual input.
2025-07-17T07:05:41.3824790Z         expected (Any): Expected input.
2025-07-17T07:05:41.3825140Z         allow_subclasses (bool): If ``True`` (default) and except for Python scalars, inputs of directly related types
2025-07-17T07:05:41.3825520Z             are allowed. Otherwise type equality is required.
2025-07-17T07:05:41.3825910Z         rtol (Optional[float]): Relative tolerance. If specified ``atol`` must also be specified. If omitted, default
2025-07-17T07:05:41.3826380Z             values based on the :attr:`~torch.Tensor.dtype` are selected with the below table.
2025-07-17T07:05:41.3826820Z         atol (Optional[float]): Absolute tolerance. If specified ``rtol`` must also be specified. If omitted, default
2025-07-17T07:05:41.3827250Z             values based on the :attr:`~torch.Tensor.dtype` are selected with the below table.
2025-07-17T07:05:41.3827630Z         equal_nan (Union[bool, str]): If ``True``, two ``NaN`` values will be considered equal.
2025-07-17T07:05:41.3828030Z         check_device (bool): If ``True`` (default), asserts that corresponding tensors are on the same
2025-07-17T07:05:41.3828420Z             :attr:`~torch.Tensor.device`. If this check is disabled, tensors on different
2025-07-17T07:05:41.3828780Z             :attr:`~torch.Tensor.device`'s are moved to the CPU before being compared.
2025-07-17T07:05:41.3829200Z         check_dtype (bool): If ``True`` (default), asserts that corresponding tensors have the same ``dtype``. If this
2025-07-17T07:05:41.3829680Z             check is disabled, tensors with different ``dtype``'s are promoted  to a common ``dtype`` (according to
2025-07-17T07:05:41.3830040Z             :func:`torch.promote_types`) before being compared.
2025-07-17T07:05:41.3830420Z         check_layout (bool): If ``True`` (default), asserts that corresponding tensors have the same ``layout``. If this
2025-07-17T07:05:41.3830890Z             check is disabled, tensors with different ``layout``'s are converted to strided tensors before being
2025-07-17T07:05:41.3831200Z             compared.
2025-07-17T07:05:41.3831510Z         check_stride (bool): If ``True`` and corresponding tensors are strided, asserts that they have the same stride.
2025-07-17T07:05:41.3832000Z         msg (Optional[Union[str, Callable[[str], str]]]): Optional error message to use in case a failure occurs during
2025-07-17T07:05:41.3832480Z             the comparison. Can also passed as callable in which case it will be called with the generated message and
2025-07-17T07:05:41.3832830Z             should return the new message.
2025-07-17T07:05:41.3832960Z 
2025-07-17T07:05:41.3833000Z     Raises:
2025-07-17T07:05:41.3833210Z         ValueError: If no :class:`torch.Tensor` can be constructed from an input.
2025-07-17T07:05:41.3833520Z         ValueError: If only ``rtol`` or ``atol`` is specified.
2025-07-17T07:05:41.3833950Z         AssertionError: If corresponding inputs are not Python scalars and are not directly related.
2025-07-17T07:05:41.3834430Z         AssertionError: If ``allow_subclasses`` is ``False``, but corresponding inputs are not Python scalars and have
2025-07-17T07:05:41.3834770Z             different types.
2025-07-17T07:05:41.3835110Z         AssertionError: If the inputs are :class:`~collections.abc.Sequence`'s, but their length does not match.
2025-07-17T07:05:41.3835600Z         AssertionError: If the inputs are :class:`~collections.abc.Mapping`'s, but their set of keys do not match.
2025-07-17T07:05:41.3836070Z         AssertionError: If corresponding tensors do not have the same :attr:`~torch.Tensor.shape`.
2025-07-17T07:05:41.3836500Z         AssertionError: If ``check_layout`` is ``True``, but corresponding tensors do not have the same
2025-07-17T07:05:41.3836820Z             :attr:`~torch.Tensor.layout`.
2025-07-17T07:05:41.3837090Z         AssertionError: If only one of corresponding tensors is quantized.
2025-07-17T07:05:41.3837530Z         AssertionError: If corresponding tensors are quantized, but have different :meth:`~torch.Tensor.qscheme`'s.
2025-07-17T07:05:41.3838030Z         AssertionError: If ``check_device`` is ``True``, but corresponding tensors are not on the same
2025-07-17T07:05:41.3838340Z             :attr:`~torch.Tensor.device`.
2025-07-17T07:05:41.3838660Z         AssertionError: If ``check_dtype`` is ``True``, but corresponding tensors do not have the same ``dtype``.
2025-07-17T07:05:41.3839140Z         AssertionError: If ``check_stride`` is ``True``, but corresponding strided tensors do not have the same stride.
2025-07-17T07:05:41.3839640Z         AssertionError: If the values of corresponding tensors are not close according to the definition above.
2025-07-17T07:05:41.3839910Z 
2025-07-17T07:05:41.3840130Z     The following table displays the default ``rtol`` and ``atol`` for different ``dtype``'s. In case of mismatching
2025-07-17T07:05:41.3840500Z     ``dtype``'s, the maximum of both tolerances is used.
2025-07-17T07:05:41.3840660Z 
2025-07-17T07:05:41.3840740Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3840970Z     | ``dtype``                 | ``rtol``   | ``atol`` |
2025-07-17T07:05:41.3841170Z     +===========================+============+==========+
2025-07-17T07:05:41.3841390Z     | :attr:`~torch.float16`    | ``1e-3``   | ``1e-5`` |
2025-07-17T07:05:41.3841620Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3841840Z     | :attr:`~torch.bfloat16`   | ``1.6e-2`` | ``1e-5`` |
2025-07-17T07:05:41.3842060Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3842270Z     | :attr:`~torch.float32`    | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:41.3842490Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3842710Z     | :attr:`~torch.float64`    | ``1e-7``   | ``1e-7`` |
2025-07-17T07:05:41.3842920Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3843150Z     | :attr:`~torch.complex32`  | ``1e-3``   | ``1e-5`` |
2025-07-17T07:05:41.3843370Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3843590Z     | :attr:`~torch.complex64`  | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:41.3843810Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3844030Z     | :attr:`~torch.complex128` | ``1e-7``   | ``1e-7`` |
2025-07-17T07:05:41.3844260Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3844480Z     | :attr:`~torch.quint8`     | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:41.3844700Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3844920Z     | :attr:`~torch.quint2x4`   | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:41.3845140Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3845360Z     | :attr:`~torch.quint4x2`   | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:41.3845580Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3845790Z     | :attr:`~torch.qint8`      | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:41.3846030Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3846260Z     | :attr:`~torch.qint32`     | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:41.3846470Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3846720Z     | other                     | ``0.0``    | ``0.0``  |
2025-07-17T07:05:41.3846940Z     +---------------------------+------------+----------+
2025-07-17T07:05:41.3847080Z 
2025-07-17T07:05:41.3847130Z     .. note::
2025-07-17T07:05:41.3847200Z 
2025-07-17T07:05:41.3847430Z         :func:`~torch.testing.assert_close` is highly configurable with strict default settings. Users are encouraged
2025-07-17T07:05:41.3847930Z         to :func:`~functools.partial` it to fit their use case. For example, if an equality check is needed, one might
2025-07-17T07:05:41.3848410Z         define an ``assert_equal`` that uses zero tolerances for every ``dtype`` by default:
2025-07-17T07:05:41.3848650Z 
2025-07-17T07:05:41.3848780Z         >>> import functools
2025-07-17T07:05:41.3849040Z         >>> assert_equal = functools.partial(torch.testing.assert_close, rtol=0, atol=0)
2025-07-17T07:05:41.3849320Z         >>> assert_equal(1e-9, 1e-10)
2025-07-17T07:05:41.3849510Z         Traceback (most recent call last):
2025-07-17T07:05:41.3849690Z         ...
2025-07-17T07:05:41.3849830Z         AssertionError: Scalars are not equal!
2025-07-17T07:05:41.3850020Z         <BLANKLINE>
2025-07-17T07:05:41.3850160Z         Expected 1e-10 but got 1e-09.
2025-07-17T07:05:41.3850360Z         Absolute difference: 9.000000000000001e-10
2025-07-17T07:05:41.3850570Z         Relative difference: 9.0
2025-07-17T07:05:41.3850680Z 
2025-07-17T07:05:41.3850730Z     Examples:
2025-07-17T07:05:41.3850860Z         >>> # tensor to tensor comparison
2025-07-17T07:05:41.3851070Z         >>> expected = torch.tensor([1e0, 1e-1, 1e-2])
2025-07-17T07:05:41.3851290Z         >>> actual = torch.acos(torch.cos(expected))
2025-07-17T07:05:41.3851530Z         >>> torch.testing.assert_close(actual, expected)
2025-07-17T07:05:41.3851680Z 
2025-07-17T07:05:41.3851740Z         >>> # scalar to scalar comparison
2025-07-17T07:05:41.3851920Z         >>> import math
2025-07-17T07:05:41.3852070Z         >>> expected = math.sqrt(2.0)
2025-07-17T07:05:41.3852250Z         >>> actual = 2.0 / math.sqrt(2.0)
2025-07-17T07:05:41.3852460Z         >>> torch.testing.assert_close(actual, expected)
2025-07-17T07:05:41.3852610Z 
2025-07-17T07:05:41.3852690Z         >>> # numpy array to numpy array comparison
2025-07-17T07:05:41.3852880Z         >>> import numpy as np
2025-07-17T07:05:41.3853080Z         >>> expected = np.array([1e0, 1e-1, 1e-2])
2025-07-17T07:05:41.3853280Z         >>> actual = np.arccos(np.cos(expected))
2025-07-17T07:05:41.3853510Z         >>> torch.testing.assert_close(actual, expected)
2025-07-17T07:05:41.3853660Z 
2025-07-17T07:05:41.3853730Z         >>> # sequence to sequence comparison
2025-07-17T07:05:41.3853920Z         >>> import numpy as np
2025-07-17T07:05:41.3854180Z         >>> # The types of the sequences do not have to match. They only have to have the same
2025-07-17T07:05:41.3854480Z         >>> # length and their elements have to match.
2025-07-17T07:05:41.3854720Z         >>> expected = [torch.tensor([1.0]), 2.0, np.array(3.0)]
2025-07-17T07:05:41.3854940Z         >>> actual = tuple(expected)
2025-07-17T07:05:41.3855150Z         >>> torch.testing.assert_close(actual, expected)
2025-07-17T07:05:41.3855300Z 
2025-07-17T07:05:41.3855370Z         >>> # mapping to mapping comparison
2025-07-17T07:05:41.3855570Z         >>> from collections import OrderedDict
2025-07-17T07:05:41.3855770Z         >>> import numpy as np
2025-07-17T07:05:41.3855940Z         >>> foo = torch.tensor(1.0)
2025-07-17T07:05:41.3856100Z         >>> bar = 2.0
2025-07-17T07:05:41.3856250Z         >>> baz = np.array(3.0)
2025-07-17T07:05:41.3856500Z         >>> # The types and a possible ordering of mappings do not have to match. They only
2025-07-17T07:05:41.3856900Z         >>> # have to have the same set of keys and their elements have to match.
2025-07-17T07:05:41.3857220Z         >>> expected = OrderedDict([("foo", foo), ("bar", bar), ("baz", baz)])
2025-07-17T07:05:41.3857490Z         >>> actual = {"baz": baz, "bar": bar, "foo": foo}
2025-07-17T07:05:41.3857750Z         >>> torch.testing.assert_close(actual, expected)
2025-07-17T07:05:41.3857910Z 
2025-07-17T07:05:41.3857980Z         >>> expected = torch.tensor([1.0, 2.0, 3.0])
2025-07-17T07:05:41.3858180Z         >>> actual = expected.clone()
2025-07-17T07:05:41.3858410Z         >>> # By default, directly related instances can be compared
2025-07-17T07:05:41.3858710Z         >>> torch.testing.assert_close(torch.nn.Parameter(actual), expected)
2025-07-17T07:05:41.3859030Z         >>> # This check can be made more strict with allow_subclasses=False
2025-07-17T07:05:41.3859280Z         >>> torch.testing.assert_close(
2025-07-17T07:05:41.3859590Z         ...     torch.nn.Parameter(actual), expected, allow_subclasses=False
2025-07-17T07:05:41.3859860Z         ... )
2025-07-17T07:05:41.3860000Z         Traceback (most recent call last):
2025-07-17T07:05:41.3860170Z         ...
2025-07-17T07:05:41.3860360Z         TypeError: No comparison pair was able to handle inputs of type
2025-07-17T07:05:41.3860700Z         <class 'torch.nn.parameter.Parameter'> and <class 'torch.Tensor'>.
2025-07-17T07:05:41.3861030Z         >>> # If the inputs are not directly related, they are never considered close
2025-07-17T07:05:41.3861340Z         >>> torch.testing.assert_close(actual.numpy(), expected)
2025-07-17T07:05:41.3861580Z         Traceback (most recent call last):
2025-07-17T07:05:41.3861750Z         ...
2025-07-17T07:05:41.3861990Z         TypeError: No comparison pair was able to handle inputs of type <class 'numpy.ndarray'>
2025-07-17T07:05:41.3862290Z         and <class 'torch.Tensor'>.
2025-07-17T07:05:41.3862570Z         >>> # Exceptions to these rules are Python scalars. They can be checked regardless of
2025-07-17T07:05:41.3862870Z         >>> # their type if check_dtype=False.
2025-07-17T07:05:41.3863110Z         >>> torch.testing.assert_close(1.0, 1, check_dtype=False)
2025-07-17T07:05:41.3863280Z 
2025-07-17T07:05:41.3863340Z         >>> # NaN != NaN by default.
2025-07-17T07:05:41.3863530Z         >>> expected = torch.tensor(float("Nan"))
2025-07-17T07:05:41.3863740Z         >>> actual = expected.clone()
2025-07-17T07:05:41.3863950Z         >>> torch.testing.assert_close(actual, expected)
2025-07-17T07:05:41.3864170Z         Traceback (most recent call last):
2025-07-17T07:05:41.3864340Z         ...
2025-07-17T07:05:41.3864490Z         AssertionError: Scalars are not close!
2025-07-17T07:05:41.3864670Z         <BLANKLINE>
2025-07-17T07:05:41.3864810Z         Expected nan but got nan.
2025-07-17T07:05:41.3865010Z         Absolute difference: nan (up to 1e-05 allowed)
2025-07-17T07:05:41.3865240Z         Relative difference: nan (up to 1.3e-06 allowed)
2025-07-17T07:05:41.3865570Z         >>> torch.testing.assert_close(actual, expected, equal_nan=True)
2025-07-17T07:05:41.3865760Z 
2025-07-17T07:05:41.3865840Z         >>> expected = torch.tensor([1.0, 2.0, 3.0])
2025-07-17T07:05:41.3866060Z         >>> actual = torch.tensor([1.0, 4.0, 5.0])
2025-07-17T07:05:41.3866280Z         >>> # The default error message can be overwritten.
2025-07-17T07:05:41.3866600Z         >>> torch.testing.assert_close(actual, expected, msg="Argh, the tensors are not close!")
2025-07-17T07:05:41.3866910Z         Traceback (most recent call last):
2025-07-17T07:05:41.3867090Z         ...
2025-07-17T07:05:41.3867240Z         AssertionError: Argh, the tensors are not close!
2025-07-17T07:05:41.3867530Z         >>> # If msg is a callable, it can be used to augment the generated message with
2025-07-17T07:05:41.3867780Z         >>> # extra information
2025-07-17T07:05:41.3867950Z         >>> torch.testing.assert_close(
2025-07-17T07:05:41.3868200Z         ...     actual, expected, msg=lambda msg: f"Header\n\n{msg}\n\nFooter"
2025-07-17T07:05:41.3868430Z         ... )
2025-07-17T07:05:41.3868620Z         Traceback (most recent call last):
2025-07-17T07:05:41.3868800Z         ...
2025-07-17T07:05:41.3868930Z         AssertionError: Header
2025-07-17T07:05:41.3869080Z         <BLANKLINE>
2025-07-17T07:05:41.3869250Z         Tensor-likes are not close!
2025-07-17T07:05:41.3869420Z         <BLANKLINE>
2025-07-17T07:05:41.3869560Z         Mismatched elements: 2 / 3 (66.7%)
2025-07-17T07:05:41.3869830Z         Greatest absolute difference: 2.0 at index (1,) (up to 1e-05 allowed)
2025-07-17T07:05:41.3870160Z         Greatest relative difference: 1.0 at index (1,) (up to 1.3e-06 allowed)
2025-07-17T07:05:41.3870420Z         <BLANKLINE>
2025-07-17T07:05:41.3870540Z         Footer
2025-07-17T07:05:41.3870660Z     
2025-07-17T07:05:41.3870870Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:41.8825350Z 
2025-07-17T07:05:41.8826040Z msg = Cannot scrape callname=triton_op in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/triton.py line=21.
2025-07-17T07:05:41.8826730Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:41.8827130Z Create a custom operator whose implementation is backed by 1+ triton kernels.
2025-07-17T07:05:41.8827360Z 
2025-07-17T07:05:41.8827490Z     This is a more structured way of using triton kernels with PyTorch.
2025-07-17T07:05:41.8827840Z     Prefer using triton kernels with no ``torch.library`` custom operator wrappers
2025-07-17T07:05:41.8828230Z     (like :func:`torch.library.custom_op`, :func:`torch.library.triton_op`) because
2025-07-17T07:05:41.8828520Z     that is simpler;
2025-07-17T07:05:41.8828770Z     only use :func:`torch.library.custom_op`/:func:`torch.library.triton_op` if you
2025-07-17T07:05:41.8829150Z     want to create an operator that behaves like PyTorch built-in operators.
2025-07-17T07:05:41.8829490Z     For example, you may use a ``torch.library`` wrapper API to define the
2025-07-17T07:05:41.8829840Z     behavior of the triton kernel when passed a tensor subclass or under
2025-07-17T07:05:41.8830100Z     a TorchDispatchMode.
2025-07-17T07:05:41.8830210Z 
2025-07-17T07:05:41.8830360Z     Use :func:`torch.library.triton_op` instead of :func:`torch.library.custom_op`
2025-07-17T07:05:41.8830650Z     when the implementation
2025-07-17T07:05:41.8830910Z     consists of 1+ triton kernels. :func:`torch.library.custom_op` treats
2025-07-17T07:05:41.8831230Z     custom operators as opaque (:func:`torch.compile` and
2025-07-17T07:05:41.8831550Z     :func:`torch.export.export` will never trace into them), but ``triton_op``
2025-07-17T07:05:41.8831910Z     makes the implementation visible to these subsystems, allowing them
2025-07-17T07:05:41.8832170Z     to optimize the triton kernel(s).
2025-07-17T07:05:41.8832300Z 
2025-07-17T07:05:41.8832430Z     Note that ``fn`` must only consist of calls to PyTorch-understood
2025-07-17T07:05:41.8832760Z     operators and triton kernels. Any triton kernels called inside ``fn``
2025-07-17T07:05:41.8833100Z     must be wrapped in a call to :func:`torch.library.wrap_triton`.
2025-07-17T07:05:41.8833290Z 
2025-07-17T07:05:41.8833340Z     Args:
2025-07-17T07:05:41.8833570Z         name (str): A name for the custom op that looks like "{namespace}::{name}",
2025-07-17T07:05:41.8833910Z             e.g. "mylib::my_linear". The name is used as the op's stable identifier
2025-07-17T07:05:41.8834220Z             in PyTorch subsystems (e.g. torch.export, FX graphs).
2025-07-17T07:05:41.8834540Z             To avoid name collisions, please use your project name as the namespace;
2025-07-17T07:05:41.8834890Z             e.g. all custom ops in pytorch/fbgemm use "fbgemm" as the namespace.
2025-07-17T07:05:41.8835260Z         mutates_args (Iterable[str] or "unknown"): The names of args that the function mutates.
2025-07-17T07:05:41.8835650Z             This MUST be accurate, otherwise, the behavior is undefined. If "unknown",
2025-07-17T07:05:41.8836100Z             it pessimistically assumes that all inputs to the operator are being mutated.
2025-07-17T07:05:41.8836460Z         schema (None | str): A schema string for the operator. If None
2025-07-17T07:05:41.8836780Z             (recommended) we'll infer a schema for the operator from its type
2025-07-17T07:05:41.8837160Z             annotations. We recommend letting us infer a schema unless you
2025-07-17T07:05:41.8837420Z             have a specific reason not to.
2025-07-17T07:05:41.8837660Z             Example: "(Tensor x, int y) -> (Tensor, Tensor)".
2025-07-17T07:05:41.8837820Z 
2025-07-17T07:05:41.8837870Z     Example::
2025-07-17T07:05:41.8837950Z 
2025-07-17T07:05:41.8838040Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-07-17T07:05:41.8838240Z         >>> import torch
2025-07-17T07:05:41.8838440Z         >>> from torch.library import triton_op, wrap_triton
2025-07-17T07:05:41.8838650Z         >>>
2025-07-17T07:05:41.8838770Z         >>> import triton
2025-07-17T07:05:41.8838970Z         >>> from triton import language as tl
2025-07-17T07:05:41.8839180Z         >>>
2025-07-17T07:05:41.8839310Z         >>> @triton.jit
2025-07-17T07:05:41.8839460Z         >>> def add_kernel(
2025-07-17T07:05:41.8839600Z         >>>     in_ptr0,
2025-07-17T07:05:41.8839750Z         >>>     in_ptr1,
2025-07-17T07:05:41.8839890Z         >>>     out_ptr,
2025-07-17T07:05:41.8840040Z         >>>     n_elements,
2025-07-17T07:05:41.8840210Z         >>>     BLOCK_SIZE: "tl.constexpr",
2025-07-17T07:05:41.8840390Z         >>> ):
2025-07-17T07:05:41.8840540Z         >>>     pid = tl.program_id(axis=0)
2025-07-17T07:05:41.8840740Z         >>>     block_start = pid * BLOCK_SIZE
2025-07-17T07:05:41.8840970Z         >>>     offsets = block_start + tl.arange(0, BLOCK_SIZE)
2025-07-17T07:05:41.8841200Z         >>>     mask = offsets < n_elements
2025-07-17T07:05:41.8841410Z         >>>     x = tl.load(in_ptr0 + offsets, mask=mask)
2025-07-17T07:05:41.8841640Z         >>>     y = tl.load(in_ptr1 + offsets, mask=mask)
2025-07-17T07:05:41.8841840Z         >>>     output = x + y
2025-07-17T07:05:41.8842040Z         >>>     tl.store(out_ptr + offsets, output, mask=mask)
2025-07-17T07:05:41.8842240Z         >>>
2025-07-17T07:05:41.8842390Z         >>> @triton_op("mylib::add", mutates_args={})
2025-07-17T07:05:41.8842660Z         >>> def add(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
2025-07-17T07:05:41.8842910Z         >>>     output = torch.empty_like(x)
2025-07-17T07:05:41.8843110Z         >>>     n_elements = output.numel()
2025-07-17T07:05:41.8843290Z         >>>
2025-07-17T07:05:41.8843410Z         >>>     def grid(meta):
2025-07-17T07:05:41.8843630Z         >>>         return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),)
2025-07-17T07:05:41.8843850Z         >>>
2025-07-17T07:05:41.8844030Z         >>>     # NB: we need to wrap the triton kernel in a call to wrap_triton
2025-07-17T07:05:41.8844330Z         >>>     wrap_triton(add_kernel)[grid](x, y, output, n_elements, 16)
2025-07-17T07:05:41.8850660Z         >>>     return output
2025-07-17T07:05:41.8850820Z         >>>
2025-07-17T07:05:41.8850950Z         >>> @torch.compile
2025-07-17T07:05:41.8851110Z         >>> def f(x, y):
2025-07-17T07:05:41.8851260Z         >>>     return add(x, y)
2025-07-17T07:05:41.8851410Z         >>>
2025-07-17T07:05:41.8851550Z         >>> x = torch.randn(3, device="cuda")
2025-07-17T07:05:41.8851750Z         >>> y = torch.randn(3, device="cuda")
2025-07-17T07:05:41.8851930Z         >>>
2025-07-17T07:05:41.8852040Z         >>> z = f(x, y)
2025-07-17T07:05:41.8852190Z         >>> assert torch.allclose(z, x + y)
2025-07-17T07:05:41.8852330Z 
2025-07-17T07:05:41.8852370Z     
2025-07-17T07:05:41.8852580Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:41.8852800Z 
2025-07-17T07:05:41.8853170Z msg = Cannot scrape callname=wrap_triton in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/triton.py line=202.
2025-07-17T07:05:41.8853760Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:41.8854200Z Allows capture of a triton kernel into a graph via make_fx or
2025-07-17T07:05:41.8854440Z     non-strict ``torch.export``.
2025-07-17T07:05:41.8854560Z 
2025-07-17T07:05:41.8854740Z     These technologies perform Dispatcher-based tracing (via
2025-07-17T07:05:41.8855040Z     ``__torch_dispatch__``) and cannot see calls to raw triton kernels.
2025-07-17T07:05:41.8855360Z     The ``wrap_triton`` API wraps a triton kernel into a callable that
2025-07-17T07:05:41.8855610Z     can actually be traced into a graph.
2025-07-17T07:05:41.8855740Z 
2025-07-17T07:05:41.8855870Z     Please use this API together with :func:`torch.library.triton_op`.
2025-07-17T07:05:41.8856060Z 
2025-07-17T07:05:41.8856110Z     Examples:
2025-07-17T07:05:41.8856180Z 
2025-07-17T07:05:41.8856240Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:41.8856390Z         >>> import torch
2025-07-17T07:05:41.8856560Z         >>> import triton
2025-07-17T07:05:41.8856740Z         >>> from triton import language as tl
2025-07-17T07:05:41.8856990Z         >>> from torch.fx.experimental.proxy_tensor import make_fx
2025-07-17T07:05:41.8857240Z         >>> from torch.library import wrap_triton
2025-07-17T07:05:41.8857430Z         >>>
2025-07-17T07:05:41.8857550Z         >>> @triton.jit
2025-07-17T07:05:41.8857690Z         >>> def add_kernel(
2025-07-17T07:05:41.8857840Z         >>>     in_ptr0,
2025-07-17T07:05:41.8857980Z         >>>     in_ptr1,
2025-07-17T07:05:41.8858120Z         >>>     out_ptr,
2025-07-17T07:05:41.8858250Z         >>>     n_elements,
2025-07-17T07:05:41.8858410Z         >>>     BLOCK_SIZE: "tl.constexpr",
2025-07-17T07:05:41.8858590Z         >>> ):
2025-07-17T07:05:41.8858720Z         >>>     pid = tl.program_id(axis=0)
2025-07-17T07:05:41.8858910Z         >>>     block_start = pid * BLOCK_SIZE
2025-07-17T07:05:41.8859140Z         >>>     offsets = block_start + tl.arange(0, BLOCK_SIZE)
2025-07-17T07:05:41.8859360Z         >>>     mask = offsets < n_elements
2025-07-17T07:05:41.8859570Z         >>>     x = tl.load(in_ptr0 + offsets, mask=mask)
2025-07-17T07:05:41.8859790Z         >>>     y = tl.load(in_ptr1 + offsets, mask=mask)
2025-07-17T07:05:41.8859990Z         >>>     output = x + y
2025-07-17T07:05:41.8860180Z         >>>     tl.store(out_ptr + offsets, output, mask=mask)
2025-07-17T07:05:41.8860380Z         >>>
2025-07-17T07:05:41.8860490Z         >>> def add(x, y):
2025-07-17T07:05:41.8860660Z         >>>     output = torch.empty_like(x)
2025-07-17T07:05:41.8860850Z         >>>     n_elements = output.numel()
2025-07-17T07:05:41.8861020Z         >>>
2025-07-17T07:05:41.8861140Z         >>>     def grid_fn(meta):
2025-07-17T07:05:41.8861360Z         >>>         return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),)
2025-07-17T07:05:41.8861570Z         >>>
2025-07-17T07:05:41.8861760Z         >>>     wrap_triton(add_kernel)[grid_fn](x, y, output, n_elements, 16)
2025-07-17T07:05:41.8861990Z         >>>     return output
2025-07-17T07:05:41.8862140Z         >>>
2025-07-17T07:05:41.8862280Z         >>> x = torch.randn(3, device="cuda")
2025-07-17T07:05:41.8862480Z         >>> y = torch.randn(3, device="cuda")
2025-07-17T07:05:41.8862670Z         >>> gm = make_fx(add)(x, y)
2025-07-17T07:05:41.8862840Z         >>> print(gm.code)
2025-07-17T07:05:41.8863000Z         >>> # def forward(self, x_1, y_1):
2025-07-17T07:05:41.8863270Z         >>> #     empty_like = torch.ops.aten.empty_like.default(x_1, pin_memory = False)
2025-07-17T07:05:41.8863630Z         >>> #     triton_kernel_wrapper_mutation_proxy = triton_kernel_wrapper_mutation(
2025-07-17T07:05:41.8863920Z         >>> #         kernel_idx = 0, constant_args_idx = 0,
2025-07-17T07:05:41.8864130Z         >>> #         grid = [(1, 1, 1)], kwargs = {
2025-07-17T07:05:41.8864360Z         >>> #             'in_ptr0': x_1, 'in_ptr1': y_1, 'out_ptr': empty_like,
2025-07-17T07:05:41.8864590Z         >>> #             'n_elements': 3, 'BLOCK_SIZE': 16
2025-07-17T07:05:41.8864790Z         >>> #         })
2025-07-17T07:05:41.8864940Z         >>> #     return empty_like
2025-07-17T07:05:41.8865080Z 
2025-07-17T07:05:41.8865130Z     
2025-07-17T07:05:41.8865360Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:41.8865570Z 
2025-07-17T07:05:41.8866020Z msg = Cannot scrape callname=unsafe_generate_fake_kernels in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/fake_profile.py line=94.
2025-07-17T07:05:41.8866660Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:41.8866880Z 
2025-07-17T07:05:41.8867010Z Registers a fake kernel based on the given operator profiles. This fake
2025-07-17T07:05:41.8867370Z kernel registration will override any existing fake kernel registrations.
2025-07-17T07:05:41.8867590Z 
2025-07-17T07:05:41.8867720Z The input is a dictionary mapping operator names to a set of operator
2025-07-17T07:05:41.8868110Z profiles, which we will use to generate fake kernels. The operator profiles
2025-07-17T07:05:41.8868470Z are a record of the input and output tensor metadata. Based on this
2025-07-17T07:05:41.8868790Z information we will match a given input to the recorded profile, and return
2025-07-17T07:05:41.8869140Z an output with the same metadata as in the recorded profile. If a profile
2025-07-17T07:05:41.8869420Z doesn't exist then an exception will be thrown.
2025-07-17T07:05:41.8869570Z 
2025-07-17T07:05:41.8869710Z The fake kernel generation is considered unsafe because it relies on the
2025-07-17T07:05:41.8870080Z rigid, pre-defined operator profiles that do not account for potential
2025-07-17T07:05:41.8870420Z variations in output behavior. Specifically, the generated kernels assume a
2025-07-17T07:05:41.8870790Z fixed relationship between input and output ranks. However, in reality, it's
2025-07-17T07:05:41.8871140Z possible that data-dependent operations may produce outputs of different
2025-07-17T07:05:41.8871490Z ranks even when given inputs of the same rank. The generated fake kernels
2025-07-17T07:05:41.8871850Z are inflexible and unable to accommodate these nuances, making them
2025-07-17T07:05:41.8872090Z potentially unsafe.
2025-07-17T07:05:41.8872190Z 
2025-07-17T07:05:41.8872230Z Args:
2025-07-17T07:05:41.8872430Z     op_profiles (dict[str, set[OpProfile]]): A dictionary mapping operator
2025-07-17T07:05:41.8872750Z         name to a set of operator profiles from which we will generate fake
2025-07-17T07:05:41.8872980Z         kernels.
2025-07-17T07:05:41.8873070Z 
2025-07-17T07:05:41.8873110Z Examples:
2025-07-17T07:05:41.8873180Z 
2025-07-17T07:05:41.8873280Z     >>> # Example: Registering an op-profile from draft-export
2025-07-17T07:05:41.8873490Z     >>> import torch
2025-07-17T07:05:41.8873680Z     >>> from torch.export._draft_export import draft_export
2025-07-17T07:05:41.8873880Z     >>>
2025-07-17T07:05:41.8874050Z     >>> @torch.library.custom_op("mylib::foo", mutates_args=())
2025-07-17T07:05:41.8874300Z     >>> def foo(x: Tensor, y: Tensor) -> Tensor:
2025-07-17T07:05:41.8874490Z     >>>     return x + y
2025-07-17T07:05:41.8874630Z     >>>
2025-07-17T07:05:41.8874760Z     >>> class M(torch.nn.Module):
2025-07-17T07:05:41.8874930Z     >>>     def forward(self, a, b):
2025-07-17T07:05:41.8875140Z     >>>         res = torch.ops.mylib.foo(a, b)  # no fake impl
2025-07-17T07:05:41.8875340Z     >>>         return res
2025-07-17T07:05:41.8875480Z     >>>
2025-07-17T07:05:41.8875650Z     >>> ep = draft_export(M(), (torch.ones(3, 4), torch.ones(3, 4))
2025-07-17T07:05:41.8875860Z     >>>
2025-07-17T07:05:41.8876100Z     >>> with torch._library.fake_profile.unsafe_generate_fake_kernels(ep._report.op_profiles):
2025-07-17T07:05:41.8876410Z     >>>     decomp = ep.run_decompositions()
2025-07-17T07:05:41.8876540Z 
2025-07-17T07:05:41.8876550Z 
2025-07-17T07:05:41.8876700Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:41.9530830Z 
2025-07-17T07:05:41.9531560Z msg = Cannot scrape callname=CustomOpDef.register_fake in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/custom_ops.py line=396.
2025-07-17T07:05:41.9532270Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:41.9532680Z Register a FakeTensor implementation for this custom op.
2025-07-17T07:05:41.9532870Z 
2025-07-17T07:05:41.9533020Z         This is necessary to get the operator to work efficiently with torch.compile.
2025-07-17T07:05:41.9533250Z 
2025-07-17T07:05:41.9533390Z         The Fake impl (sometimes also known as a meta kernel or abstract impl)
2025-07-17T07:05:41.9533730Z         specifies the behavior of this operator on Tensors that carry no data.
2025-07-17T07:05:41.9534030Z         Given some input Tensors with certain properties
2025-07-17T07:05:41.9534350Z         (sizes/strides/storage_offset/device), it specifies what the properties of
2025-07-17T07:05:41.9534640Z         the output Tensors are.
2025-07-17T07:05:41.9534840Z 
2025-07-17T07:05:41.9535010Z         Please see :func:`torch.library.impl_abstract` for more details.
2025-07-17T07:05:41.9535200Z 
2025-07-17T07:05:41.9535240Z         Args:
2025-07-17T07:05:41.9535420Z             fn (Callable): The function to register as the FakeTensor
2025-07-17T07:05:41.9535650Z                 implementation.
2025-07-17T07:05:41.9535760Z 
2025-07-17T07:05:41.9535810Z         Examples:
2025-07-17T07:05:41.9535940Z             >>> import torch
2025-07-17T07:05:41.9536100Z             >>> import numpy as np
2025-07-17T07:05:41.9536270Z             >>> from torch import Tensor
2025-07-17T07:05:41.9536440Z             >>>
2025-07-17T07:05:41.9536640Z             >>> # Example 1: an operator without data-dependent output shape
2025-07-17T07:05:41.9536950Z             >>> @torch.library.custom_op("mylib::linear", mutates_args=())
2025-07-17T07:05:41.9537240Z             >>> def linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor:
2025-07-17T07:05:41.9537490Z             >>>     return (x @ weight.t()) + bias
2025-07-17T07:05:41.9537680Z             >>>
2025-07-17T07:05:41.9537810Z             >>> @linear.register_fake
2025-07-17T07:05:41.9537990Z             >>> def _(x, weight, bias):
2025-07-17T07:05:41.9538170Z             >>>     assert x.dim() == 2
2025-07-17T07:05:41.9538370Z             >>>     assert weight.dim() == 2
2025-07-17T07:05:41.9538560Z             >>>     assert bias.dim() == 1
2025-07-17T07:05:41.9538760Z             >>>     assert x.shape[1] == weight.shape[1]
2025-07-17T07:05:41.9538980Z             >>>     assert weight.shape[0] == bias.shape[0]
2025-07-17T07:05:41.9539210Z             >>>     assert x.device == weight.device
2025-07-17T07:05:41.9539440Z             >>>     return x.new_empty(x.size(0), weight.size(0))
2025-07-17T07:05:41.9539640Z             >>>
2025-07-17T07:05:41.9539780Z             >>> x = torch.randn(2, 2)
2025-07-17T07:05:41.9539960Z             >>> weight = torch.randn(2, 2)
2025-07-17T07:05:41.9540150Z             >>> bias = torch.randn(2)
2025-07-17T07:05:41.9540360Z             >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-07-17T07:05:41.9540620Z             >>> out = torch.compile(linear, fullgraph=True)(x, weight, bias)
2025-07-17T07:05:41.9540900Z             >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-07-17T07:05:41.9541200Z             >>> assert torch.allclose(out, torch.nn.functional.linear(x, weight, bias))
2025-07-17T07:05:41.9541460Z             >>>
2025-07-17T07:05:41.9541640Z             >>> # Example 2: an operator with data-dependent output shape
2025-07-17T07:05:41.9541940Z             >>> @torch.library.custom_op("mylib::nonzero", mutates_args=())
2025-07-17T07:05:41.9542190Z             >>> def nonzero(x: Tensor) -> Tensor:
2025-07-17T07:05:41.9542390Z             >>>     x_np = x.cpu().numpy()
2025-07-17T07:05:41.9542590Z             >>>     res = np.stack(np.nonzero(x_np), axis=1)
2025-07-17T07:05:41.9542820Z             >>>     return torch.tensor(res, device=x.device)
2025-07-17T07:05:41.9543020Z             >>>
2025-07-17T07:05:41.9543210Z             >>> @nonzero.register_fake
2025-07-17T07:05:41.9543390Z             >>> def _(x):
2025-07-17T07:05:41.9543570Z             >>> # Number of nonzero-elements is data-dependent.
2025-07-17T07:05:41.9543840Z             >>> # Since we cannot peek at the data in an abstract impl,
2025-07-17T07:05:41.9544130Z             >>> # we use the ctx object to construct a new symint that
2025-07-17T07:05:41.9544370Z             >>> # represents the data-dependent size.
2025-07-17T07:05:41.9544580Z             >>>     ctx = torch.library.get_ctx()
2025-07-17T07:05:41.9544790Z             >>>     nnz = ctx.new_dynamic_size()
2025-07-17T07:05:41.9544980Z             >>>     shape = [nnz, x.dim()]
2025-07-17T07:05:41.9545200Z             >>>     result = x.new_empty(shape, dtype=torch.int64)
2025-07-17T07:05:41.9545410Z             >>>     return result
2025-07-17T07:05:41.9545560Z             >>>
2025-07-17T07:05:41.9545730Z             >>> x = torch.tensor([0, 1, 2, 0, 0, 1])
2025-07-17T07:05:41.9545990Z             >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-07-17T07:05:41.9546230Z             >>> out = torch.compile(nonzero, fullgraph=True)(x)
2025-07-17T07:05:41.9546470Z             >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-07-17T07:05:41.9546700Z             >>> assert torch.allclose(out, x.nonzero())
2025-07-17T07:05:41.9546840Z 
2025-07-17T07:05:41.9546880Z         
2025-07-17T07:05:41.9547260Z Original Error: IndentationError('expected an indented block after function definition on line 36', ('<source_block>', 37, 1, '_._ = None\n', 37, 2))
2025-07-17T07:05:41.9547620Z 
2025-07-17T07:05:41.9547660Z _._ = None
2025-07-17T07:05:41.9547770Z ^
2025-07-17T07:05:41.9548220Z msg = Cannot scrape callname=Conv1d in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py line=354.
2025-07-17T07:05:41.9548830Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:41.9549180Z Applies a 1D convolution over a quantized input signal composed of
2025-07-17T07:05:41.9549440Z     several quantized input planes.
2025-07-17T07:05:41.9549560Z 
2025-07-17T07:05:41.9549690Z     For details on input arguments, parameters, and implementation see
2025-07-17T07:05:41.9549940Z     :class:`~torch.nn.Conv1d`.
2025-07-17T07:05:41.9550050Z 
2025-07-17T07:05:41.9550100Z     .. note::
2025-07-17T07:05:41.9550300Z         Only `zeros` is supported for the :attr:`padding_mode` argument.
2025-07-17T07:05:41.9550480Z 
2025-07-17T07:05:41.9550530Z     .. note::
2025-07-17T07:05:41.9550710Z         Only `torch.quint8` is supported for the input data type.
2025-07-17T07:05:41.9550880Z 
2025-07-17T07:05:41.9550880Z 
2025-07-17T07:05:41.9550930Z     Attributes:
2025-07-17T07:05:41.9551140Z         weight (Tensor):     packed tensor derived from the learnable weight
2025-07-17T07:05:41.9551390Z                              parameter.
2025-07-17T07:05:41.9551600Z         scale (Tensor):      scalar for the output scale
2025-07-17T07:05:41.9551850Z         zero_point (Tensor): scalar for the output zero point
2025-07-17T07:05:41.9552020Z 
2025-07-17T07:05:41.9552110Z     See :class:`~torch.nn.Conv1d` for other attributes.
2025-07-17T07:05:41.9552270Z 
2025-07-17T07:05:41.9552320Z     Examples::
2025-07-17T07:05:41.9552390Z 
2025-07-17T07:05:41.9552490Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_QENGINE)
2025-07-17T07:05:41.9552720Z         >>> m = nn.quantized.Conv1d(16, 33, 3, stride=2)
2025-07-17T07:05:41.9552930Z         >>> input = torch.randn(20, 16, 100)
2025-07-17T07:05:41.9553120Z         >>> # quantize input to quint8
2025-07-17T07:05:41.9553300Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:41.9553540Z         >>> q_input = torch.quantize_per_tensor(input, scale=1.0, zero_point=0,
2025-07-17T07:05:41.9553810Z         ...                                     dtype=torch.quint8)
2025-07-17T07:05:41.9554010Z         >>> output = m(q_input)
2025-07-17T07:05:41.9554120Z 
2025-07-17T07:05:41.9554160Z     
2025-07-17T07:05:41.9554400Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:41.9554620Z 
2025-07-17T07:05:41.9555000Z msg = Cannot scrape callname=LSTM in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/rnn.py line=12.
2025-07-17T07:05:41.9555630Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:41.9555930Z A quantized long short-term memory (LSTM).
2025-07-17T07:05:41.9556060Z 
2025-07-17T07:05:41.9556230Z     For the description and the argument types, please, refer to :class:`~torch.nn.LSTM`
2025-07-17T07:05:41.9556460Z 
2025-07-17T07:05:41.9556510Z     Attributes:
2025-07-17T07:05:41.9556660Z         layers : instances of the `_LSTMLayer`
2025-07-17T07:05:41.9556790Z 
2025-07-17T07:05:41.9556840Z     .. note::
2025-07-17T07:05:41.9557060Z         To access the weights and biases, you need to access them per layer.
2025-07-17T07:05:41.9557380Z         See examples in :class:`~torch.ao.nn.quantizable.LSTM`
2025-07-17T07:05:41.9557550Z 
2025-07-17T07:05:41.9557600Z     Examples::
2025-07-17T07:05:41.9557730Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:41.9557900Z         >>> custom_module_config = {
2025-07-17T07:05:41.9558100Z         ...     'float_to_observed_custom_module_class': {
2025-07-17T07:05:41.9558330Z         ...         nn.LSTM: nn.quantizable.LSTM,
2025-07-17T07:05:41.9558510Z         ...     },
2025-07-17T07:05:41.9558670Z         ...     'observed_to_quantized_custom_module_class': {
2025-07-17T07:05:41.9558920Z         ...         nn.quantizable.LSTM: nn.quantized.LSTM,
2025-07-17T07:05:41.9559110Z         ...     }
2025-07-17T07:05:41.9559230Z         ... }
2025-07-17T07:05:41.9559430Z         >>> tq.prepare(model, prepare_custom_module_class=custom_module_config)
2025-07-17T07:05:41.9559760Z         >>> tq.convert(model, convert_custom_module_class=custom_module_config)
2025-07-17T07:05:41.9559990Z     
2025-07-17T07:05:41.9560200Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:41.9560420Z 
2025-07-17T07:05:41.9560870Z msg = Cannot scrape callname=DTypeConfig in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/backend_config/backend_config.py line=181.
2025-07-17T07:05:41.9561540Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:41.9561770Z 
2025-07-17T07:05:41.9561920Z Config object that specifies the supported data types passed as arguments to
2025-07-17T07:05:41.9562270Z quantize ops in the reference model spec, for input and output activations,
2025-07-17T07:05:41.9562530Z weights, and biases.
2025-07-17T07:05:41.9562620Z 
2025-07-17T07:05:41.9562710Z For example, consider the following reference model:
2025-07-17T07:05:41.9562870Z 
2025-07-17T07:05:41.9562970Z   quant1 - [dequant1 - fp32_linear - quant2] - dequant2
2025-07-17T07:05:41.9563120Z 
2025-07-17T07:05:41.9563260Z The pattern in the square brackets refers to the reference pattern of
2025-07-17T07:05:41.9563590Z statically quantized linear. Setting the input dtype as `torch.quint8`
2025-07-17T07:05:41.9563940Z in the DTypeConfig means we pass in `torch.quint8` as the dtype argument
2025-07-17T07:05:41.9564270Z to the first quantize op (quant1). Similarly, setting the output dtype as
2025-07-17T07:05:41.9564600Z `torch.quint8` means we pass in `torch.quint8` as the dtype argument to
2025-07-17T07:05:41.9564860Z the second quantize op (quant2).
2025-07-17T07:05:41.9564980Z 
2025-07-17T07:05:41.9565110Z Note that the dtype here does not refer to the interface dtypes of the
2025-07-17T07:05:41.9565420Z op. For example, the "input dtype" here is not the dtype of the input
2025-07-17T07:05:41.9565740Z tensor passed to the quantized linear op. Though it can still be the
2025-07-17T07:05:41.9566050Z same as the interface dtype, this is not always the case, e.g. the
2025-07-17T07:05:41.9566420Z interface dtype is fp32 in dynamic quantization but the "input dtype"
2025-07-17T07:05:41.9566750Z specified in the DTypeConfig would still be quint8. The semantics of
2025-07-17T07:05:41.9567070Z dtypes here are the same as the semantics of the dtypes specified in
2025-07-17T07:05:41.9567330Z the observers.
2025-07-17T07:05:41.9567410Z 
2025-07-17T07:05:41.9567540Z These dtypes are matched against the ones specified in the user's
2025-07-17T07:05:41.9567850Z QConfig. If there is a match, and the QConfig satisfies the constraints
2025-07-17T07:05:41.9568180Z specified in the DTypeConfig (if any), then we will quantize the given
2025-07-17T07:05:41.9568500Z pattern using this DTypeConfig. Otherwise, the QConfig is ignored and
2025-07-17T07:05:41.9568770Z the pattern will not be quantized.
2025-07-17T07:05:41.9568890Z 
2025-07-17T07:05:41.9568940Z Example usage::
2025-07-17T07:05:41.9569020Z 
2025-07-17T07:05:41.9569080Z     >>> # xdoctest: +SKIP(failing)
2025-07-17T07:05:41.9575230Z     >>> dtype_config1 = DTypeConfig(
2025-07-17T07:05:41.9575470Z     ...     input_dtype=torch.quint8,
2025-07-17T07:05:41.9575650Z     ...     output_dtype=torch.quint8,
2025-07-17T07:05:41.9575830Z     ...     weight_dtype=torch.qint8,
2025-07-17T07:05:41.9576020Z     ...     bias_dtype=torch.float)
2025-07-17T07:05:41.9576140Z 
2025-07-17T07:05:41.9576200Z     >>> dtype_config2 = DTypeConfig(
2025-07-17T07:05:41.9576400Z     ...     input_dtype=DTypeWithConstraints(
2025-07-17T07:05:41.9576600Z     ...         dtype=torch.quint8,
2025-07-17T07:05:41.9576780Z     ...         quant_min_lower_bound=0,
2025-07-17T07:05:41.9576970Z     ...         quant_max_upper_bound=255,
2025-07-17T07:05:41.9577140Z     ...     ),
2025-07-17T07:05:41.9577290Z     ...     output_dtype=DTypeWithConstraints(
2025-07-17T07:05:41.9577490Z     ...         dtype=torch.quint8,
2025-07-17T07:05:41.9577660Z     ...         quant_min_lower_bound=0,
2025-07-17T07:05:41.9577840Z     ...         quant_max_upper_bound=255,
2025-07-17T07:05:41.9578010Z     ...     ),
2025-07-17T07:05:41.9578160Z     ...     weight_dtype=DTypeWithConstraints(
2025-07-17T07:05:41.9578350Z     ...         dtype=torch.qint8,
2025-07-17T07:05:41.9578530Z     ...         quant_min_lower_bound=-128,
2025-07-17T07:05:41.9578730Z     ...         quant_max_upper_bound=127,
2025-07-17T07:05:41.9578900Z     ...     ),
2025-07-17T07:05:41.9579030Z     ...     bias_dtype=torch.float)
2025-07-17T07:05:41.9579150Z 
2025-07-17T07:05:41.9579220Z     >>> dtype_config1.input_dtype
2025-07-17T07:05:41.9579380Z     torch.quint8
2025-07-17T07:05:41.9579460Z 
2025-07-17T07:05:41.9579520Z     >>> dtype_config2.input_dtype
2025-07-17T07:05:41.9579670Z     torch.quint8
2025-07-17T07:05:41.9579760Z 
2025-07-17T07:05:41.9579840Z     >>> dtype_config2.input_dtype_with_constraints
2025-07-17T07:05:41.9580300Z     DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=0, quant_max_upper_bound=255, scale_min_lower_bound=None, scale_max_upper_bound=None)
2025-07-17T07:05:41.9580680Z 
2025-07-17T07:05:41.9580830Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:42.0253630Z 
2025-07-17T07:05:42.0254510Z msg = Cannot scrape callname=ModelReportVisualizer.generate_filtered_tables in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=301.
2025-07-17T07:05:42.0255440Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:42.0255680Z 
2025-07-17T07:05:42.0255850Z Takes in optional filter values and generates two tables with desired information.
2025-07-17T07:05:42.0256090Z 
2025-07-17T07:05:42.0256220Z The generated tables are presented in both a list-of-lists format
2025-07-17T07:05:42.0256420Z 
2025-07-17T07:05:42.0256550Z The reason for the two tables are that they handle different things:
2025-07-17T07:05:42.0256850Z 1.) the first table handles all tensor level information
2025-07-17T07:05:42.0257160Z 2.) the second table handles and displays all channel based information
2025-07-17T07:05:42.0257560Z 
2025-07-17T07:05:42.0257760Z The reasoning for this is that having all the info in one table can make it ambiguous which collected
2025-07-17T07:05:42.0258230Z     statistics are global, and which are actually per-channel, so it's better to split it up into two
2025-07-17T07:05:42.0258830Z     tables. This also makes the information much easier to digest given the plethora of statistics collected
2025-07-17T07:05:42.0259120Z 
2025-07-17T07:05:42.0259170Z Tensor table columns:
2025-07-17T07:05:42.0259390Z     idx  layer_fqn  feature_1   feature_2   feature_3   .... feature_n
2025-07-17T07:05:42.0259690Z     ----  ---------  ---------   ---------   ---------        ---------
2025-07-17T07:05:42.0259870Z 
2025-07-17T07:05:42.0259930Z Per-Channel table columns:
2025-07-17T07:05:42.0260180Z     idx  layer_fqn  channel  feature_1   feature_2   feature_3   .... feature_n
2025-07-17T07:05:42.0260560Z     ----  ---------  -------  ---------   ---------   ---------        ---------
2025-07-17T07:05:42.0260780Z 
2025-07-17T07:05:42.0260830Z Args:
2025-07-17T07:05:42.0261060Z     feature_filter (str, optional): Filters the features presented to only those that
2025-07-17T07:05:42.0261360Z         contain this filter substring
2025-07-17T07:05:42.0261610Z         Default = "", results in all the features being printed
2025-07-17T07:05:42.0261940Z     module_fqn_filter (str, optional): Only includes modules that contains this string
2025-07-17T07:05:42.0262320Z         Default = "", results in all the modules in the reports to be visible in the table
2025-07-17T07:05:42.0262540Z 
2025-07-17T07:05:42.0262610Z Returns a dictionary with two keys:
2025-07-17T07:05:42.0262850Z     (Dict[str, Tuple[List, List]]) A dict containing two keys:
2025-07-17T07:05:42.0263100Z     "tensor_level_info", "channel_level_info"
2025-07-17T07:05:42.0263310Z         Each key maps to a tuple with:
2025-07-17T07:05:42.0263510Z             A list of the headers of each table
2025-07-17T07:05:42.0263770Z             A list of lists containing the table information row by row
2025-07-17T07:05:42.0264060Z             The 0th index row will contain the headers of the columns
2025-07-17T07:05:42.0264320Z             The rest of the rows will contain data
2025-07-17T07:05:42.0264460Z 
2025-07-17T07:05:42.0264520Z Example Use:
2025-07-17T07:05:42.0264670Z     >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:42.0264900Z     >>> mod_report_visualizer.generate_filtered_tables(
2025-07-17T07:05:42.0265190Z     ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-07-17T07:05:42.0265540Z     ... )  # generates table with per_channel_min info for all modules in block 1 of the model
2025-07-17T07:05:42.0265770Z 
2025-07-17T07:05:42.0265930Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:42.0266150Z 
2025-07-17T07:05:42.0266740Z msg = Cannot scrape callname=ModelReportVisualizer.generate_table_visualization in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=399.
2025-07-17T07:05:42.0267540Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:42.0267770Z 
2025-07-17T07:05:42.0267930Z Takes in optional filter values and prints out formatted tables of the information.
2025-07-17T07:05:42.0268160Z 
2025-07-17T07:05:42.0268360Z The reason for the two tables printed out instead of one large one are that they handle different things:
2025-07-17T07:05:42.0268760Z 1.) the first table handles all tensor level information
2025-07-17T07:05:42.0269050Z 2.) the second table handles and displays all channel based information
2025-07-17T07:05:42.0269250Z 
2025-07-17T07:05:42.0269440Z The reasoning for this is that having all the info in one table can make it ambiguous which collected
2025-07-17T07:05:42.0269880Z     statistics are global, and which are actually per-channel, so it's better to split it up into two
2025-07-17T07:05:42.0270420Z     tables. This also makes the information much easier to digest given the plethora of statistics collected
2025-07-17T07:05:42.0270690Z 
2025-07-17T07:05:42.0270750Z Tensor table columns:
2025-07-17T07:05:42.0270990Z  idx  layer_fqn  feature_1   feature_2   feature_3   .... feature_n
2025-07-17T07:05:42.0271260Z ----  ---------  ---------   ---------   ---------        ---------
2025-07-17T07:05:42.0271430Z 
2025-07-17T07:05:42.0271490Z Per-Channel table columns:
2025-07-17T07:05:42.0271590Z 
2025-07-17T07:05:42.0271730Z  idx  layer_fqn  channel  feature_1   feature_2   feature_3   .... feature_n
2025-07-17T07:05:42.0272030Z ----  ---------  -------  ---------   ---------   ---------        ---------
2025-07-17T07:05:42.0272200Z 
2025-07-17T07:05:42.0272240Z Args:
2025-07-17T07:05:42.0272460Z     feature_filter (str, optional): Filters the features presented to only those that
2025-07-17T07:05:42.0272780Z         contain this filter substring
2025-07-17T07:05:42.0273030Z         Default = "", results in all the features being printed
2025-07-17T07:05:42.0273350Z     module_fqn_filter (str, optional): Only includes modules that contains this string
2025-07-17T07:05:42.0273730Z         Default = "", results in all the modules in the reports to be visible in the table
2025-07-17T07:05:42.0273940Z 
2025-07-17T07:05:42.0274000Z Example Use:
2025-07-17T07:05:42.0274150Z     >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:42.0274390Z     >>> mod_report_visualizer.generate_table_visualization(
2025-07-17T07:05:42.0274670Z     ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-07-17T07:05:42.0274900Z     ... )
2025-07-17T07:05:42.0275090Z     >>> # prints out neatly formatted table with per_channel_min info
2025-07-17T07:05:42.0275340Z     >>> # for all modules in block 1 of the model
2025-07-17T07:05:42.0275480Z 
2025-07-17T07:05:42.0275630Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:42.0275850Z 
2025-07-17T07:05:42.0276440Z msg = Cannot scrape callname=ModelReportVisualizer.generate_plot_visualization in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=564.
2025-07-17T07:05:42.0277230Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:42.0277450Z 
2025-07-17T07:05:42.0277600Z Takes in a feature and optional module_filter and plots of the desired data.
2025-07-17T07:05:42.0277810Z 
2025-07-17T07:05:42.0277970Z For per channel features, it averages the value across the channels and plots a point
2025-07-17T07:05:42.0278360Z per module. The reason for this is that for models with hundreds of channels, it can
2025-07-17T07:05:42.0278740Z be hard to differentiate one channel line from another, and so the point of generating
2025-07-17T07:05:42.0279130Z a single average point per module is to give a sense of general trends that encourage
2025-07-17T07:05:42.0279410Z further deep dives.
2025-07-17T07:05:42.0279500Z 
2025-07-17T07:05:42.0279540Z Note:
2025-07-17T07:05:42.0279760Z     Only features in the report that have tensor value data are plottable by this class
2025-07-17T07:05:42.0280080Z     When the tensor information is plotted, it will plot:
2025-07-17T07:05:42.0280330Z         idx as the x val, feature value as the y_val
2025-07-17T07:05:42.0280570Z     When the channel information is plotted, it will plot:
2025-07-17T07:05:42.0280890Z         the first idx of each module as the x val, feature value as the y_val [for each channel]
2025-07-17T07:05:42.0281260Z         The reason for this is that we want to be able to compare values across the
2025-07-17T07:05:42.0281630Z         channels for same layer, and it will be hard if values are staggered by idx
2025-07-17T07:05:42.0281950Z         This means each module is represented by only 1 x value
2025-07-17T07:05:42.0282160Z Args:
2025-07-17T07:05:42.0282420Z     feature_filter (str): Filters the features presented to only those that
2025-07-17T07:05:42.0282690Z         contain this filter substring
2025-07-17T07:05:42.0282980Z     module_fqn_filter (str, optional): Only includes modules that contains this string
2025-07-17T07:05:42.0283390Z         Default = "", results in all the modules in the reports to be visible in the table
2025-07-17T07:05:42.0283600Z 
2025-07-17T07:05:42.0283650Z Example Use:
2025-07-17T07:05:42.0283800Z     >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:42.0284030Z     >>> mod_report_visualizer.generate_plot_visualization(
2025-07-17T07:05:42.0284320Z     ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-07-17T07:05:42.0284550Z     ... )
2025-07-17T07:05:42.0284730Z     >>> # outputs line plot of per_channel_min information for all
2025-07-17T07:05:42.0285010Z     >>> # modules in block1 of model each channel gets it's own line,
2025-07-17T07:05:42.0285320Z     >>> # and it's plotted across the in-order modules on the x-axis
2025-07-17T07:05:42.0285500Z 
2025-07-17T07:05:42.0285660Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:42.0285880Z 
2025-07-17T07:05:42.0286470Z msg = Cannot scrape callname=ModelReportVisualizer.generate_histogram_visualization in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=643.
2025-07-17T07:05:42.0287280Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:42.0287500Z 
2025-07-17T07:05:42.0287670Z Takes in a feature and optional module_filter and plots the histogram of desired data.
2025-07-17T07:05:42.0287900Z 
2025-07-17T07:05:42.0287940Z Note:
2025-07-17T07:05:42.0288160Z     Only features in the report that have tensor value data can be viewed as a histogram
2025-07-17T07:05:42.0288550Z     If you want to plot a histogram from all the channel values of a specific feature for
2025-07-17T07:05:42.0288930Z         a specific model, make sure to specify both the model and the feature properly
2025-07-17T07:05:42.0289280Z         in the filters and you should be able to see a distribution of the channel data
2025-07-17T07:05:42.0289500Z 
2025-07-17T07:05:42.0289550Z Args:
2025-07-17T07:05:42.0289770Z     feature_filter (str, optional): Filters the features presented to only those that
2025-07-17T07:05:42.0290050Z         contain this filter substring
2025-07-17T07:05:42.0290270Z         Default = "", results in all the features being printed
2025-07-17T07:05:42.0290590Z     module_fqn_filter (str, optional): Only includes modules that contains this string
2025-07-17T07:05:42.0290950Z         Default = "", results in all the modules in the reports to be visible in the table
2025-07-17T07:05:42.0291300Z     num_bins (int, optional): The number of bins to create the histogram with
2025-07-17T07:05:42.0291620Z         Default = 10, the values will be split into 10 equal sized bins
2025-07-17T07:05:42.0291800Z 
2025-07-17T07:05:42.0291850Z Example Use:
2025-07-17T07:05:42.0291980Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:42.0292250Z     >>> mod_report_visualizer.generategenerate_histogram_visualization_plot_visualization(
2025-07-17T07:05:42.0292620Z     ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-07-17T07:05:42.0292840Z     ... )
2025-07-17T07:05:42.0293070Z     # outputs histogram of per_channel_min information for all modules in block1 of model
2025-07-17T07:05:42.0293450Z         information is gathered across all channels for all modules in block 1 for the
2025-07-17T07:05:42.0293800Z         per_channel_min and is displayed in a histogram of equally sized bins
2025-07-17T07:05:42.0294000Z 
2025-07-17T07:05:42.0294150Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:42.3838330Z 
2025-07-17T07:05:42.3839270Z msg = Cannot scrape callname=ModelReport in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report.py line=24.
2025-07-17T07:05:42.3840010Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:42.3840250Z 
2025-07-17T07:05:42.3840440Z The ModelReport class aims to provide users an easy way to diagnose issues that they run into
2025-07-17T07:05:42.3840960Z with their models. The class works with all traceable GraphModules to help diagnose issues,
2025-07-17T07:05:42.3841410Z though the requirements on the type of model more-so depends on the specific report the user
2025-07-17T07:05:42.3841850Z is trying to generate. With respect to the reports, the ModelReport class is initialized with
2025-07-17T07:05:42.3842270Z a set of Detector classes, each of which generate reports on quantization configuration
2025-07-17T07:05:42.3842560Z issues a use might have.
2025-07-17T07:05:42.3842660Z 
2025-07-17T07:05:42.3842740Z Currently supports generating reports on:
2025-07-17T07:05:42.3843090Z - Suggestions for per-channel vs. per-tensor quantization (nn.Module)
2025-07-17T07:05:42.3843510Z - Suggestions for dynamic vs static quantization for linear layers (Graph Modules)
2025-07-17T07:05:42.3843910Z - Suggestions for input-weight equalization for linear and conv layers (Graph Modules)
2025-07-17T07:05:42.3844280Z - Suggestions for outlier detection for all layers (Graph Modules)
2025-07-17T07:05:42.3844500Z 
2025-07-17T07:05:42.3844740Z The ModelReport class has the primary functionality of inserting observers (primarily the ModelReportObserver)
2025-07-17T07:05:42.3845270Z where needed for each detector to gather the information it needs, and then after calibration, the ModelReport
2025-07-17T07:05:42.3845760Z class compiles the report generated by each Detector class into a single report to return to the user. It also
2025-07-17T07:05:42.3846180Z has the capability to remove all the observers it inserted as well.
2025-07-17T07:05:42.3846370Z 
2025-07-17T07:05:42.3846550Z * :attr:`_model` The model we wish to generate the report for. Must be a traceable GraphModule
2025-07-17T07:05:42.3846790Z 
2025-07-17T07:05:42.3847010Z * :attr:`_desired_report_detectors` The set of Detectors representing desired reports from the ModelReport class
2025-07-17T07:05:42.3847480Z     Make sure that these are all unique types of detectors [do not have more than 1 of the same class]
2025-07-17T07:05:42.3847730Z 
2025-07-17T07:05:42.3847910Z * :attr:`_desired_detector_names` The set of detector names of the _desired_report_detectors.
2025-07-17T07:05:42.3848290Z     This set is generated by calling the get_detector_name() of each detector
2025-07-17T07:05:42.3848550Z 
2025-07-17T07:05:42.3848750Z * :attr:`_detector_name_to_observer_fqns` The mapping from each detector to fqns of observers of interest
2025-07-17T07:05:42.3849200Z     The purpose of this is to keep track of what observers were inserted for each detector, so that they
2025-07-17T07:05:42.3849520Z     can be removed at the end if desired
2025-07-17T07:05:42.3849650Z 
2025-07-17T07:05:42.3849840Z * :attr:`_prepared_flag` A boolean flag that keeps track of whether we have prepared the model or not
2025-07-17T07:05:42.3850270Z     This is to ensure we only insert observers once with the ModelReport instance
2025-07-17T07:05:42.3850480Z 
2025-07-17T07:05:42.3850630Z * :attr:`_removed_observers` A boolean to track if we have removed observers already
2025-07-17T07:05:42.3851030Z     The purpose is to ensure we don't attempt to remove observers twice with the same ModelReport
2025-07-17T07:05:42.3851460Z     instance. This also allows the functionality where we can generate the report multiple times
2025-07-17T07:05:42.3851810Z     as long as we haven't removed the observers yet.
2025-07-17T07:05:42.3851960Z 
2025-07-17T07:05:42.3852000Z Note:
2025-07-17T07:05:42.3852250Z     This class was initially designed to work with the Fx Graph Mode workflow in mind. However,
2025-07-17T07:05:42.3852680Z     full functionality is available as long as there is a traceable GraphModule that is being used.
2025-07-17T07:05:42.3853140Z     One method to get a traceable GraphModule without going through the Fx workflow is to use
2025-07-17T07:05:42.3853450Z     the QuantizationTracer class.
2025-07-17T07:05:42.3853570Z 
2025-07-17T07:05:42.3853660Z General Flow for Fx workflow:
2025-07-17T07:05:42.3854010Z 1.) Initialize ModelReport object with reports of interest by passing in initialized detector objects and model
2025-07-17T07:05:42.3854380Z 2.) Prepare your model with prepare_fx
2025-07-17T07:05:42.3854650Z 3.) Call model_report.prepare_detailed_calibration to add relevant observers
2025-07-17T07:05:42.3854930Z 4.) Calibrate your model with data
2025-07-17T07:05:42.3855260Z 5.) Call model_report.generate_report on your model to generate report and optionally remove added observers
2025-07-17T07:05:42.3855580Z Optional
2025-07-17T07:05:42.3855810Z     6.) Call model_report.generate_visualizer to get a ModelReportVisualizer instance
2025-07-17T07:05:42.3856360Z     7.) To help in parsing report information and debugging, view report info as a:
2025-07-17T07:05:42.3856690Z         - Table
2025-07-17T07:05:42.3856830Z         - Histogram
2025-07-17T07:05:42.3856970Z         - Line plot
2025-07-17T07:05:42.3857240Z 8.) Call model_report.generate_qconfigs to generate the qconfigs based on the report suggestions
2025-07-17T07:05:42.3857490Z 
2025-07-17T07:05:42.3857560Z Example (with QuantizationTracer):
2025-07-17T07:05:42.3857740Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:42.3857900Z     >>> # get the necessary qconfig
2025-07-17T07:05:42.3858080Z     >>> config = PrepareCustomConfig()
2025-07-17T07:05:42.3858310Z     >>> skipped_module_names, skipped_module_classes = (
2025-07-17T07:05:42.3858560Z     ...     get_skipped_module_name_and_classes(config, False)
2025-07-17T07:05:42.3858770Z     ... )
2025-07-17T07:05:42.3858840Z 
2025-07-17T07:05:42.3858930Z     >>> # initialize our model and get GraphModule
2025-07-17T07:05:42.3859130Z     >>> model = SomeModel()
2025-07-17T07:05:42.3859380Z     >>> tracer = QuantizationTracer(skipped_module_names, skipped_module_classes)
2025-07-17T07:05:42.3859700Z     >>> graph_module = GraphModule(model, tracer.trace(model))
2025-07-17T07:05:42.3859880Z 
2025-07-17T07:05:42.3859970Z     >>> # get our set of detectors and ModelReport instance
2025-07-17T07:05:42.3860180Z     >>> detector_set = set(
2025-07-17T07:05:42.3860330Z     ...     [
2025-07-17T07:05:42.3860490Z     ...         DynamicStaticDetector(tolerance=0.5),
2025-07-17T07:05:42.3860760Z     ...         InputWeightEqualizationDetector(ratio_threshold=0.7),
2025-07-17T07:05:42.3860980Z     ...     ]
2025-07-17T07:05:42.3861100Z     ... )
2025-07-17T07:05:42.3861290Z     >>> tracer_reporter = ModelReport(graph_module, tracer_detector_set)
2025-07-17T07:05:42.3861480Z 
2025-07-17T07:05:42.3861580Z     >>> # now we insert the observers and calibrate the model
2025-07-17T07:05:42.3861900Z     >>> tracer_model_with_observers = tracer_reporter.prepare_detailed_calibration()
2025-07-17T07:05:42.3862200Z     >>> for i in range(num_callibration_batches):
2025-07-17T07:05:42.3862420Z     >>>     example_input = get_callibration_input()
2025-07-17T07:05:42.3862650Z     >>>     tracer_model_with_observers(example_input)
2025-07-17T07:05:42.3862800Z 
2025-07-17T07:05:42.3862960Z     >>> # finally we generate the reports and optionally remove the observers we inserted
2025-07-17T07:05:42.3863280Z     >>> reports = tracer_reporter.generate_model_report(
2025-07-17T07:05:42.3863490Z     ...     remove_inserted_observers=True
2025-07-17T07:05:42.3863670Z     ... )
2025-07-17T07:05:42.3863740Z 
2025-07-17T07:05:42.3863870Z     >>> # Optional: we can generate the qconfig mapping based on the suggestions
2025-07-17T07:05:42.3864160Z     >>> qconfigs = model_report.generate_qconfig_mapping()
2025-07-17T07:05:42.3864320Z 
2025-07-17T07:05:42.3864470Z     >>> # Optional: we can generate the equalization mapping based on the suggestions
2025-07-17T07:05:42.3864790Z     >>> qconfigs = model_report.generate_equalization_mapping()
2025-07-17T07:05:42.3865020Z 
2025-07-17T07:05:42.3865230Z     >>> # Optional: we get a ModelReportVisualizer instance to do any visualizations desired
2025-07-17T07:05:42.3865600Z     >>> model_report_visualizer = tracer_reporter.generate_visualizer()
2025-07-17T07:05:42.3865810Z 
2025-07-17T07:05:42.3865810Z 
2025-07-17T07:05:42.3865970Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:42.3866180Z 
2025-07-17T07:05:42.3866660Z msg = Cannot scrape callname=BaseSparsifier.squash_mask in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py line=229.
2025-07-17T07:05:42.3867350Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:42.3867670Z Squashes the sparse masks into the appropriate tensors.
2025-07-17T07:05:42.3867840Z 
2025-07-17T07:05:42.3867990Z         If either the `params_to_keep` or `params_to_keep_per_layer` is set,
2025-07-17T07:05:42.3868320Z         the module will have a `sparse_params` dict attached to it.
2025-07-17T07:05:42.3868500Z 
2025-07-17T07:05:42.3868540Z         Args:
2025-07-17T07:05:42.3868730Z             params_to_keep: List of keys to save in the module or a dict
2025-07-17T07:05:42.3869020Z                             representing the modules and keys that will have
2025-07-17T07:05:42.3869260Z                             sparsity parameters saved
2025-07-17T07:05:42.3869530Z             params_to_keep_per_layer: Dict to specify the params that should be
2025-07-17T07:05:42.3869820Z                             saved for specific layers. The keys in the dict
2025-07-17T07:05:42.3870080Z                             should be the module fqn, while the values should
2025-07-17T07:05:42.3870340Z                             be a list of strings with the names of the variables
2025-07-17T07:05:42.3870580Z                             to save in the `sparse_params`
2025-07-17T07:05:42.3877350Z 
2025-07-17T07:05:42.3877410Z         Examples:
2025-07-17T07:05:42.3877590Z             >>> # xdoctest: +SKIP("locals are undefined")
2025-07-17T07:05:42.3877820Z             >>> # Don't save any sparse params
2025-07-17T07:05:42.3878020Z             >>> sparsifier.squash_mask()
2025-07-17T07:05:42.3878230Z             >>> hasattr(model.submodule1, "sparse_params")
2025-07-17T07:05:42.3878430Z             False
2025-07-17T07:05:42.3878510Z 
2025-07-17T07:05:42.3878580Z             >>> # Keep sparse params per layer
2025-07-17T07:05:42.3878780Z             >>> sparsifier.squash_mask(
2025-07-17T07:05:42.3878970Z             ...     params_to_keep_per_layer={
2025-07-17T07:05:42.3879180Z             ...         "submodule1.linear1": ("foo", "bar"),
2025-07-17T07:05:42.3879410Z             ...         "submodule2.linear42": ("baz",),
2025-07-17T07:05:42.3879610Z             ...     }
2025-07-17T07:05:42.3879740Z             ... )
2025-07-17T07:05:42.3879920Z             >>> print(model.submodule1.linear1.sparse_params)
2025-07-17T07:05:42.3880140Z             {'foo': 42, 'bar': 24}
2025-07-17T07:05:42.3880350Z             >>> print(model.submodule2.linear42.sparse_params)
2025-07-17T07:05:42.3880560Z             {'baz': 0.1}
2025-07-17T07:05:42.3880660Z 
2025-07-17T07:05:42.3880740Z             >>> # Keep sparse params for all layers
2025-07-17T07:05:42.3880980Z             >>> sparsifier.squash_mask(params_to_keep=("foo", "bar"))
2025-07-17T07:05:42.3881250Z             >>> print(model.submodule1.linear1.sparse_params)
2025-07-17T07:05:42.3881460Z             {'foo': 42, 'bar': 24}
2025-07-17T07:05:42.3881670Z             >>> print(model.submodule2.linear42.sparse_params)
2025-07-17T07:05:42.3881880Z             {'foo': 42, 'bar': 24}
2025-07-17T07:05:42.3882000Z 
2025-07-17T07:05:42.3882120Z             >>> # Keep some sparse params for all layers, and specific ones for
2025-07-17T07:05:42.3882360Z             >>> # some other layers
2025-07-17T07:05:42.3882530Z             >>> sparsifier.squash_mask(
2025-07-17T07:05:42.3882730Z             ...     params_to_keep=("foo", "bar"),
2025-07-17T07:05:42.3883060Z             ...     params_to_keep_per_layer={"submodule2.linear42": ("baz",)},
2025-07-17T07:05:42.3883280Z             ... )
2025-07-17T07:05:42.3883460Z             >>> print(model.submodule1.linear1.sparse_params)
2025-07-17T07:05:42.3883710Z             {'foo': 42, 'bar': 24}
2025-07-17T07:05:42.3883920Z             >>> print(model.submodule2.linear42.sparse_params)
2025-07-17T07:05:42.3884150Z             {'foo': 42, 'bar': 24, 'baz': 0.1}
2025-07-17T07:05:42.3884320Z         
2025-07-17T07:05:42.3884540Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:42.4697320Z 
2025-07-17T07:05:42.4698210Z msg = Cannot scrape callname=ActivationSparsifier in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/pruning/_experimental/activation_sparsifier/activation_sparsifier.py line=16.
2025-07-17T07:05:42.4699240Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:42.4699510Z 
2025-07-17T07:05:42.4699670Z The Activation sparsifier class aims to sparsify/prune activations in a neural
2025-07-17T07:05:42.4700070Z network. The idea is to attach the sparsifier to a layer (or layers) and it
2025-07-17T07:05:42.4700440Z zeroes out the activations based on the mask_fn (or sparsification function)
2025-07-17T07:05:42.4700710Z input by the user.
2025-07-17T07:05:42.4700950Z The mask_fn is applied once all the inputs are aggregated and reduced i.e.
2025-07-17T07:05:42.4701240Z mask = mask_fn(reduce_fn(aggregate_fn(activations)))
2025-07-17T07:05:42.4701390Z 
2025-07-17T07:05:42.4701450Z Note::
2025-07-17T07:05:42.4701710Z     The sparsification mask is computed on the input **before it goes through the attached layer**.
2025-07-17T07:05:42.4701970Z 
2025-07-17T07:05:42.4702020Z Args:
2025-07-17T07:05:42.4702130Z     model (nn.Module):
2025-07-17T07:05:42.4702360Z         The model whose layers will be sparsified. The layers that needs to be
2025-07-17T07:05:42.4702710Z         sparsified should be added separately using the register_layer() function
2025-07-17T07:05:42.4702990Z     aggregate_fn (Optional, Callable):
2025-07-17T07:05:42.4703280Z         default aggregate_fn that is used if not specified while registering the layer.
2025-07-17T07:05:42.4703600Z         specifies how inputs should be aggregated over time.
2025-07-17T07:05:42.4703940Z         The aggregate_fn should usually take 2 torch tensors and return the aggregated tensor.
2025-07-17T07:05:42.4704220Z         Example
2025-07-17T07:05:42.4704410Z             def add_agg_fn(tensor1, tensor2):  return tensor1 + tensor2
2025-07-17T07:05:42.4704640Z             reduce_fn (Optional, Callable):
2025-07-17T07:05:42.4704930Z                 default reduce_fn that is used if not specified while registering the layer.
2025-07-17T07:05:42.4705290Z                 reduce_fn will be called on the aggregated tensor i.e. the tensor obtained after
2025-07-17T07:05:42.4705580Z                 calling agg_fn() on all inputs.
2025-07-17T07:05:42.4705770Z                 Example
2025-07-17T07:05:42.4705990Z             def mean_reduce_fn(agg_tensor):    return agg_tensor.mean(dim=0)
2025-07-17T07:05:42.4706240Z             mask_fn (Optional, Callable):
2025-07-17T07:05:42.4706550Z                 default mask_fn that is used to create the sparsification mask using the tensor obtained after
2025-07-17T07:05:42.4706950Z                 calling the reduce_fn(). This is used by default if a custom one is passed in the
2025-07-17T07:05:42.4707230Z                 register_layer().
2025-07-17T07:05:42.4707550Z                 Note that the mask_fn() definition should contain the sparse arguments that is passed in sparse_config
2025-07-17T07:05:42.4707870Z                 arguments.
2025-07-17T07:05:42.4708030Z             features (Optional, list):
2025-07-17T07:05:42.4708240Z                 default selected features to sparsify.
2025-07-17T07:05:42.4708650Z                 If this is non-empty, then the mask_fn will be applied for each feature of the input.
2025-07-17T07:05:42.4708930Z                 For example,
2025-07-17T07:05:42.4709200Z             mask = [mask_fn(reduce_fn(aggregated_fn(input[feature])) for feature in features]
2025-07-17T07:05:42.4709540Z             feature_dim (Optional, int):
2025-07-17T07:05:42.4709830Z                 default dimension of input features. Again, features along this dim will be chosen
2025-07-17T07:05:42.4710120Z                 for sparsification.
2025-07-17T07:05:42.4710300Z             sparse_config (Dict):
2025-07-17T07:05:42.4710540Z                 Default configuration for the mask_fn. This config will be passed
2025-07-17T07:05:42.4710800Z                 with the mask_fn()
2025-07-17T07:05:42.4710920Z 
2025-07-17T07:05:42.4710970Z Example:
2025-07-17T07:05:42.4711090Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:42.4711240Z     >>> model = SomeModel()
2025-07-17T07:05:42.4711560Z     >>> act_sparsifier = ActivationSparsifier(...)  # init activation sparsifier
2025-07-17T07:05:42.4711870Z     >>> # Initialize aggregate_fn
2025-07-17T07:05:42.4712030Z     >>> def agg_fn(x, y):
2025-07-17T07:05:42.4712180Z     >>>     return x + y
2025-07-17T07:05:42.4712330Z     >>>
2025-07-17T07:05:42.4712440Z     >>> # Initialize reduce_fn
2025-07-17T07:05:42.4712600Z     >>> def reduce_fn(x):
2025-07-17T07:05:42.4712760Z     >>>     return torch.mean(x, dim=0)
2025-07-17T07:05:42.4712930Z     >>>
2025-07-17T07:05:42.4713040Z     >>> # Initialize mask_fn
2025-07-17T07:05:42.4713200Z     >>> def mask_fn(data):
2025-07-17T07:05:42.4713380Z     >>>     return torch.eye(data.shape).to(data.device)
2025-07-17T07:05:42.4713570Z     >>>
2025-07-17T07:05:42.4713690Z     >>>
2025-07-17T07:05:42.4713810Z     >>> act_sparsifier.register_layer(
2025-07-17T07:05:42.4713990Z     ...     model.some_layer,
2025-07-17T07:05:42.4714150Z     ...     aggregate_fn=agg_fn,
2025-07-17T07:05:42.4714320Z     ...     reduce_fn=reduce_fn,
2025-07-17T07:05:42.4714470Z     ...     mask_fn=mask_fn,
2025-07-17T07:05:42.4714620Z     ... )
2025-07-17T07:05:42.4714730Z     >>>
2025-07-17T07:05:42.4714840Z     >>> # start training process
2025-07-17T07:05:42.4715000Z     >>> for _ in [...]:
2025-07-17T07:05:42.4715140Z     >>> # epoch starts
2025-07-17T07:05:42.4715330Z     >>> # model.forward(), compute_loss() and model.backwards()
2025-07-17T07:05:42.4715550Z     >>> # epoch ends
2025-07-17T07:05:42.4715700Z     >>>     act_sparsifier.step()
2025-07-17T07:05:42.4715870Z     >>> # end training process
2025-07-17T07:05:42.4716040Z     >>> sparsifier.squash_mask()
2025-07-17T07:05:42.4716160Z 
2025-07-17T07:05:42.4716310Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:42.4716530Z 
2025-07-17T07:05:42.4717080Z msg = Cannot scrape callname=BaseDataScheduler.get_schedule_param in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/pruning/_experimental/data_scheduler/base_data_scheduler.py line=91.
2025-07-17T07:05:42.4717850Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:42.4718090Z 
2025-07-17T07:05:42.4718210Z Abstract method that needs to be implemented by the child class.
2025-07-17T07:05:42.4718540Z The expected return type should is a dictionary of name to schedule_param value
2025-07-17T07:05:42.4718920Z The returned values will be updated in sparsifier when the scheduler step() function
2025-07-17T07:05:42.4719190Z is called.
2025-07-17T07:05:42.4719260Z 
2025-07-17T07:05:42.4719300Z Example:
2025-07-17T07:05:42.4719430Z     >>> def get_schedule_param(self):
2025-07-17T07:05:42.4719600Z     ...     new_param = {}
2025-07-17T07:05:42.4719800Z     ...     for name in self.sparsifier.data_groups.keys():
2025-07-17T07:05:42.4720010Z     ...         new_param[name] = (
2025-07-17T07:05:42.4720280Z     ...             self.sparsifier.data_groups[name][self.schedule_param] * 0.5
2025-07-17T07:05:42.4720520Z     ...         )
2025-07-17T07:05:42.4720660Z     ...     return new_param
2025-07-17T07:05:42.4720770Z 
2025-07-17T07:05:42.4721010Z When the step() function is called, the value in self.sparsifier.data_groups[name][self.schedule_param]
2025-07-17T07:05:42.4721330Z would be halved
2025-07-17T07:05:42.4721410Z 
2025-07-17T07:05:42.4721590Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:42.4721800Z 
2025-07-17T07:05:42.4722230Z msg = Cannot scrape callname=RelaxedBernoulli in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/relaxed_bernoulli.py line=120.
2025-07-17T07:05:42.4722880Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:42.4723100Z 
2025-07-17T07:05:42.4723210Z Creates a RelaxedBernoulli distribution, parametrized by
2025-07-17T07:05:42.4723500Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits`
2025-07-17T07:05:42.4723830Z (but not both). This is a relaxed version of the `Bernoulli` distribution,
2025-07-17T07:05:42.4724170Z so the values are in (0, 1), and has reparametrizable samples.
2025-07-17T07:05:42.4724340Z 
2025-07-17T07:05:42.4724390Z Example::
2025-07-17T07:05:42.4724460Z 
2025-07-17T07:05:42.4724540Z     >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-07-17T07:05:42.4724770Z     >>> m = RelaxedBernoulli(torch.tensor([2.2]),
2025-07-17T07:05:42.4724990Z     ...                      torch.tensor([0.1, 0.2, 0.3, 0.99]))
2025-07-17T07:05:42.4725180Z     >>> m.sample()
2025-07-17T07:05:42.4725330Z     tensor([ 0.2951,  0.3442,  0.8918,  0.9021])
2025-07-17T07:05:42.4725460Z 
2025-07-17T07:05:42.4725500Z Args:
2025-07-17T07:05:42.4725650Z     temperature (Tensor): relaxation temperature
2025-07-17T07:05:42.4725900Z     probs (Number, Tensor): the probability of sampling `1`
2025-07-17T07:05:42.4726170Z     logits (Number, Tensor): the log-odds of sampling `1`
2025-07-17T07:05:42.4726330Z 
2025-07-17T07:05:42.4726480Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:42.4726690Z 
2025-07-17T07:05:42.4727160Z msg = Cannot scrape callname=RelaxedOneHotCategorical in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/relaxed_categorical.py line=109.
2025-07-17T07:05:42.4727870Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:42.4728090Z 
2025-07-17T07:05:42.4728210Z Creates a RelaxedOneHotCategorical distribution parametrized by
2025-07-17T07:05:42.4728520Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits`.
2025-07-17T07:05:42.4728840Z This is a relaxed version of the :class:`OneHotCategorical` distribution, so
2025-07-17T07:05:42.4729150Z its samples are on simplex, and are reparametrizable.
2025-07-17T07:05:42.4729310Z 
2025-07-17T07:05:42.4729350Z Example::
2025-07-17T07:05:42.4729430Z 
2025-07-17T07:05:42.4729510Z     >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-07-17T07:05:42.4729750Z     >>> m = RelaxedOneHotCategorical(torch.tensor([2.2]),
2025-07-17T07:05:42.4730000Z     ...                              torch.tensor([0.1, 0.2, 0.3, 0.4]))
2025-07-17T07:05:42.4730200Z     >>> m.sample()
2025-07-17T07:05:42.4730350Z     tensor([ 0.1294,  0.2324,  0.3859,  0.2523])
2025-07-17T07:05:42.4730480Z 
2025-07-17T07:05:42.4730520Z Args:
2025-07-17T07:05:42.4730660Z     temperature (Tensor): relaxation temperature
2025-07-17T07:05:42.4730870Z     probs (Tensor): event probabilities
2025-07-17T07:05:42.4731120Z     logits (Tensor): unnormalized log probability for each event
2025-07-17T07:05:42.4731290Z 
2025-07-17T07:05:42.4731440Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:42.4731650Z 
2025-07-17T07:05:42.4732140Z msg = Cannot scrape callname=LowRankMultivariateNormal in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/lowrank_multivariate_normal.py line=56.
2025-07-17T07:05:42.4732900Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:42.4733120Z 
2025-07-17T07:05:42.4733300Z Creates a multivariate normal distribution with covariance matrix having a low-rank form
2025-07-17T07:05:42.4733660Z parameterized by :attr:`cov_factor` and :attr:`cov_diag`::
2025-07-17T07:05:42.4733860Z 
2025-07-17T07:05:42.4733960Z     covariance_matrix = cov_factor @ cov_factor.T + cov_diag
2025-07-17T07:05:42.4734140Z 
2025-07-17T07:05:42.4734180Z Example:
2025-07-17T07:05:42.4734330Z     >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK)
2025-07-17T07:05:42.4734560Z     >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-07-17T07:05:42.4734780Z     >>> m = LowRankMultivariateNormal(
2025-07-17T07:05:42.4735020Z     ...     torch.zeros(2), torch.tensor([[1.0], [0.0]]), torch.ones(2)
2025-07-17T07:05:42.4735250Z     ... )
2025-07-17T07:05:42.4735490Z     >>> m.sample()  # normally distributed with mean=`[0,0]`, cov_factor=`[[1],[0]]`, cov_diag=`[1,1]`
2025-07-17T07:05:42.4735840Z     tensor([-0.2102, -0.5429])
2025-07-17T07:05:42.4735970Z 
2025-07-17T07:05:42.4736010Z Args:
2025-07-17T07:05:42.4736220Z     loc (Tensor): mean of the distribution with shape `batch_shape + event_shape`
2025-07-17T07:05:42.4736580Z     cov_factor (Tensor): factor part of low-rank form of covariance matrix with shape
2025-07-17T07:05:42.4736870Z         `batch_shape + event_shape + (rank,)`
2025-07-17T07:05:42.4737170Z     cov_diag (Tensor): diagonal part of low-rank form of covariance matrix with shape
2025-07-17T07:05:42.4737450Z         `batch_shape + event_shape`
2025-07-17T07:05:42.4737580Z 
2025-07-17T07:05:42.4737620Z Note:
2025-07-17T07:05:42.4737840Z     The computation for determinant and inverse of covariance matrix is avoided when
2025-07-17T07:05:42.4738210Z     `cov_factor.shape[1] << cov_factor.shape[0]` thanks to `Woodbury matrix identity
2025-07-17T07:05:42.4738560Z     <https://en.wikipedia.org/wiki/Woodbury_matrix_identity>`_ and
2025-07-17T07:05:42.4738920Z     `matrix determinant lemma <https://en.wikipedia.org/wiki/Matrix_determinant_lemma>`_.
2025-07-17T07:05:42.4739320Z     Thanks to these formulas, we just need to compute the determinant and inverse of
2025-07-17T07:05:42.4739610Z     the small size "capacitance" matrix::
2025-07-17T07:05:42.4739740Z 
2025-07-17T07:05:42.4739860Z         capacitance = I + cov_factor.T @ inv(cov_diag) @ cov_factor
2025-07-17T07:05:42.4740040Z 
2025-07-17T07:05:42.4740190Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:42.4973200Z 
2025-07-17T07:05:42.4973840Z msg = Cannot scrape callname=MixtureSameFamily in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/mixture_same_family.py line=15.
2025-07-17T07:05:42.4974580Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:42.4974820Z 
2025-07-17T07:05:42.4974980Z The `MixtureSameFamily` distribution implements a (batch of) mixture
2025-07-17T07:05:42.4975350Z distribution where all component are from different parameterizations of
2025-07-17T07:05:42.4975710Z the same distribution type. It is parameterized by a `Categorical`
2025-07-17T07:05:42.4976040Z "selecting distribution" (over `k` component) and a component
2025-07-17T07:05:42.4976360Z distribution, i.e., a `Distribution` with a rightmost batch shape
2025-07-17T07:05:42.4976650Z (equal to `[k]`) which indexes each (batch of) component.
2025-07-17T07:05:42.4976820Z 
2025-07-17T07:05:42.4976890Z Examples::
2025-07-17T07:05:42.4976960Z 
2025-07-17T07:05:42.4977030Z     >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:42.4977300Z     >>> # Construct Gaussian Mixture Model in 1D consisting of 5 equally
2025-07-17T07:05:42.4977560Z     >>> # weighted normal distributions
2025-07-17T07:05:42.4977760Z     >>> mix = D.Categorical(torch.ones(5,))
2025-07-17T07:05:42.4977990Z     >>> comp = D.Normal(torch.randn(5,), torch.rand(5,))
2025-07-17T07:05:42.4978230Z     >>> gmm = MixtureSameFamily(mix, comp)
2025-07-17T07:05:42.4978380Z 
2025-07-17T07:05:42.4978750Z     >>> # Construct Gaussian Mixture Model in 2D consisting of 5 equally
2025-07-17T07:05:42.4979030Z     >>> # weighted bivariate normal distributions
2025-07-17T07:05:42.4979250Z     >>> mix = D.Categorical(torch.ones(5,))
2025-07-17T07:05:42.4979520Z     >>> comp = D.Independent(D.Normal(
2025-07-17T07:05:42.4979730Z     ...          torch.randn(5,2), torch.rand(5,2)), 1)
2025-07-17T07:05:42.4979950Z     >>> gmm = MixtureSameFamily(mix, comp)
2025-07-17T07:05:42.4980080Z 
2025-07-17T07:05:42.4980190Z     >>> # Construct a batch of 3 Gaussian Mixture Models in 2D each
2025-07-17T07:05:42.4980490Z     >>> # consisting of 5 random weighted bivariate normal distributions
2025-07-17T07:05:42.4980740Z     >>> mix = D.Categorical(torch.rand(3,5))
2025-07-17T07:05:42.4980940Z     >>> comp = D.Independent(D.Normal(
2025-07-17T07:05:42.4981160Z     ...         torch.randn(3,5,2), torch.rand(3,5,2)), 1)
2025-07-17T07:05:42.4981420Z     >>> gmm = MixtureSameFamily(mix, comp)
2025-07-17T07:05:42.4981580Z 
2025-07-17T07:05:42.4981630Z Args:
2025-07-17T07:05:42.4981820Z     mixture_distribution: `torch.distributions.Categorical`-like
2025-07-17T07:05:42.4982120Z         instance. Manages the probability of selecting component.
2025-07-17T07:05:42.4982410Z         The number of categories must match the rightmost batch
2025-07-17T07:05:42.4982690Z         dimension of the `component_distribution`. Must have either
2025-07-17T07:05:42.4982950Z         scalar `batch_shape` or `batch_shape` matching
2025-07-17T07:05:42.4983180Z         `component_distribution.batch_shape[:-1]`
2025-07-17T07:05:42.4983460Z     component_distribution: `torch.distributions.Distribution`-like
2025-07-17T07:05:42.4983770Z         instance. Right-most batch dimension indexes component.
2025-07-17T07:05:42.4983950Z 
2025-07-17T07:05:42.4984100Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:42.4984320Z 
2025-07-17T07:05:42.4984370Z gathering tests
2025-07-17T07:05:42.4984500Z running 719 test(s)
2025-07-17T07:05:42.4984950Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::typename:0, line 1074 <- wrt source file
2025-07-17T07:05:42.4985610Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::typename:0
2025-07-17T07:05:42.4986270Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::is_tensor:0, line 1110 <- wrt source file
2025-07-17T07:05:42.4986920Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::is_tensor:0
2025-07-17T07:05:42.4987600Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::set_default_device:0, line 1195 <- wrt source file
2025-07-17T07:05:42.4988300Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::set_default_device:0
2025-07-17T07:05:42.4989010Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::set_default_tensor_type:0, line 1244 <- wrt source file
2025-07-17T07:05:42.4989750Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::set_default_tensor_type:0
2025-07-17T07:05:42.4990440Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::set_default_dtype:0, line 1281 <- wrt source file
2025-07-17T07:05:42.4991130Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::set_default_dtype:0
2025-07-17T07:05:42.4991840Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::use_deterministic_algorithms:0, line 1436 <- wrt source file
2025-07-17T07:05:42.4992610Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::use_deterministic_algorithms:0
2025-07-17T07:05:42.4993310Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::compile:0, line 2559 <- wrt source file
2025-07-17T07:05:42.4994020Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::compile:0
2025-07-17T07:05:42.4994750Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::_is_device_backend_autoload_enabled:0, line 2832 <- wrt source file
2025-07-17T07:05:42.4995520Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/__init__.py::_is_device_backend_autoload_enabled:0
2025-07-17T07:05:42.4996300Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::Library.define:0, line 152 <- wrt source file
2025-07-17T07:05:42.4997010Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::Library.define:0
2025-07-17T07:05:42.4997730Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::Library._impl_with_aoti_compile:0, line 246 <- wrt source file
2025-07-17T07:05:42.4998480Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::Library._impl_with_aoti_compile:0
2025-07-17T07:05:42.4999190Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::Library.impl:0, line 306 <- wrt source file
2025-07-17T07:05:42.4999890Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::Library.impl:0
2025-07-17T07:05:42.5000540Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::define:0, line 511 <- wrt source file
2025-07-17T07:05:42.5001180Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::define:0
2025-07-17T07:05:42.5001820Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::impl:0, line 617 <- wrt source file
2025-07-17T07:05:42.5002440Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::impl:0
2025-07-17T07:05:42.5003090Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::register_kernel:0, line 798 <- wrt source file
2025-07-17T07:05:42.5003770Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::register_kernel:0
2025-07-17T07:05:42.5004460Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::register_autocast:0, line 866 <- wrt source file
2025-07-17T07:05:42.5012250Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::register_autocast:0
2025-07-17T07:05:42.5013010Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::register_torch_dispatch:0, line 1217 <- wrt source file
2025-07-17T07:05:42.5013730Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::register_torch_dispatch:0
2025-07-17T07:05:42.5014430Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::register_vmap:0, line 1306 <- wrt source file
2025-07-17T07:05:42.5015100Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py::register_vmap:0
2025-07-17T07:05:42.5015830Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_custom_ops.py::custom_op:0, line 55 <- wrt source file
2025-07-17T07:05:42.5016500Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_custom_ops.py::custom_op:0
2025-07-17T07:05:42.5017210Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_custom_ops.py::impl:0, line 138 <- wrt source file
2025-07-17T07:05:42.5017850Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_custom_ops.py::impl:0
2025-07-17T07:05:42.5018520Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_custom_ops.py::impl_abstract:0, line 208 <- wrt source file
2025-07-17T07:05:42.5019220Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_custom_ops.py::impl_abstract:0
2025-07-17T07:05:42.5122450Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/quasirandom.py::SobolEngine:0, line 39 <- wrt source file
2025-07-17T07:05:42.5123240Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/quasirandom.py::SobolEngine:0
2025-07-17T07:05:42.5123970Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/torch_version.py::TorchVersion:0, line 19 <- wrt source file
2025-07-17T07:05:42.5124690Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/torch_version.py::TorchVersion:0
2025-07-17T07:05:42.5125430Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/overrides.py::get_ignored_functions:0, line 116 <- wrt source file
2025-07-17T07:05:42.5126160Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/overrides.py::get_ignored_functions:0
2025-07-17T07:05:42.5126890Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/overrides.py::get_testing_overrides:0, line 422 <- wrt source file
2025-07-17T07:05:42.5127610Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/overrides.py::get_testing_overrides:0
2025-07-17T07:05:42.5128320Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/overrides.py::wrap_torch_function:0, line 1575 <- wrt source file
2025-07-17T07:05:42.5129030Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/overrides.py::wrap_torch_function:0
2025-07-17T07:05:42.5129750Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/overrides.py::handle_torch_function:0, line 1710 <- wrt source file
2025-07-17T07:05:42.5130470Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/overrides.py::handle_torch_function:0
2025-07-17T07:05:42.5131230Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/overrides.py::is_tensor_method_or_property:0, line 1958 <- wrt source file
2025-07-17T07:05:42.5131990Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/overrides.py::is_tensor_method_or_property:0
2025-07-17T07:05:42.5132710Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/overrides.py::is_tensor_like:0, line 1977 <- wrt source file
2025-07-17T07:05:42.5133390Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/overrides.py::is_tensor_like:0
2025-07-17T07:05:42.5134110Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_namedtensor_internals.py::update_names:0, line 118 <- wrt source file
2025-07-17T07:05:42.5135100Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_namedtensor_internals.py::update_names:0
2025-07-17T07:05:42.5135830Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py::Tensor.register_hook:0, line 649 <- wrt source file
2025-07-17T07:05:42.5136620Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py::Tensor.register_hook:0
2025-07-17T07:05:42.5137380Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py::Tensor.register_post_accumulate_grad_hook:0, line 706 <- wrt source file
2025-07-17T07:05:42.5138180Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py::Tensor.register_post_accumulate_grad_hook:0
2025-07-17T07:05:42.5139010Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py::Tensor.refine_names:0, line 1333 <- wrt source file
2025-07-17T07:05:42.5139750Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py::Tensor.refine_names:0
2025-07-17T07:05:42.5140440Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py::Tensor.align_to:0, line 1378 <- wrt source file
2025-07-17T07:05:42.5141120Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py::Tensor.align_to:0
2025-07-17T07:05:42.5141790Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py::Tensor.rename:0, line 1451 <- wrt source file
2025-07-17T07:05:42.5142470Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py::Tensor.rename:0
2025-07-17T07:05:42.5143150Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py::Tensor.to_sparse_coo:0, line 1481 <- wrt source file
2025-07-17T07:05:42.5143850Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py::Tensor.to_sparse_coo:0
2025-07-17T07:05:42.5144510Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/hub.py::list:0, line 468 <- wrt source file
2025-07-17T07:05:42.5145120Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/hub.py::list:0
2025-07-17T07:05:42.5145730Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/hub.py::help:0, line 528 <- wrt source file
2025-07-17T07:05:42.5146330Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/hub.py::help:0
2025-07-17T07:05:42.5146990Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor_str.py::set_printoptions:0, line 53 <- wrt source file
2025-07-17T07:05:42.5147690Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor_str.py::set_printoptions:0
2025-07-17T07:05:42.5148430Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::broadcast_tensors:0, line 64 <- wrt source file
2025-07-17T07:05:42.5149130Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::broadcast_tensors:0
2025-07-17T07:05:42.5149830Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::broadcast_shapes:0, line 92 <- wrt source file
2025-07-17T07:05:42.5150520Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::broadcast_shapes:0
2025-07-17T07:05:42.5151250Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::split:0, line 193 <- wrt source file
2025-07-17T07:05:42.5151910Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::split:0
2025-07-17T07:05:42.5152620Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::einsum:0, line 307 <- wrt source file
2025-07-17T07:05:42.5153270Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::einsum:0
2025-07-17T07:05:42.5153960Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::_unique_consecutive_impl:0, line 1041 <- wrt source file
2025-07-17T07:05:42.5154720Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::_unique_consecutive_impl:0
2025-07-17T07:05:42.5155460Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::tensordot:0, line 1316 <- wrt source file
2025-07-17T07:05:42.5156130Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::tensordot:0
2025-07-17T07:05:42.5156810Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::cartesian_prod:0, line 1400 <- wrt source file
2025-07-17T07:05:42.5157510Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::cartesian_prod:0
2025-07-17T07:05:42.5158190Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::block_diag:0, line 1434 <- wrt source file
2025-07-17T07:05:42.5158870Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::block_diag:0
2025-07-17T07:05:42.5159540Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::cdist:0, line 1490 <- wrt source file
2025-07-17T07:05:42.5160210Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::cdist:0
2025-07-17T07:05:42.5160880Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::atleast_1d:0, line 1531 <- wrt source file
2025-07-17T07:05:42.8705550Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::atleast_1d:0
2025-07-17T07:05:42.8706290Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::atleast_2d:0, line 1567 <- wrt source file
2025-07-17T07:05:42.8707010Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::atleast_2d:0
2025-07-17T07:05:42.8707710Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::atleast_3d:0, line 1605 <- wrt source file
2025-07-17T07:05:42.8708410Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::atleast_3d:0
2025-07-17T07:05:42.8709090Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::norm:0, line 1778 <- wrt source file
2025-07-17T07:05:42.8709750Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::norm:0
2025-07-17T07:05:42.8710450Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::unravel_index:0, line 1946 <- wrt source file
2025-07-17T07:05:42.8711340Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::unravel_index:0
2025-07-17T07:05:42.8712030Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::chain_matmul:0, line 2046 <- wrt source file
2025-07-17T07:05:42.8712810Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::chain_matmul:0
2025-07-17T07:05:42.8713480Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::_lu_impl:0, line 2146 <- wrt source file
2025-07-17T07:05:42.8714150Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py::_lu_impl:0
2025-07-17T07:05:42.8714900Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_C.cpython-312-darwin.so::Generator:0, line 15 <- wrt source file
2025-07-17T07:05:42.8715660Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_C.cpython-312-darwin.so::Generator:0
2025-07-17T07:05:42.8716380Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_C.cpython-312-darwin.so::_LinAlgError:0, line 5 <- wrt source file
2025-07-17T07:05:42.8717110Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_C.cpython-312-darwin.so::_LinAlgError:0
2025-07-17T07:05:42.8717840Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/serialization.py::add_safe_globals:0, line 299 <- wrt source file
2025-07-17T07:05:42.8718550Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/serialization.py::add_safe_globals:0
2025-07-17T07:05:42.8719270Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/serialization.py::safe_globals:0, line 324 <- wrt source file
2025-07-17T07:05:42.8719970Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/serialization.py::safe_globals:0
2025-07-17T07:05:42.8720660Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/serialization.py::skip_data:0, line 400 <- wrt source file
2025-07-17T07:05:42.8721350Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/serialization.py::skip_data:0
2025-07-17T07:05:42.8722050Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/serialization.py::register_package:0, line 472 <- wrt source file
2025-07-17T07:05:42.8722770Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/serialization.py::register_package:0
2025-07-17T07:05:42.8723460Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/serialization.py::save:0, line 950 <- wrt source file
2025-07-17T07:05:42.8724130Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/serialization.py::save:0
2025-07-17T07:05:42.8724840Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/monitor/__init__.py::TensorboardEventHandler:0, line 22 <- wrt source file
2025-07-17T07:05:42.8725610Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/monitor/__init__.py::TensorboardEventHandler:0
2025-07-17T07:05:42.8726380Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/futures/__init__.py::Future.add_done_callback:0, line 197 <- wrt source file
2025-07-17T07:05:42.8727150Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/futures/__init__.py::Future.add_done_callback:0
2025-07-17T07:05:42.8727930Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/futures/__init__.py::Future.set_exception:0, line 261 <- wrt source file
2025-07-17T07:05:42.8728670Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/futures/__init__.py::Future.set_exception:0
2025-07-17T07:05:42.8729440Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/futures/__init__.py::collect_all:0, line 295 <- wrt source file
2025-07-17T07:05:42.8730140Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/futures/__init__.py::collect_all:0
2025-07-17T07:05:42.8730840Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/__init__.py::_compile_kernel:0, line 1760 <- wrt source file
2025-07-17T07:05:42.8731580Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/__init__.py::_compile_kernel:0
2025-07-17T07:05:42.8732320Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_inductor/__init__.py::list_mode_options:0, line 320 <- wrt source file
2025-07-17T07:05:42.8733050Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_inductor/__init__.py::list_mode_options:0
2025-07-17T07:05:42.8733770Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_inductor/__init__.py::list_options:0, line 357 <- wrt source file
2025-07-17T07:05:42.8734470Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_inductor/__init__.py::list_options:0
2025-07-17T07:05:42.8735210Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/accelerator/__init__.py::current_accelerator:0, line 113 <- wrt source file
2025-07-17T07:05:42.8735980Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/accelerator/__init__.py::current_accelerator:0
2025-07-17T07:05:42.8736720Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/accelerator/__init__.py::device_index:0, line 249 <- wrt source file
2025-07-17T07:05:42.8737450Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/accelerator/__init__.py::device_index:0
2025-07-17T07:05:42.8738140Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/jit/__init__.py::annotate:0, line 147 <- wrt source file
2025-07-17T07:05:42.8738800Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/jit/__init__.py::annotate:0
2025-07-17T07:05:42.8739520Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/sparse/__init__.py::check_sparse_tensor_invariants:0, line 475 <- wrt source file
2025-07-17T07:05:42.8740310Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/sparse/__init__.py::check_sparse_tensor_invariants:0
2025-07-17T07:05:42.8741060Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/sparse/__init__.py::as_sparse_gradcheck:0, line 561 <- wrt source file
2025-07-17T07:05:42.8741790Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/sparse/__init__.py::as_sparse_gradcheck:0
2025-07-17T07:05:42.8742500Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/__init__.py::save:0, line 357 <- wrt source file
2025-07-17T07:05:42.8743160Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/__init__.py::save:0
2025-07-17T07:05:42.8743880Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/__init__.py::load:0, line 427 <- wrt source file
2025-07-17T07:05:43.0567820Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/__init__.py::load:0
2025-07-17T07:05:43.0568860Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/__init__.py::register_dataclass:0, line 575 <- wrt source file
2025-07-17T07:05:43.0569650Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/__init__.py::register_dataclass:0
2025-07-17T07:05:43.0570400Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nested/__init__.py::as_nested_tensor:0, line 61 <- wrt source file
2025-07-17T07:05:43.0571220Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nested/__init__.py::as_nested_tensor:0
2025-07-17T07:05:43.0572000Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nested/__init__.py::nested_tensor:0, line 240 <- wrt source file
2025-07-17T07:05:43.0572730Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nested/__init__.py::nested_tensor:0
2025-07-17T07:05:43.0573460Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nested/__init__.py::narrow:0, line 315 <- wrt source file
2025-07-17T07:05:43.0574160Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nested/__init__.py::narrow:0
2025-07-17T07:05:43.0574890Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nested/__init__.py::nested_tensor_from_jagged:0, line 405 <- wrt source file
2025-07-17T07:05:43.0575660Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nested/__init__.py::nested_tensor_from_jagged:0
2025-07-17T07:05:43.0576390Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nested/__init__.py::masked_select:0, line 481 <- wrt source file
2025-07-17T07:05:43.0577090Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nested/__init__.py::masked_select:0
2025-07-17T07:05:43.0577830Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::allow_in_graph:0, line 123 <- wrt source file
2025-07-17T07:05:43.0578560Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::allow_in_graph:0
2025-07-17T07:05:43.0579300Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::substitute_in_graph:0, line 179 <- wrt source file
2025-07-17T07:05:43.0580040Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::substitute_in_graph:0
2025-07-17T07:05:43.0580790Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::wrap_numpy:0, line 406 <- wrt source file
2025-07-17T07:05:43.0581490Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::wrap_numpy:0
2025-07-17T07:05:43.0582240Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::is_compiling:0, line 438 <- wrt source file
2025-07-17T07:05:43.0582940Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::is_compiling:0
2025-07-17T07:05:43.0583720Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::is_dynamo_compiling:0, line 459 <- wrt source file
2025-07-17T07:05:43.0584460Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::is_dynamo_compiling:0
2025-07-17T07:05:43.0585240Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::is_exporting:0, line 477 <- wrt source file
2025-07-17T07:05:43.0585940Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::is_exporting:0
2025-07-17T07:05:43.0586650Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::save_cache_artifacts:0, line 492 <- wrt source file
2025-07-17T07:05:43.0587410Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::save_cache_artifacts:0
2025-07-17T07:05:43.0588180Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::load_cache_artifacts:0, line 507 <- wrt source file
2025-07-17T07:05:43.0588930Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/compiler/__init__.py::load_cache_artifacts:0
2025-07-17T07:05:43.0589700Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/flat_apply.py::FlatApply.__call__:0, line 80 <- wrt source file
2025-07-17T07:05:43.0590490Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/flat_apply.py::FlatApply.__call__:0
2025-07-17T07:05:43.0591230Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/cond.py::cond:0, line 107 <- wrt source file
2025-07-17T07:05:43.0591930Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/cond.py::cond:0
2025-07-17T07:05:43.0592620Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/map.py::map:0, line 148 <- wrt source file
2025-07-17T07:05:43.0593310Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/map.py::map:0
2025-07-17T07:05:43.0594000Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/scan.py::scan:0, line 163 <- wrt source file
2025-07-17T07:05:43.0594700Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/scan.py::scan:0
2025-07-17T07:05:43.0595420Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/scan.py::ScanAutogradOp:0, line 431 <- wrt source file
2025-07-17T07:05:43.0596170Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/scan.py::ScanAutogradOp:0
2025-07-17T07:05:43.0596950Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/associative_scan.py::associative_scan:0, line 133 <- wrt source file
2025-07-17T07:05:43.0597770Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/associative_scan.py::associative_scan:0
2025-07-17T07:05:43.0598600Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/associative_scan.py::generic_associative_scan:0, line 269 <- wrt source file
2025-07-17T07:05:43.0599440Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_higher_order_ops/associative_scan.py::generic_associative_scan:0
2025-07-17T07:05:43.0600250Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_prims/context.py::TorchRefsMode:0, line 95 <- wrt source file
2025-07-17T07:05:43.0600950Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_prims/context.py::TorchRefsMode:0
2025-07-17T07:05:43.0601710Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_logging/_internal.py::set_logs:0, line 457 <- wrt source file
2025-07-17T07:05:43.0602400Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_logging/_internal.py::set_logs:0
2025-07-17T07:05:43.0603110Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/fx_minifier.py::minifier:0, line 194 <- wrt source file
2025-07-17T07:05:43.0603850Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/fx_minifier.py::minifier:0
2025-07-17T07:05:43.0604610Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/aot_autograd.py::aot_function:0, line 747 <- wrt source file
2025-07-17T07:05:43.0605350Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/aot_autograd.py::aot_function:0
2025-07-17T07:05:43.0606090Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::vjp:0, line 233 <- wrt source file
2025-07-17T07:05:43.0637000Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::vjp:0
2025-07-17T07:05:43.0637790Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::jacrev:0, line 475 <- wrt source file
2025-07-17T07:05:43.0638550Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::jacrev:0
2025-07-17T07:05:43.0639310Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::jvp:0, line 1023 <- wrt source file
2025-07-17T07:05:43.0640060Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::jvp:0
2025-07-17T07:05:43.0640810Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::jacfwd:0, line 1181 <- wrt source file
2025-07-17T07:05:43.0641550Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::jacfwd:0
2025-07-17T07:05:43.0642290Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::hessian:0, line 1341 <- wrt source file
2025-07-17T07:05:43.0643030Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::hessian:0
2025-07-17T07:05:43.0643790Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::functionalize:0, line 1505 <- wrt source file
2025-07-17T07:05:43.0644570Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::functionalize:0
2025-07-17T07:05:43.0645330Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::linearize:0, line 1704 <- wrt source file
2025-07-17T07:05:43.0646070Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/eager_transforms.py::linearize:0
2025-07-17T07:05:43.0647090Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/benchmark_utils.py::benchmark_utilization:0, line 184 <- wrt source file
2025-07-17T07:05:43.0647960Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/benchmark_utils.py::benchmark_utilization:0
2025-07-17T07:05:43.0648750Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/functional_call.py::functional_call:0, line 36 <- wrt source file
2025-07-17T07:05:43.0649600Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/functional_call.py::functional_call:0
2025-07-17T07:05:43.0650590Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/_aot_autograd/schemas.py::CompilerWrapper.post_compile:0, line 1066 <- wrt source file
2025-07-17T07:05:43.0651540Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/_aot_autograd/schemas.py::CompilerWrapper.post_compile:0
2025-07-17T07:05:43.0652340Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_equal:0, line 171 <- wrt source file
2025-07-17T07:05:43.0653070Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_equal:0
2025-07-17T07:05:43.0653810Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_array_less:0, line 1008 <- wrt source file
2025-07-17T07:05:43.0654560Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_array_less:0
2025-07-17T07:05:43.0655310Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_string_equal:0, line 1073 <- wrt source file
2025-07-17T07:05:43.0656070Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_string_equal:0
2025-07-17T07:05:43.0656830Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_allclose:0, line 1294 <- wrt source file
2025-07-17T07:05:43.0657600Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_allclose:0
2025-07-17T07:05:43.0658370Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal_nulp:0, line 1360 <- wrt source file
2025-07-17T07:05:43.0659190Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal_nulp:0
2025-07-17T07:05:43.0659980Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_array_max_ulp:0, line 1423 <- wrt source file
2025-07-17T07:05:43.0660750Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_array_max_ulp:0
2025-07-17T07:05:43.0661520Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::nulp_diff:0, line 1468 <- wrt source file
2025-07-17T07:05:43.0662230Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::nulp_diff:0
2025-07-17T07:05:43.0662950Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_warns:0, line 1578 <- wrt source file
2025-07-17T07:05:43.0663770Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py::assert_warns:0
2025-07-17T07:05:43.0664540Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_export/utils.py::register_module_as_pytree_input_node:0, line 1345 <- wrt source file
2025-07-17T07:05:43.0665370Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_export/utils.py::register_module_as_pytree_input_node:0
2025-07-17T07:05:43.0666220Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_export/wrappers.py::mark_subclass_constructor_exportable_experimental:0, line 157 <- wrt source file
2025-07-17T07:05:43.0667140Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_export/wrappers.py::mark_subclass_constructor_exportable_experimental:0
2025-07-17T07:05:43.0668020Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::fractional_max_pool2d_with_indices:0, line 464 <- wrt source file
2025-07-17T07:05:43.0668830Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::fractional_max_pool2d_with_indices:0
2025-07-17T07:05:43.0669640Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::fractional_max_pool3d_with_indices:0, line 583 <- wrt source file
2025-07-17T07:05:43.0670440Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::fractional_max_pool3d_with_indices:0
2025-07-17T07:05:43.0671200Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::gumbel_softmax:0, line 2178 <- wrt source file
2025-07-17T07:05:43.0671920Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::gumbel_softmax:0
2025-07-17T07:05:43.0672610Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::embedding:0, line 2482 <- wrt source file
2025-07-17T07:05:43.0673300Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::embedding:0
2025-07-17T07:05:43.0674000Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::embedding_bag:0, line 2622 <- wrt source file
2025-07-17T07:05:43.0674700Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::embedding_bag:0
2025-07-17T07:05:43.0675400Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::ctc_loss:0, line 3055 <- wrt source file
2025-07-17T07:05:43.0676070Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::ctc_loss:0
2025-07-17T07:05:43.0696290Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::nll_loss:0, line 3125 <- wrt source file
2025-07-17T07:05:43.0697050Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::nll_loss:0
2025-07-17T07:05:43.0697850Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::cross_entropy:0, line 3434 <- wrt source file
2025-07-17T07:05:43.0698560Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::cross_entropy:0
2025-07-17T07:05:43.0699510Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::binary_cross_entropy:0, line 3499 <- wrt source file
2025-07-17T07:05:43.0700260Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::binary_cross_entropy:0
2025-07-17T07:05:43.0701090Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::binary_cross_entropy_with_logits:0, line 3569 <- wrt source file
2025-07-17T07:05:43.0701890Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::binary_cross_entropy_with_logits:0
2025-07-17T07:05:43.0702620Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::pad:0, line 5267 <- wrt source file
2025-07-17T07:05:43.0703330Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/functional.py::pad:0
2025-07-17T07:05:43.0704000Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::uniform_:0, line 230 <- wrt source file
2025-07-17T07:05:43.0704640Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::uniform_:0
2025-07-17T07:05:43.0705310Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::normal_:0, line 257 <- wrt source file
2025-07-17T07:05:43.0705950Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::normal_:0
2025-07-17T07:05:43.0706600Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::trunc_normal_:0, line 292 <- wrt source file
2025-07-17T07:05:43.0707270Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::trunc_normal_:0
2025-07-17T07:05:43.0707920Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::constant_:0, line 306 <- wrt source file
2025-07-17T07:05:43.0708570Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::constant_:0
2025-07-17T07:05:43.0716290Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::ones_:0, line 323 <- wrt source file
2025-07-17T07:05:43.0716920Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::ones_:0
2025-07-17T07:05:43.0717560Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::zeros_:0, line 336 <- wrt source file
2025-07-17T07:05:43.0718190Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::zeros_:0
2025-07-17T07:05:43.0718810Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::eye_:0, line 352 <- wrt source file
2025-07-17T07:05:43.0719440Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::eye_:0
2025-07-17T07:05:43.0720070Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::dirac_:0, line 374 <- wrt source file
2025-07-17T07:05:43.0720700Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::dirac_:0
2025-07-17T07:05:43.0721360Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::xavier_uniform_:0, line 460 <- wrt source file
2025-07-17T07:05:43.0722040Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::xavier_uniform_:0
2025-07-17T07:05:43.0722800Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::xavier_normal_:0, line 492 <- wrt source file
2025-07-17T07:05:43.0723480Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::xavier_normal_:0
2025-07-17T07:05:43.0724180Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::kaiming_uniform_:0, line 543 <- wrt source file
2025-07-17T07:05:43.0724860Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::kaiming_uniform_:0
2025-07-17T07:05:43.0725540Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::kaiming_normal_:0, line 608 <- wrt source file
2025-07-17T07:05:43.0726240Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::kaiming_normal_:0
2025-07-17T07:05:43.0726970Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::orthogonal_:0, line 647 <- wrt source file
2025-07-17T07:05:43.0727650Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::orthogonal_:0
2025-07-17T07:05:43.0728340Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::sparse_:0, line 700 <- wrt source file
2025-07-17T07:05:43.0728990Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py::sparse_:0
2025-07-17T07:05:43.0729640Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/grad.py::conv1d_input:0, line 32 <- wrt source file
2025-07-17T07:05:43.0730300Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/grad.py::conv1d_input:0
2025-07-17T07:05:43.0730960Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/grad.py::conv1d_weight:0, line 79 <- wrt source file
2025-07-17T07:05:43.0731620Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/grad.py::conv1d_weight:0
2025-07-17T07:05:43.0732280Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/grad.py::conv2d_input:0, line 130 <- wrt source file
2025-07-17T07:05:43.0732940Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/grad.py::conv2d_input:0
2025-07-17T07:05:43.0733600Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/grad.py::conv2d_weight:0, line 177 <- wrt source file
2025-07-17T07:05:43.0734260Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/grad.py::conv2d_weight:0
2025-07-17T07:05:43.0734920Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/grad.py::conv3d_input:0, line 228 <- wrt source file
2025-07-17T07:05:43.0735580Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/grad.py::conv3d_input:0
2025-07-17T07:05:43.0736240Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/grad.py::conv3d_weight:0, line 275 <- wrt source file
2025-07-17T07:05:43.0736900Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/grad.py::conv3d_weight:0
2025-07-17T07:05:43.0737590Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/attention/__init__.py::sdpa_kernel:0, line 119 <- wrt source file
2025-07-17T07:05:43.0738370Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/attention/__init__.py::sdpa_kernel:0
2025-07-17T07:05:43.0739100Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/attention/bias.py::CausalBias:0, line 95 <- wrt source file
2025-07-17T07:05:43.0739860Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/attention/bias.py::CausalBias:0
2025-07-17T07:05:43.0740590Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/data_parallel.py::DataParallel:0, line 127 <- wrt source file
2025-07-17T07:05:43.0741360Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/data_parallel.py::DataParallel:0
2025-07-17T07:05:44.5446960Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel:0, line 642 <- wrt source file
2025-07-17T07:05:44.5447950Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel:0
2025-07-17T07:05:44.5448840Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.no_sync:0, line 1446 <- wrt source file
2025-07-17T07:05:44.5449740Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.no_sync:0
2025-07-17T07:05:44.5450680Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:0, line 1999 <- wrt source file
2025-07-17T07:05:44.5451620Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:0
2025-07-17T07:05:44.5452570Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:1, line 2009 <- wrt source file
2025-07-17T07:05:44.5453510Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:1
2025-07-17T07:05:44.5454460Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_builtin_comm_hook:0, line 2044 <- wrt source file
2025-07-17T07:05:44.5455440Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_builtin_comm_hook:0
2025-07-17T07:05:44.5456300Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/spectral_norm.py::spectral_norm:0, line 314 <- wrt source file
2025-07-17T07:05:44.5457050Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/spectral_norm.py::spectral_norm:0
2025-07-17T07:05:44.5457810Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/spectral_norm.py::remove_spectral_norm:0, line 346 <- wrt source file
2025-07-17T07:05:44.5458590Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/spectral_norm.py::remove_spectral_norm:0
2025-07-17T07:05:44.5459360Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/stateless.py::functional_call:0, line 196 <- wrt source file
2025-07-17T07:05:44.5460110Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/stateless.py::functional_call:0
2025-07-17T07:05:44.5461030Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/_per_sample_grad.py::call_for_per_sample_grads:0, line 35 <- wrt source file
2025-07-17T07:05:44.5461850Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/_per_sample_grad.py::call_for_per_sample_grads:0
2025-07-17T07:05:44.5462710Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/weight_norm.py::weight_norm:0, line 134 <- wrt source file
2025-07-17T07:05:44.5463440Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/weight_norm.py::weight_norm:0
2025-07-17T07:05:44.5464180Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/weight_norm.py::remove_weight_norm:0, line 156 <- wrt source file
2025-07-17T07:05:44.5464960Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/weight_norm.py::remove_weight_norm:0
2025-07-17T07:05:44.5465740Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py::identity:0, line 849 <- wrt source file
2025-07-17T07:05:44.5466420Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py::identity:0
2025-07-17T07:05:44.5467130Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py::random_unstructured:0, line 885 <- wrt source file
2025-07-17T07:05:44.5467860Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py::random_unstructured:0
2025-07-17T07:05:44.5468590Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py::l1_unstructured:0, line 928 <- wrt source file
2025-07-17T07:05:44.5469310Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py::l1_unstructured:0
2025-07-17T07:05:44.5470020Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py::random_structured:0, line 968 <- wrt source file
2025-07-17T07:05:44.5470740Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py::random_structured:0
2025-07-17T07:05:44.5471480Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py::remove:0, line 1197 <- wrt source file
2025-07-17T07:05:44.5472150Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py::remove:0
2025-07-17T07:05:44.5472830Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py::is_pruned:0, line 1225 <- wrt source file
2025-07-17T07:05:44.5473520Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py::is_pruned:0
2025-07-17T07:05:44.5474250Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/parametrizations.py::orthogonal:0, line 265 <- wrt source file
2025-07-17T07:05:44.5475010Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/parametrizations.py::orthogonal:0
2025-07-17T07:05:44.5475760Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/parametrizations.py::weight_norm:0, line 360 <- wrt source file
2025-07-17T07:05:44.5476540Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/parametrizations.py::weight_norm:0
2025-07-17T07:05:44.5477350Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/parametrizations.py::spectral_norm:0, line 591 <- wrt source file
2025-07-17T07:05:44.5478130Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/parametrizations.py::spectral_norm:0
2025-07-17T07:05:44.5478910Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/init.py::skip_init:0, line 33 <- wrt source file
2025-07-17T07:05:44.5479600Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/init.py::skip_init:0
2025-07-17T07:05:44.5480270Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/rnn.py::pad_sequence:0, line 431 <- wrt source file
2025-07-17T07:05:44.5480990Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/rnn.py::pad_sequence:0
2025-07-17T07:05:44.5481700Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/rnn.py::unpad_sequence:0, line 492 <- wrt source file
2025-07-17T07:05:44.5482410Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/rnn.py::unpad_sequence:0
2025-07-17T07:05:44.5483110Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/rnn.py::pack_sequence:0, line 548 <- wrt source file
2025-07-17T07:05:44.5483800Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/rnn.py::pack_sequence:0
2025-07-17T07:05:44.5484500Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/rnn.py::unpack_sequence:0, line 576 <- wrt source file
2025-07-17T07:05:44.5485210Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/rnn.py::unpack_sequence:0
2025-07-17T07:05:44.5486050Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/_expanded_weights/expanded_weights_utils.py::sum_over_all_but_batch_and_last_n:0, line 178 <- wrt source file
2025-07-17T07:05:44.8587700Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/_expanded_weights/expanded_weights_utils.py::sum_over_all_but_batch_and_last_n:0
2025-07-17T07:05:44.8588670Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/_expanded_weights/conv_utils.py::unfold3d:0, line 315 <- wrt source file
2025-07-17T07:05:44.8589600Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/_expanded_weights/conv_utils.py::unfold3d:0
2025-07-17T07:05:44.8590420Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/upsampling.py::Upsample:0, line 77 <- wrt source file
2025-07-17T07:05:44.8591180Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/upsampling.py::Upsample:0
2025-07-17T07:05:44.8591940Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/upsampling.py::UpsamplingNearest2d:0, line 223 <- wrt source file
2025-07-17T07:05:44.8592730Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/upsampling.py::UpsamplingNearest2d:0
2025-07-17T07:05:44.8593600Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/upsampling.py::UpsamplingBilinear2d:0, line 273 <- wrt source file
2025-07-17T07:05:44.8594570Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/upsampling.py::UpsamplingBilinear2d:0
2025-07-17T07:05:44.8595370Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/channelshuffle.py::ChannelShuffle:0, line 21 <- wrt source file
2025-07-17T07:05:44.8596260Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/channelshuffle.py::ChannelShuffle:0
2025-07-17T07:05:44.8597040Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm1d:0, line 187 <- wrt source file
2025-07-17T07:05:44.8597800Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm1d:0
2025-07-17T07:05:44.8598650Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm2d:0, line 303 <- wrt source file
2025-07-17T07:05:44.8599610Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm2d:0
2025-07-17T07:05:44.8600570Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm3d:0, line 419 <- wrt source file
2025-07-17T07:05:44.8601360Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm3d:0
2025-07-17T07:05:44.8602090Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/flatten.py::Flatten:0, line 30 <- wrt source file
2025-07-17T07:05:44.8602790Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/flatten.py::Flatten:0
2025-07-17T07:05:44.8603510Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py::BatchNorm1d:0, line 330 <- wrt source file
2025-07-17T07:05:44.8604240Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py::BatchNorm1d:0
2025-07-17T07:05:44.8604980Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py::BatchNorm2d:0, line 441 <- wrt source file
2025-07-17T07:05:44.8605710Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py::BatchNorm2d:0
2025-07-17T07:05:44.8606440Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py::BatchNorm3d:0, line 552 <- wrt source file
2025-07-17T07:05:44.8607170Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py::BatchNorm3d:0
2025-07-17T07:05:44.8607920Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/linear.py::Identity:0, line 34 <- wrt source file
2025-07-17T07:05:44.8608610Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/linear.py::Identity:0
2025-07-17T07:05:44.8609310Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/linear.py::Linear:0, line 80 <- wrt source file
2025-07-17T07:05:44.8610000Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/linear.py::Linear:0
2025-07-17T07:05:44.8610700Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/linear.py::Bilinear:0, line 179 <- wrt source file
2025-07-17T07:05:44.8611390Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/linear.py::Bilinear:0
2025-07-17T07:05:44.8612150Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxPool1d:0, line 129 <- wrt source file
2025-07-17T07:05:44.8612890Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxPool1d:0
2025-07-17T07:05:44.8613680Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxPool2d:0, line 206 <- wrt source file
2025-07-17T07:05:44.8614390Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxPool2d:0
2025-07-17T07:05:44.8615100Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxPool3d:0, line 289 <- wrt source file
2025-07-17T07:05:44.8615860Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxPool3d:0
2025-07-17T07:05:44.8616590Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxUnpool1d:0, line 363 <- wrt source file
2025-07-17T07:05:44.8617310Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxUnpool1d:0
2025-07-17T07:05:44.8618030Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxUnpool3d:0, line 545 <- wrt source file
2025-07-17T07:05:44.8618740Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::MaxUnpool3d:0
2025-07-17T07:05:44.8619450Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AvgPool1d:0, line 636 <- wrt source file
2025-07-17T07:05:44.8620160Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AvgPool1d:0
2025-07-17T07:05:44.8620870Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AvgPool2d:0, line 731 <- wrt source file
2025-07-17T07:05:44.8621580Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AvgPool2d:0
2025-07-17T07:05:44.8622280Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AvgPool3d:0, line 847 <- wrt source file
2025-07-17T07:05:44.8622990Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AvgPool3d:0
2025-07-17T07:05:44.8623730Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool2d:0, line 937 <- wrt source file
2025-07-17T07:05:44.8624500Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool2d:0
2025-07-17T07:05:44.8625260Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool3d:0, line 1024 <- wrt source file
2025-07-17T07:05:44.8626020Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool3d:0
2025-07-17T07:05:44.8626760Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::LPPool1d:0, line 1143 <- wrt source file
2025-07-17T07:05:44.8627470Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::LPPool1d:0
2025-07-17T07:05:44.8640610Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::LPPool2d:0, line 1194 <- wrt source file
2025-07-17T07:05:44.8641370Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::LPPool2d:0
2025-07-17T07:05:44.8642130Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::LPPool3d:0, line 1253 <- wrt source file
2025-07-17T07:05:44.8642860Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::LPPool3d:0
2025-07-17T07:05:44.8643620Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool1d:0, line 1308 <- wrt source file
2025-07-17T07:05:44.8644430Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool1d:0
2025-07-17T07:05:44.8645220Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool2d:0, line 1342 <- wrt source file
2025-07-17T07:05:44.8645970Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool2d:0
2025-07-17T07:05:44.8646730Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool3d:0, line 1385 <- wrt source file
2025-07-17T07:05:44.8647500Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool3d:0
2025-07-17T07:05:44.8648280Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool1d:0, line 1432 <- wrt source file
2025-07-17T07:05:44.8649060Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool1d:0
2025-07-17T07:05:44.8649810Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool2d:0, line 1463 <- wrt source file
2025-07-17T07:05:44.8650610Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool2d:0
2025-07-17T07:05:44.8651370Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool3d:0, line 1502 <- wrt source file
2025-07-17T07:05:44.8652160Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool3d:0
2025-07-17T07:05:44.8652910Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/distance.py::PairwiseDistance:0, line 38 <- wrt source file
2025-07-17T07:05:44.8653670Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/distance.py::PairwiseDistance:0
2025-07-17T07:05:44.8654420Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/distance.py::CosineSimilarity:0, line 78 <- wrt source file
2025-07-17T07:05:44.8655170Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/distance.py::CosineSimilarity:0
2025-07-17T07:05:44.8655910Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential:0, line 81 <- wrt source file
2025-07-17T07:05:44.8656640Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential:0
2025-07-17T07:05:44.8657440Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential.append:0, line 254 <- wrt source file
2025-07-17T07:05:44.8658250Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential.append:0
2025-07-17T07:05:44.8659250Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential.insert:0, line 277 <- wrt source file
2025-07-17T07:05:44.8660020Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential.insert:0
2025-07-17T07:05:44.8660790Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential.extend:0, line 308 <- wrt source file
2025-07-17T07:05:44.8661570Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::Sequential.extend:0
2025-07-17T07:05:44.8662340Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::ModuleList:0, line 337 <- wrt source file
2025-07-17T07:05:44.8663070Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::ModuleList:0
2025-07-17T07:05:44.8663800Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::ModuleDict:0, line 517 <- wrt source file
2025-07-17T07:05:44.8664520Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::ModuleDict:0
2025-07-17T07:05:44.8665270Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::ParameterList:0, line 647 <- wrt source file
2025-07-17T07:05:44.8666020Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::ParameterList:0
2025-07-17T07:05:44.8666760Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::ParameterDict:0, line 799 <- wrt source file
2025-07-17T07:05:44.8667500Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/container.py::ParameterDict:0
2025-07-17T07:05:44.8668250Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pixelshuffle.py::PixelShuffle:0, line 40 <- wrt source file
2025-07-17T07:05:44.8669010Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pixelshuffle.py::PixelShuffle:0
2025-07-17T07:05:44.8669780Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pixelshuffle.py::PixelUnshuffle:0, line 93 <- wrt source file
2025-07-17T07:05:44.8670550Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pixelshuffle.py::PixelUnshuffle:0
2025-07-17T07:05:44.8671280Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::L1Loss:0, line 115 <- wrt source file
2025-07-17T07:05:44.8671950Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::L1Loss:0
2025-07-17T07:05:44.8672630Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::NLLLoss:0, line 212 <- wrt source file
2025-07-17T07:05:44.8673310Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::NLLLoss:0
2025-07-17T07:05:44.8674060Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::PoissonNLLLoss:0, line 323 <- wrt source file
2025-07-17T07:05:44.8674790Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::PoissonNLLLoss:0
2025-07-17T07:05:44.8675540Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::GaussianNLLLoss:0, line 409 <- wrt source file
2025-07-17T07:05:44.8676260Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::GaussianNLLLoss:0
2025-07-17T07:05:44.8676970Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::KLDivLoss:0, line 523 <- wrt source file
2025-07-17T07:05:44.8677720Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::KLDivLoss:0
2025-07-17T07:05:44.8678440Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::MSELoss:0, line 602 <- wrt source file
2025-07-17T07:05:44.8679120Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::MSELoss:0
2025-07-17T07:05:44.8679810Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::BCELoss:0, line 685 <- wrt source file
2025-07-17T07:05:45.6505660Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::BCELoss:0
2025-07-17T07:05:45.6506460Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:0, line 757 <- wrt source file
2025-07-17T07:05:45.6507250Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:0
2025-07-17T07:05:45.6508020Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:1, line 805 <- wrt source file
2025-07-17T07:05:45.6508790Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:1
2025-07-17T07:05:45.6509570Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::MultiLabelMarginLoss:0, line 951 <- wrt source file
2025-07-17T07:05:45.6510340Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::MultiLabelMarginLoss:0
2025-07-17T07:05:45.6511090Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:0, line 1277 <- wrt source file
2025-07-17T07:05:45.6511830Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:0
2025-07-17T07:05:45.6512570Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::CosineEmbeddingLoss:0, line 1419 <- wrt source file
2025-07-17T07:05:45.6513310Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::CosineEmbeddingLoss:0
2025-07-17T07:05:45.6514050Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::MarginRankingLoss:0, line 1485 <- wrt source file
2025-07-17T07:05:45.6514790Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::MarginRankingLoss:0
2025-07-17T07:05:45.6515790Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::MultiMarginLoss:0, line 1565 <- wrt source file
2025-07-17T07:05:45.6516520Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::MultiMarginLoss:0
2025-07-17T07:05:45.6517330Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::TripletMarginLoss:0, line 1666 <- wrt source file
2025-07-17T07:05:45.6518070Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py::TripletMarginLoss:0
2025-07-17T07:05:45.6518810Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Threshold:0, line 72 <- wrt source file
2025-07-17T07:05:45.6519620Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Threshold:0
2025-07-17T07:05:45.6520380Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::ReLU:0, line 114 <- wrt source file
2025-07-17T07:05:45.6521130Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::ReLU:0
2025-07-17T07:05:45.6521830Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::RReLU:0, line 173 <- wrt source file
2025-07-17T07:05:45.6522550Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::RReLU:0
2025-07-17T07:05:45.6523270Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardtanh:0, line 229 <- wrt source file
2025-07-17T07:05:45.6524000Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardtanh:0
2025-07-17T07:05:45.6524740Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::ReLU6:0, line 294 <- wrt source file
2025-07-17T07:05:45.6525450Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::ReLU6:0
2025-07-17T07:05:45.6526180Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Sigmoid:0, line 322 <- wrt source file
2025-07-17T07:05:45.6526890Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Sigmoid:0
2025-07-17T07:05:45.6527620Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardsigmoid:0, line 354 <- wrt source file
2025-07-17T07:05:45.6528360Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardsigmoid:0
2025-07-17T07:05:45.6529080Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Tanh:0, line 387 <- wrt source file
2025-07-17T07:05:45.6529850Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Tanh:0
2025-07-17T07:05:45.6530540Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::SiLU:0, line 420 <- wrt source file
2025-07-17T07:05:45.6531250Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::SiLU:0
2025-07-17T07:05:45.6531950Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Mish:0, line 459 <- wrt source file
2025-07-17T07:05:45.6532690Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Mish:0
2025-07-17T07:05:45.6533450Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardswish:0, line 504 <- wrt source file
2025-07-17T07:05:45.6540790Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardswish:0
2025-07-17T07:05:45.6541510Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::ELU:0, line 547 <- wrt source file
2025-07-17T07:05:45.6542210Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::ELU:0
2025-07-17T07:05:45.6542990Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::CELU:0, line 589 <- wrt source file
2025-07-17T07:05:45.6543720Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::CELU:0
2025-07-17T07:05:45.6544420Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::SELU:0, line 642 <- wrt source file
2025-07-17T07:05:45.6545120Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::SELU:0
2025-07-17T07:05:45.6545820Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::GLU:0, line 682 <- wrt source file
2025-07-17T07:05:45.6546520Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::GLU:0
2025-07-17T07:05:45.6547210Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::GELU:0, line 724 <- wrt source file
2025-07-17T07:05:45.6547920Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::GELU:0
2025-07-17T07:05:45.6548640Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardshrink:0, line 767 <- wrt source file
2025-07-17T07:05:45.6549370Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Hardshrink:0
2025-07-17T07:05:45.6550100Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::LeakyReLU:0, line 816 <- wrt source file
2025-07-17T07:05:45.6550830Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::LeakyReLU:0
2025-07-17T07:05:45.6551590Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::LogSigmoid:0, line 852 <- wrt source file
2025-07-17T07:05:46.3598820Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::LogSigmoid:0
2025-07-17T07:05:46.3599720Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softplus:0, line 885 <- wrt source file
2025-07-17T07:05:46.3600540Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softplus:0
2025-07-17T07:05:46.3601290Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softshrink:0, line 928 <- wrt source file
2025-07-17T07:05:46.3602320Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softshrink:0
2025-07-17T07:05:46.3603170Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::MultiheadAttention:0, line 1036 <- wrt source file
2025-07-17T07:05:46.3604090Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::MultiheadAttention:0
2025-07-17T07:05:46.3604900Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::PReLU:0, line 1501 <- wrt source file
2025-07-17T07:05:46.3605660Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::PReLU:0
2025-07-17T07:05:46.3606460Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softsign:0, line 1543 <- wrt source file
2025-07-17T07:05:46.3607280Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softsign:0
2025-07-17T07:05:46.3608050Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Tanhshrink:0, line 1566 <- wrt source file
2025-07-17T07:05:46.3608780Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Tanhshrink:0
2025-07-17T07:05:46.3609500Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softmin:0, line 1601 <- wrt source file
2025-07-17T07:05:46.3610210Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softmin:0
2025-07-17T07:05:46.3610930Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softmax:0, line 1659 <- wrt source file
2025-07-17T07:05:46.3611650Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softmax:0
2025-07-17T07:05:46.3612390Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softmax2d:0, line 1700 <- wrt source file
2025-07-17T07:05:46.3613150Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::Softmax2d:0
2025-07-17T07:05:46.3613870Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::LogSoftmax:0, line 1736 <- wrt source file
2025-07-17T07:05:46.3614600Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/activation.py::LogSoftmax:0
2025-07-17T07:05:46.3615340Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py::Transformer:0, line 90 <- wrt source file
2025-07-17T07:05:46.3616080Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py::Transformer:0
2025-07-17T07:05:46.3616850Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerEncoder:0, line 336 <- wrt source file
2025-07-17T07:05:46.3617630Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerEncoder:0
2025-07-17T07:05:46.3618450Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerDecoder:0, line 562 <- wrt source file
2025-07-17T07:05:46.3619290Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerDecoder:0
2025-07-17T07:05:46.3620100Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerEncoderLayer:0, line 686 <- wrt source file
2025-07-17T07:05:46.3620940Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerEncoderLayer:0
2025-07-17T07:05:46.3621750Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerDecoderLayer:0, line 995 <- wrt source file
2025-07-17T07:05:46.3622570Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py::TransformerDecoderLayer:0
2025-07-17T07:05:46.3623390Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/sparse.py::Embedding:0, line 71 <- wrt source file
2025-07-17T07:05:46.3624130Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/sparse.py::Embedding:0
2025-07-17T07:05:46.3624880Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/sparse.py::Embedding.from_pretrained:0, line 243 <- wrt source file
2025-07-17T07:05:46.3625660Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/sparse.py::Embedding.from_pretrained:0
2025-07-17T07:05:46.3626450Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/sparse.py::EmbeddingBag.from_pretrained:0, line 521 <- wrt source file
2025-07-17T07:05:46.3627260Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/sparse.py::EmbeddingBag.from_pretrained:0
2025-07-17T07:05:46.3628050Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.register_buffer:0, line 551 <- wrt source file
2025-07-17T07:05:46.3628810Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.register_buffer:0
2025-07-17T07:05:46.3629570Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.apply:0, line 1037 <- wrt source file
2025-07-17T07:05:46.3630290Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.apply:0
2025-07-17T07:05:46.3631000Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.to:0, line 1288 <- wrt source file
2025-07-17T07:05:46.3631700Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.to:0
2025-07-17T07:05:46.3632460Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.state_dict:0, line 2224 <- wrt source file
2025-07-17T07:05:46.3633200Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.state_dict:0
2025-07-17T07:05:46.3633940Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.parameters:0, line 2665 <- wrt source file
2025-07-17T07:05:46.3634690Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.parameters:0
2025-07-17T07:05:46.3635450Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_parameters:0, line 2693 <- wrt source file
2025-07-17T07:05:46.3636280Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_parameters:0
2025-07-17T07:05:46.3637040Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.buffers:0, line 2720 <- wrt source file
2025-07-17T07:05:46.3637790Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.buffers:0
2025-07-17T07:05:46.3638530Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_buffers:0, line 2747 <- wrt source file
2025-07-17T07:05:47.0037720Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_buffers:0
2025-07-17T07:05:47.0038970Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_children:0, line 2778 <- wrt source file
2025-07-17T07:05:47.0039890Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_children:0
2025-07-17T07:05:47.0040660Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.modules:0, line 2802 <- wrt source file
2025-07-17T07:05:47.0041420Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.modules:0
2025-07-17T07:05:47.0042180Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_modules:0, line 2840 <- wrt source file
2025-07-17T07:05:47.0042940Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/module.py::Module.named_modules:0
2025-07-17T07:05:47.0043670Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout:0, line 60 <- wrt source file
2025-07-17T07:05:47.0044410Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout:0
2025-07-17T07:05:47.0045150Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout1d:0, line 105 <- wrt source file
2025-07-17T07:05:47.0045870Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout1d:0
2025-07-17T07:05:47.0046580Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout2d:0, line 157 <- wrt source file
2025-07-17T07:05:47.0047320Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout2d:0
2025-07-17T07:05:47.0048030Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout3d:0, line 202 <- wrt source file
2025-07-17T07:05:47.0048740Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/dropout.py::Dropout3d:0
2025-07-17T07:05:47.0049480Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/dropout.py::AlphaDropout:0, line 245 <- wrt source file
2025-07-17T07:05:47.0050200Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/dropout.py::AlphaDropout:0
2025-07-17T07:05:47.0050950Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/dropout.py::FeatureAlphaDropout:0, line 294 <- wrt source file
2025-07-17T07:05:47.0051800Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/dropout.py::FeatureAlphaDropout:0
2025-07-17T07:05:47.0052550Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/lazy.py::LazyModuleMixin:0, line 77 <- wrt source file
2025-07-17T07:05:47.0053330Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/lazy.py::LazyModuleMixin:0
2025-07-17T07:05:47.0054090Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/normalization.py::LocalResponseNorm:0, line 38 <- wrt source file
2025-07-17T07:05:47.0054880Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/normalization.py::LocalResponseNorm:0
2025-07-17T07:05:47.0055680Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/normalization.py::LayerNorm:0, line 151 <- wrt source file
2025-07-17T07:05:47.0056460Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/normalization.py::LayerNorm:0
2025-07-17T07:05:47.0057200Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/normalization.py::GroupNorm:0, line 262 <- wrt source file
2025-07-17T07:05:47.0057950Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/normalization.py::GroupNorm:0
2025-07-17T07:05:47.0058690Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/normalization.py::RMSNorm:0, line 355 <- wrt source file
2025-07-17T07:05:47.0059440Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/normalization.py::RMSNorm:0
2025-07-17T07:05:47.0060140Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/rnn.py::RNN:0, line 595 <- wrt source file
2025-07-17T07:05:47.0060800Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/rnn.py::RNN:0
2025-07-17T07:05:47.0061460Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/rnn.py::LSTM:0, line 950 <- wrt source file
2025-07-17T07:05:47.0062110Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/rnn.py::LSTM:0
2025-07-17T07:05:47.0062780Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/rnn.py::GRU:0, line 1285 <- wrt source file
2025-07-17T07:05:47.0063430Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/rnn.py::GRU:0
2025-07-17T07:05:47.0064110Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/rnn.py::RNNCell:0, line 1534 <- wrt source file
2025-07-17T07:05:47.0064810Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/rnn.py::RNNCell:0
2025-07-17T07:05:47.0065500Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/rnn.py::LSTMCell:0, line 1656 <- wrt source file
2025-07-17T07:05:47.0066210Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/rnn.py::LSTMCell:0
2025-07-17T07:05:47.0066880Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/rnn.py::GRUCell:0, line 1770 <- wrt source file
2025-07-17T07:05:47.0067610Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/rnn.py::GRUCell:0
2025-07-17T07:05:47.0068310Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::CircularPad1d:0, line 70 <- wrt source file
2025-07-17T07:05:47.0069080Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::CircularPad1d:0
2025-07-17T07:05:47.0069810Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::CircularPad2d:0, line 122 <- wrt source file
2025-07-17T07:05:47.0070540Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::CircularPad2d:0
2025-07-17T07:05:47.0071290Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::CircularPad3d:0, line 187 <- wrt source file
2025-07-17T07:05:47.0072040Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::CircularPad3d:0
2025-07-17T07:05:47.0072760Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ConstantPad1d:0, line 241 <- wrt source file
2025-07-17T07:05:47.0073520Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ConstantPad1d:0
2025-07-17T07:05:47.0074250Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ConstantPad2d:0, line 294 <- wrt source file
2025-07-17T07:05:47.0074970Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ConstantPad2d:0
2025-07-17T07:05:47.0075700Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ConstantPad3d:0, line 350 <- wrt source file
2025-07-17T07:05:47.0076430Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ConstantPad3d:0
2025-07-17T07:05:47.0077160Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReflectionPad1d:0, line 395 <- wrt source file
2025-07-17T07:05:47.0077910Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReflectionPad1d:0
2025-07-17T07:05:47.0078650Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReflectionPad2d:0, line 439 <- wrt source file
2025-07-17T07:05:47.0079380Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReflectionPad2d:0
2025-07-17T07:05:47.0080120Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReflectionPad3d:0, line 497 <- wrt source file
2025-07-17T07:05:47.0080860Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReflectionPad3d:0
2025-07-17T07:05:47.0081600Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReplicationPad1d:0, line 556 <- wrt source file
2025-07-17T07:05:47.0082360Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReplicationPad1d:0
2025-07-17T07:05:47.0083110Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReplicationPad2d:0, line 600 <- wrt source file
2025-07-17T07:05:47.0083880Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReplicationPad2d:0
2025-07-17T07:05:47.0084630Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReplicationPad3d:0, line 658 <- wrt source file
2025-07-17T07:05:47.0085430Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ReplicationPad3d:0
2025-07-17T07:05:47.0086180Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ZeroPad1d:0, line 692 <- wrt source file
2025-07-17T07:05:47.0086920Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ZeroPad1d:0
2025-07-17T07:05:47.0087690Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ZeroPad2d:0, line 747 <- wrt source file
2025-07-17T07:05:47.0088460Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ZeroPad2d:0
2025-07-17T07:05:47.0089180Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ZeroPad3d:0, line 806 <- wrt source file
2025-07-17T07:05:47.0089920Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/padding.py::ZeroPad3d:0
2025-07-17T07:05:47.0090610Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/fold.py::Fold:0, line 224 <- wrt source file
2025-07-17T07:05:47.0091270Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/fold.py::Fold:0
2025-07-17T07:05:47.0091940Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/fold.py::Unfold:0, line 389 <- wrt source file
2025-07-17T07:05:47.0092620Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/fold.py::Unfold:0
2025-07-17T07:05:47.0093300Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/run.py::__doc__:0, line 57 <- wrt source file
2025-07-17T07:05:47.0093980Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/run.py::__doc__:0
2025-07-17T07:05:47.0094730Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::_coalescing_manager:0, line 2574 <- wrt source file
2025-07-17T07:05:47.0095550Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::_coalescing_manager:0
2025-07-17T07:05:47.0096350Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::_time_estimator:0, line 2676 <- wrt source file
2025-07-17T07:05:47.0097140Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::_time_estimator:0
2025-07-17T07:05:47.0097940Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::all_gather_object:0, line 3143 <- wrt source file
2025-07-17T07:05:47.0098740Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::all_gather_object:0
2025-07-17T07:05:47.0099530Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::send_object_list:0, line 3372 <- wrt source file
2025-07-17T07:05:47.0100400Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::send_object_list:0
2025-07-17T07:05:47.0101200Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::recv_object_list:0, line 3474 <- wrt source file
2025-07-17T07:05:47.0102030Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::recv_object_list:0
2025-07-17T07:05:47.0102840Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::broadcast_object_list:0, line 3588 <- wrt source file
2025-07-17T07:05:47.0103660Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::broadcast_object_list:0
2025-07-17T07:05:47.0104510Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::scatter_object_list:0, line 3711 <- wrt source file
2025-07-17T07:05:47.0105350Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::scatter_object_list:0
2025-07-17T07:05:47.0106160Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::all_gather_into_tensor:0, line 3920 <- wrt source file
2025-07-17T07:05:47.0106990Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::all_gather_into_tensor:0
2025-07-17T07:05:47.0107810Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::all_gather_coalesced:0, line 4058 <- wrt source file
2025-07-17T07:05:47.0108630Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::all_gather_coalesced:0
2025-07-17T07:05:47.0109420Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::gather:0, line 4164 <- wrt source file
2025-07-17T07:05:47.0110170Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py::gather:0
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2025-07-17T07:05:47.0155000Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/algorithms/join.py::Join:0
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2025-07-17T07:05:47.0239220Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/graph.py::Node.name:0
2025-07-17T07:05:47.0239930Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/graph.py::Node.register_hook:0, line 110 <- wrt source file
2025-07-17T07:05:47.0240660Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/graph.py::Node.register_hook:0
2025-07-17T07:05:47.0241400Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/graph.py::Node.register_prehook:0, line 147 <- wrt source file
2025-07-17T07:05:47.0242140Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/graph.py::Node.register_prehook:0
2025-07-17T07:05:47.0242870Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/graph.py::saved_tensors_hooks:0, line 271 <- wrt source file
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2025-07-17T07:05:47.0248100Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/graph.py::register_multi_grad_hook:0
2025-07-17T07:05:47.0248890Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/graph.py::allow_mutation_on_saved_tensors:0, line 741 <- wrt source file
2025-07-17T07:05:47.0249680Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/graph.py::allow_mutation_on_saved_tensors:0
2025-07-17T07:05:47.0250440Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/forward_ad.py::make_dual:0, line 82 <- wrt source file
2025-07-17T07:05:47.0251150Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/forward_ad.py::make_dual:0
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2025-07-17T07:05:47.0265370Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/grad_mode.py::enable_grad:0
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2025-07-17T07:05:47.0279000Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/function.py::FunctionCtx.mark_non_differentiable:0
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2025-07-17T07:05:47.0299930Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py::merge:0
2025-07-17T07:05:47.0300790Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py::merge_with:0, line 64 <- wrt source file
2025-07-17T07:05:47.0301670Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py::merge_with:0
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2025-07-17T07:05:47.0303410Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py::valmap:0
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2025-07-17T07:05:47.0305150Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py::keymap:0
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2025-07-17T07:05:47.0306860Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py::itemmap:0
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2025-07-17T07:05:47.0308600Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py::valfilter:0
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2025-07-17T07:05:47.0310380Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py::keyfilter:0
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2025-07-17T07:05:47.0312150Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py::itemfilter:0
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2025-07-17T07:05:47.0314060Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py::assoc:0
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2025-07-17T07:05:47.0315830Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py::dissoc:0
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2025-07-17T07:05:47.0317520Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py::first:0
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2025-07-17T07:05:47.0322380Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/more.py::reify_object:0
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2025-07-17T07:05:47.0324010Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/more.py::unify_object:0
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2025-07-17T07:05:47.0325650Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/utils.py::transitive_get:0
2025-07-17T07:05:47.0326450Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/utils.py::_toposort:0, line 42 <- wrt source file
2025-07-17T07:05:47.0327300Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/utils.py::_toposort:0
2025-07-17T07:05:47.0328110Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/utils.py::reverse_dict:0, line 70 <- wrt source file
2025-07-17T07:05:47.0328940Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/utils.py::reverse_dict:0
2025-07-17T07:05:47.0329740Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/utils.py::freeze:0, line 95 <- wrt source file
2025-07-17T07:05:47.0330520Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/utils.py::freeze:0
2025-07-17T07:05:47.0331330Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/match.py::VarDispatcher:0, line 48 <- wrt source file
2025-07-17T07:05:47.0332170Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/match.py::VarDispatcher:0
2025-07-17T07:05:47.0333070Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher:0, line 113 <- wrt source file
2025-07-17T07:05:47.0334010Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher:0
2025-07-17T07:05:47.0334980Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher.register:0, line 138 <- wrt source file
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2025-07-17T07:05:47.0336960Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher.add:0, line 191 <- wrt source file
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2025-07-17T07:05:47.0338930Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher.dispatch:0, line 304 <- wrt source file
2025-07-17T07:05:47.0339930Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher.dispatch:0
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2025-07-17T07:05:47.0341880Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::str_signature:0
2025-07-17T07:05:47.0342820Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/variadic.py::isvariadic:0, line 47 <- wrt source file
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2025-07-17T07:05:47.0344720Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/variadic.py::Variadic:0, line 83 <- wrt source file
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2025-07-17T07:05:47.0346580Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/core.py::dispatch:0, line 20 <- wrt source file
2025-07-17T07:05:47.0347480Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/core.py::dispatch:0
2025-07-17T07:05:47.0348390Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::expand_tuples:0, line 18 <- wrt source file
2025-07-17T07:05:47.0349340Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::expand_tuples:0
2025-07-17T07:05:47.0350270Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::_toposort:0, line 41 <- wrt source file
2025-07-17T07:05:47.0351180Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::_toposort:0
2025-07-17T07:05:47.0352090Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::reverse_dict:0, line 68 <- wrt source file
2025-07-17T07:05:47.0353000Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::reverse_dict:0
2025-07-17T07:05:47.0353910Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::groupby:0, line 87 <- wrt source file
2025-07-17T07:05:47.0354800Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::groupby:0
2025-07-17T07:05:47.0355700Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::typename:0, line 117 <- wrt source file
2025-07-17T07:05:47.0356600Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::typename:0
2025-07-17T07:05:47.0357400Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/passes/shape_prop.py::ShapeProp:0, line 99 <- wrt source file
2025-07-17T07:05:47.0358120Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/passes/shape_prop.py::ShapeProp:0
2025-07-17T07:05:47.0358850Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/passes/split_module.py::split_module:0, line 89 <- wrt source file
2025-07-17T07:05:47.0359590Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/passes/split_module.py::split_module:0
2025-07-17T07:05:47.0360370Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/passes/graph_drawer.py::FxGraphDrawer.get_dot_graph:0, line 129 <- wrt source file
2025-07-17T07:05:47.0361190Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/passes/graph_drawer.py::FxGraphDrawer.get_dot_graph:0
2025-07-17T07:05:47.0362150Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/passes/utils/matcher_with_name_node_map_utils.py::SubgraphMatcherWithNameNodeMap:0, line 51 <- wrt source file
2025-07-17T07:05:47.0363130Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/passes/utils/matcher_with_name_node_map_utils.py::SubgraphMatcherWithNameNodeMap:0
2025-07-17T07:05:47.0363990Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/gds.py::gds_register_buffer:0, line 42 <- wrt source file
2025-07-17T07:05:47.0485570Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/gds.py::gds_register_buffer:0
2025-07-17T07:05:47.0486360Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/gds.py::gds_deregister_buffer:0, line 58 <- wrt source file
2025-07-17T07:05:47.0487320Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/gds.py::gds_deregister_buffer:0
2025-07-17T07:05:47.0488100Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/gds.py::GdsFile:0, line 85 <- wrt source file
2025-07-17T07:05:47.0488780Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/gds.py::GdsFile:0
2025-07-17T07:05:47.0489490Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_jit_fn:0, line 114 <- wrt source file
2025-07-17T07:05:47.0490240Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_jit_fn:0
2025-07-17T07:05:47.0490970Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_jit_fn:1, line 125 <- wrt source file
2025-07-17T07:05:47.0491680Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_jit_fn:1
2025-07-17T07:05:47.0492390Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_jit_fn:2, line 140 <- wrt source file
2025-07-17T07:05:47.0493100Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_jit_fn:2
2025-07-17T07:05:47.0493840Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_multi_output_jit_fn:0, line 173 <- wrt source file
2025-07-17T07:05:47.0494620Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/jiterator.py::_create_multi_output_jit_fn:0
2025-07-17T07:05:47.0495350Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/profiler.py::profile:0, line 75 <- wrt source file
2025-07-17T07:05:47.0496030Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/profiler.py::profile:0
2025-07-17T07:05:47.0496750Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/masked/_ops.py::logaddexp:0, line 1530 <- wrt source file
2025-07-17T07:05:47.0497420Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/masked/_ops.py::logaddexp:0
2025-07-17T07:05:47.0498180Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/masked/maskedtensor/core.py::is_masked_tensor:0, line 25 <- wrt source file
2025-07-17T07:05:47.0498960Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/masked/maskedtensor/core.py::is_masked_tensor:0
2025-07-17T07:05:47.0499740Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::LambdaLR:0, line 280 <- wrt source file
2025-07-17T07:05:47.0500450Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::LambdaLR:0
2025-07-17T07:05:47.0501230Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::MultiplicativeLR:0, line 388 <- wrt source file
2025-07-17T07:05:47.0501980Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::MultiplicativeLR:0
2025-07-17T07:05:47.0502720Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::StepLR:0, line 491 <- wrt source file
2025-07-17T07:05:47.0503480Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::StepLR:0
2025-07-17T07:05:47.0504230Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::MultiStepLR:0, line 547 <- wrt source file
2025-07-17T07:05:47.0504950Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::MultiStepLR:0
2025-07-17T07:05:47.0505660Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::ConstantLR:0, line 608 <- wrt source file
2025-07-17T07:05:47.0506370Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::ConstantLR:0
2025-07-17T07:05:47.0507070Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::LinearLR:0, line 683 <- wrt source file
2025-07-17T07:05:47.0507770Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::LinearLR:0
2025-07-17T07:05:47.0508480Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::ExponentialLR:0, line 773 <- wrt source file
2025-07-17T07:05:47.0509210Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::ExponentialLR:0
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2025-07-17T07:05:47.0517410Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::PolynomialLR:0
2025-07-17T07:05:47.0518170Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingLR:0, line 1062 <- wrt source file
2025-07-17T07:05:47.0518920Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingLR:0
2025-07-17T07:05:47.0519670Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::ChainedScheduler:0, line 1134 <- wrt source file
2025-07-17T07:05:47.0520420Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::ChainedScheduler:0
2025-07-17T07:05:47.0521210Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:0, line 1794 <- wrt source file
2025-07-17T07:05:47.0522060Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:0
2025-07-17T07:05:47.0522980Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:1, line 1810 <- wrt source file
2025-07-17T07:05:47.0523830Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:1
2025-07-17T07:05:47.0524620Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/swa_utils.py::update_bn:0, line 337 <- wrt source file
2025-07-17T07:05:47.0525320Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/swa_utils.py::update_bn:0
2025-07-17T07:05:47.0526060Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_inductor/select_algorithm.py::add_preprocessing_fn:0, line 3289 <- wrt source file
2025-07-17T07:05:47.0526880Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_inductor/select_algorithm.py::add_preprocessing_fn:0
2025-07-17T07:05:47.0527720Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_inductor/cpp_builder.py::get_name_and_dir_from_output_file_path:0, line 1457 <- wrt source file
2025-07-17T07:05:47.0528660Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_inductor/cpp_builder.py::get_name_and_dir_from_output_file_path:0
2025-07-17T07:05:47.0529480Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_pytree.py::register_dataclass:0, line 307 <- wrt source file
2025-07-17T07:05:47.0530230Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_pytree.py::register_dataclass:0
2025-07-17T07:05:47.0530970Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_pytree.py::register_constant:0, line 423 <- wrt source file
2025-07-17T07:05:47.0531710Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_pytree.py::register_constant:0
2025-07-17T07:05:47.0532460Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_pytree.py::tree_is_leaf:0, line 1030 <- wrt source file
2025-07-17T07:05:47.0533170Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_pytree.py::tree_is_leaf:0
2025-07-17T07:05:47.0533950Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_pytree.py::tree_map:0, line 1349 <- wrt source file
2025-07-17T07:05:47.0534650Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_pytree.py::tree_map:0
2025-07-17T07:05:47.0535400Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/checkpoint.py::checkpoint_sequential:0, line 547 <- wrt source file
2025-07-17T07:05:47.0536190Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/checkpoint.py::checkpoint_sequential:0
2025-07-17T07:05:47.0536990Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/checkpoint.py::set_checkpoint_early_stop:0, line 749 <- wrt source file
2025-07-17T07:05:47.0537790Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/checkpoint.py::set_checkpoint_early_stop:0
2025-07-17T07:05:47.0538630Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/backend_registration.py::rename_privateuse1_backend:0, line 69 <- wrt source file
2025-07-17T07:05:47.0539500Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/backend_registration.py::rename_privateuse1_backend:0
2025-07-17T07:05:47.0540450Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/backend_registration.py::generate_methods_for_privateuse1_backend:0, line 375 <- wrt source file
2025-07-17T07:05:47.0541440Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/backend_registration.py::generate_methods_for_privateuse1_backend:0
2025-07-17T07:05:47.0542320Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/backend_registration.py::_get_custom_mod_func:0, line 410 <- wrt source file
2025-07-17T07:05:47.0543140Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/backend_registration.py::_get_custom_mod_func:0
2025-07-17T07:05:47.0544120Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/dlpack.py::from_dlpack:0, line 80 <- wrt source file
2025-07-17T07:05:47.0544840Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/dlpack.py::from_dlpack:0
2025-07-17T07:05:47.0545530Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_is_leaf:0, line 277 <- wrt source file
2025-07-17T07:05:47.0546230Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_is_leaf:0
2025-07-17T07:05:47.0547050Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_flatten:0, line 320 <- wrt source file
2025-07-17T07:05:47.0547890Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_flatten:0
2025-07-17T07:05:47.0548590Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_unflatten:0, line 357 <- wrt source file
2025-07-17T07:05:47.0549310Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_unflatten:0
2025-07-17T07:05:47.0550020Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_iter:0, line 387 <- wrt source file
2025-07-17T07:05:47.0550710Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_iter:0
2025-07-17T07:05:47.0551410Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_leaves:0, line 422 <- wrt source file
2025-07-17T07:05:47.0552110Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_leaves:0
2025-07-17T07:05:47.0552820Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_structure:0, line 457 <- wrt source file
2025-07-17T07:05:47.0553540Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_structure:0
2025-07-17T07:05:47.0554240Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_map:0, line 494 <- wrt source file
2025-07-17T07:05:47.0554930Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::tree_map:0
2025-07-17T07:05:47.0555640Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::broadcast_prefix:0, line 910 <- wrt source file
2025-07-17T07:05:47.0556430Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py::broadcast_prefix:0
2025-07-17T07:05:47.0557230Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_sympy/functions.py::MinMaxBase._collapse_arguments:0, line 718 <- wrt source file
2025-07-17T07:05:47.0558090Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_sympy/functions.py::MinMaxBase._collapse_arguments:0
2025-07-17T07:05:47.0558900Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/hipify/hipify_python.py::find_closure_group:0, line 439 <- wrt source file
2025-07-17T07:05:47.0559700Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/hipify/hipify_python.py::find_closure_group:0
2025-07-17T07:05:47.0560530Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/hipify/hipify_python.py::replace_extern_shared:0, line 535 <- wrt source file
2025-07-17T07:05:47.0561380Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/hipify/hipify_python.py::replace_extern_shared:0
2025-07-17T07:05:47.0562190Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.__init__:0, line 216 <- wrt source file
2025-07-17T07:05:47.0563010Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.__init__:0
2025-07-17T07:05:47.0563830Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_hparams:0, line 314 <- wrt source file
2025-07-17T07:05:47.0564660Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_hparams:0
2025-07-17T07:05:47.0565520Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalar:0, line 362 <- wrt source file
2025-07-17T07:05:47.0566350Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalar:0
2025-07-17T07:05:47.0567170Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalars:0, line 394 <- wrt source file
2025-07-17T07:05:47.0568000Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalars:0
2025-07-17T07:05:47.0568830Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_tensor:0, line 441 <- wrt source file
2025-07-17T07:05:47.0569650Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_tensor:0
2025-07-17T07:05:47.0570490Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram:0, line 480 <- wrt source file
2025-07-17T07:05:47.0571340Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram:0
2025-07-17T07:05:47.0572180Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram_raw:0, line 533 <- wrt source file
2025-07-17T07:05:47.0573050Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram_raw:0
2025-07-17T07:05:47.0573920Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_image:0, line 599 <- wrt source file
2025-07-17T07:05:47.0574770Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_image:0
2025-07-17T07:05:47.0575580Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_images:0, line 648 <- wrt source file
2025-07-17T07:05:47.0576410Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_images:0
2025-07-17T07:05:47.0577250Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_text:0, line 811 <- wrt source file
2025-07-17T07:05:47.0578080Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_text:0
2025-07-17T07:05:47.0578910Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_embedding:0, line 878 <- wrt source file
2025-07-17T07:05:47.0579750Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_embedding:0
2025-07-17T07:05:47.0580590Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_pr_curve:0, line 989 <- wrt source file
2025-07-17T07:05:47.0581440Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_pr_curve:0
2025-07-17T07:05:47.0582380Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_multilinechart:0, line 1063 <- wrt source file
2025-07-17T07:05:47.0583330Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_multilinechart:0
2025-07-17T07:05:47.0584270Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_marginchart:0, line 1084 <- wrt source file
2025-07-17T07:05:47.0585270Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_marginchart:0
2025-07-17T07:05:47.0586170Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars:0, line 1108 <- wrt source file
2025-07-17T07:05:47.0587050Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars:0
2025-07-17T07:05:47.0587900Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_mesh:0, line 1154 <- wrt source file
2025-07-17T07:05:47.0588710Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_mesh:0
2025-07-17T07:05:47.0589490Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/dataset.py::IterableDataset:0, line 94 <- wrt source file
2025-07-17T07:05:47.0590320Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/dataset.py::IterableDataset:0
2025-07-17T07:05:47.0591060Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/dataset.py::StackDataset:0, line 219 <- wrt source file
2025-07-17T07:05:47.0591810Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/dataset.py::StackDataset:0
2025-07-17T07:05:47.0592530Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/dataset.py::random_split:0, line 441 <- wrt source file
2025-07-17T07:05:47.0593250Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/dataset.py::random_split:0
2025-07-17T07:05:47.0593970Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/sampler.py::Sampler:0, line 40 <- wrt source file
2025-07-17T07:05:47.0594690Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/sampler.py::Sampler:0
2025-07-17T07:05:47.0595450Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/sampler.py::WeightedRandomSampler:0, line 238 <- wrt source file
2025-07-17T07:05:47.0596240Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/sampler.py::WeightedRandomSampler:0
2025-07-17T07:05:47.0596990Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/sampler.py::BatchSampler:0, line 301 <- wrt source file
2025-07-17T07:05:47.0597710Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/sampler.py::BatchSampler:0
2025-07-17T07:05:47.0598460Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/_utils/collate.py::default_convert:0, line 39 <- wrt source file
2025-07-17T07:05:47.0599230Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/_utils/collate.py::default_convert:0
2025-07-17T07:05:47.0599980Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/_utils/collate.py::collate:0, line 137 <- wrt source file
2025-07-17T07:05:47.0600700Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/_utils/collate.py::collate:0
2025-07-17T07:05:47.0601440Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/_utils/collate.py::default_collate:0, line 364 <- wrt source file
2025-07-17T07:05:47.0602210Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/_utils/collate.py::default_collate:0
2025-07-17T07:05:47.0603000Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/datapipe.py::IterDataPipe:0, line 97 <- wrt source file
2025-07-17T07:05:47.0603790Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/datapipe.py::IterDataPipe:0
2025-07-17T07:05:47.0604580Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/datapipe.py::MapDataPipe:0, line 264 <- wrt source file
2025-07-17T07:05:47.0605370Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/datapipe.py::MapDataPipe:0
2025-07-17T07:05:47.0606220Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/fileopener.py::FileOpenerIterDataPipe:0, line 35 <- wrt source file
2025-07-17T07:05:47.0607140Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/fileopener.py::FileOpenerIterDataPipe:0
2025-07-17T07:05:47.0608020Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/callable.py::MapperIterDataPipe:0, line 52 <- wrt source file
2025-07-17T07:05:47.0608920Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/callable.py::MapperIterDataPipe:0
2025-07-17T07:05:47.0609780Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/callable.py::CollatorIterDataPipe:0, line 198 <- wrt source file
2025-07-17T07:05:47.0610650Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/callable.py::CollatorIterDataPipe:0
2025-07-17T07:05:47.0611530Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/grouping.py::BatcherIterDataPipe:0, line 53 <- wrt source file
2025-07-17T07:05:47.1043190Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/grouping.py::BatcherIterDataPipe:0
2025-07-17T07:05:47.1044180Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/grouping.py::UnBatcherIterDataPipe:0, line 113 <- wrt source file
2025-07-17T07:05:47.1045080Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/grouping.py::UnBatcherIterDataPipe:0
2025-07-17T07:05:47.1045960Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/grouping.py::GrouperIterDataPipe:0, line 180 <- wrt source file
2025-07-17T07:05:47.1046830Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/grouping.py::GrouperIterDataPipe:0
2025-07-17T07:05:47.1047690Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/selecting.py::FilterIterDataPipe:0, line 37 <- wrt source file
2025-07-17T07:05:47.1048560Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/selecting.py::FilterIterDataPipe:0
2025-07-17T07:05:47.1049420Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::ConcaterIterDataPipe:0, line 38 <- wrt source file
2025-07-17T07:05:47.1050300Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::ConcaterIterDataPipe:0
2025-07-17T07:05:47.1051170Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::ForkerIterDataPipe:0, line 88 <- wrt source file
2025-07-17T07:05:47.1052040Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::ForkerIterDataPipe:0
2025-07-17T07:05:47.1052890Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::_ChildDataPipe:0, line 307 <- wrt source file
2025-07-17T07:05:47.1053730Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::_ChildDataPipe:0
2025-07-17T07:05:47.1054600Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::DemultiplexerIterDataPipe:0, line 393 <- wrt source file
2025-07-17T07:05:47.1055680Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::DemultiplexerIterDataPipe:0
2025-07-17T07:05:47.1056630Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::MultiplexerIterDataPipe:0, line 603 <- wrt source file
2025-07-17T07:05:47.1057610Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::MultiplexerIterDataPipe:0
2025-07-17T07:05:47.1058520Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::ZipperIterDataPipe:0, line 671 <- wrt source file
2025-07-17T07:05:47.1059580Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combining.py::ZipperIterDataPipe:0
2025-07-17T07:05:47.1060530Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/filelister.py::FileListerIterDataPipe:0, line 30 <- wrt source file
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2025-07-17T07:05:47.1062320Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/utils.py::IterableWrapperIterDataPipe:0, line 29 <- wrt source file
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2025-07-17T07:05:47.1064120Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/combinatorics.py::ShufflerIterDataPipe:0, line 88 <- wrt source file
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2025-07-17T07:05:47.1066040Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/streamreader.py::StreamReaderIterDataPipe:0, line 25 <- wrt source file
2025-07-17T07:05:47.1066960Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/iter/streamreader.py::StreamReaderIterDataPipe:0
2025-07-17T07:05:47.1067830Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/utils/decoder.py::basichandlers:0, line 47 <- wrt source file
2025-07-17T07:05:47.1068650Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/utils/decoder.py::basichandlers:0
2025-07-17T07:05:47.1069490Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/utils/common.py::validate_input_col:0, line 37 <- wrt source file
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2025-07-17T07:05:47.1074670Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/map/combining.py::ConcaterMapDataPipe:0, line 29 <- wrt source file
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2025-07-17T07:05:47.1076400Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/map/combining.py::ZipperMapDataPipe:0, line 73 <- wrt source file
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2025-07-17T07:05:47.1078170Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/map/utils.py::SequenceWrapperMapDataPipe:0, line 29 <- wrt source file
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2025-07-17T07:05:47.1079940Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/datapipes/map/combinatorics.py::ShufflerIterDataPipe:0, line 34 <- wrt source file
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2025-07-17T07:05:47.1081640Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/testing/_creation.py::make_tensor:0, line 114 <- wrt source file
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2025-07-17T07:05:47.1086220Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/testing/_internal/common_utils.py::decorateIf:0, line 824 <- wrt source file
2025-07-17T07:05:47.1086990Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/testing/_internal/common_utils.py::decorateIf:0
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2025-07-17T07:05:47.1091300Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/testing/_internal/common_utils.py::random_hermitian_pd_matrix:0, line 4775 <- wrt source file
2025-07-17T07:05:47.1092140Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/testing/_internal/common_utils.py::random_hermitian_pd_matrix:0
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2025-07-17T07:05:47.1093770Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/testing/_internal/logging_utils.py::logs_to_string:0
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2025-07-17T07:05:47.1095450Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/testing/_internal/logging_utils.py::multiple_logs_to_string:0
2025-07-17T07:05:47.1096340Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/testing/_internal/distributed/_tensor/common_dtensor.py::skip_unless_torch_gpu:0, line 327 <- wrt source file
2025-07-17T07:05:47.1097270Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/testing/_internal/distributed/_tensor/common_dtensor.py::skip_unless_torch_gpu:0
2025-07-17T07:05:47.1098220Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/testing/_internal/optests/autograd_registration.py::autograd_registration_check:0, line 29 <- wrt source file
2025-07-17T07:05:47.1099170Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/testing/_internal/optests/autograd_registration.py::autograd_registration_check:0
2025-07-17T07:05:47.1100020Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/infer_schema.py::infer_schema:0, line 51 <- wrt source file
2025-07-17T07:05:47.1100780Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/infer_schema.py::infer_schema:0
2025-07-17T07:05:47.1101510Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/custom_ops.py::custom_op:0, line 98 <- wrt source file
2025-07-17T07:05:47.1102250Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/custom_ops.py::custom_op:0
2025-07-17T07:05:47.1103040Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.set_kernel_enabled:0, line 237 <- wrt source file
2025-07-17T07:05:47.1103860Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.set_kernel_enabled:0
2025-07-17T07:05:47.1104660Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_kernel:0, line 306 <- wrt source file
2025-07-17T07:05:47.1105450Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_kernel:0
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2025-07-17T07:05:47.1107110Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autograd:0
2025-07-17T07:05:47.1107910Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_vmap:0, line 708 <- wrt source file
2025-07-17T07:05:47.1108770Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_vmap:0
2025-07-17T07:05:47.1109550Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autocast:0, line 794 <- wrt source file
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2025-07-17T07:05:47.1111200Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/fake_impl.py::FakeImplCtx.new_dynamic_size:0, line 175 <- wrt source file
2025-07-17T07:05:47.1112050Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/fake_impl.py::FakeImplCtx.new_dynamic_size:0
2025-07-17T07:05:47.1112840Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/fake_class_registry.py::register_fake_class:0, line 197 <- wrt source file
2025-07-17T07:05:47.1113630Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/fake_class_registry.py::register_fake_class:0
2025-07-17T07:05:47.1114370Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/amp/grad_scaler.py::GradScaler:0, line 64 <- wrt source file
2025-07-17T07:05:47.1115070Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/amp/grad_scaler.py::GradScaler:0
2025-07-17T07:05:47.1115810Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/jit/_check.py::AttributeTypeIsSupportedChecker:0, line 36 <- wrt source file
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2025-07-17T07:05:47.1118180Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/jit/mobile/__init__.py::_load_for_lite_interpreter:0
2025-07-17T07:05:47.1118970Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/jit/mobile/__init__.py::_get_mobile_model_contained_types:0, line 122 <- wrt source file
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2025-07-17T07:05:47.1120590Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/jit/mobile/__init__.py::_get_model_ops_and_info:0, line 214 <- wrt source file
2025-07-17T07:05:47.1121350Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/jit/mobile/__init__.py::_get_model_ops_and_info:0
2025-07-17T07:05:47.1122110Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_dynamo/decorators.py::substitute_in_graph:0, line 344 <- wrt source file
2025-07-17T07:05:47.1122910Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_dynamo/decorators.py::substitute_in_graph:0
2025-07-17T07:05:47.1123720Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_dynamo/variables/base.py::VariableTracker.python_type:0, line 322 <- wrt source file
2025-07-17T07:05:47.1124560Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_dynamo/variables/base.py::VariableTracker.python_type:0
2025-07-17T07:05:47.1125360Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/functional.py::conv1d:0, line 211 <- wrt source file
2025-07-17T07:05:47.1126130Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/functional.py::conv1d:0
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2025-07-17T07:05:47.1127720Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/functional.py::conv2d:0
2025-07-17T07:05:47.1128480Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/functional.py::conv3d:0, line 359 <- wrt source file
2025-07-17T07:05:47.1129250Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/functional.py::conv3d:0
2025-07-17T07:05:47.1130010Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/__init__.py::Quantize:0, line 95 <- wrt source file
2025-07-17T07:05:47.1130780Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/__init__.py::Quantize:0
2025-07-17T07:05:47.1131560Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/__init__.py::DeQuantize:0, line 145 <- wrt source file
2025-07-17T07:05:47.1132350Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/__init__.py::DeQuantize:0
2025-07-17T07:05:47.1133150Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/linear.py::Linear:0, line 30 <- wrt source file
2025-07-17T07:05:47.1133950Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/linear.py::Linear:0
2025-07-17T07:05:47.1134750Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv1d:0, line 43 <- wrt source file
2025-07-17T07:05:47.1135550Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv1d:0
2025-07-17T07:05:47.1136340Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv2d:0, line 124 <- wrt source file
2025-07-17T07:05:47.1137140Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv2d:0
2025-07-17T07:05:47.1137930Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv3d:0, line 209 <- wrt source file
2025-07-17T07:05:47.1138720Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv3d:0
2025-07-17T07:05:47.1139580Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose1d:0, line 296 <- wrt source file
2025-07-17T07:05:47.1140440Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose1d:0
2025-07-17T07:05:47.1141310Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose2d:0, line 378 <- wrt source file
2025-07-17T07:05:47.1142150Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose2d:0
2025-07-17T07:05:47.1143030Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose3d:0, line 460 <- wrt source file
2025-07-17T07:05:47.1144030Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose3d:0
2025-07-17T07:05:47.1144920Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTM:0, line 515 <- wrt source file
2025-07-17T07:05:47.1145700Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTM:0
2025-07-17T07:05:47.1146470Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRU:0, line 801 <- wrt source file
2025-07-17T07:05:47.1147240Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRU:0
2025-07-17T07:05:47.1148030Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::RNNCell:0, line 1206 <- wrt source file
2025-07-17T07:05:47.1148830Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::RNNCell:0
2025-07-17T07:05:47.1149620Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTMCell:0, line 1273 <- wrt source file
2025-07-17T07:05:47.1150450Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTMCell:0
2025-07-17T07:05:47.1151370Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRUCell:0, line 1326 <- wrt source file
2025-07-17T07:05:47.1152160Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRUCell:0
2025-07-17T07:05:47.1153000Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::FloatFunctional:0, line 23 <- wrt source file
2025-07-17T07:05:47.1153880Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::FloatFunctional:0
2025-07-17T07:05:47.1161500Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::QFunctional:0, line 176 <- wrt source file
2025-07-17T07:05:47.1162370Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::QFunctional:0
2025-07-17T07:05:47.1163190Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/linear.py::Linear:0, line 138 <- wrt source file
2025-07-17T07:05:47.1164080Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/linear.py::Linear:0
2025-07-17T07:05:47.1164880Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/activation.py::ReLU6:0, line 36 <- wrt source file
2025-07-17T07:05:47.1165690Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/activation.py::ReLU6:0
2025-07-17T07:05:47.1166460Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv2d:0, line 505 <- wrt source file
2025-07-17T07:05:47.1167210Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv2d:0
2025-07-17T07:05:47.1167990Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv3d:0, line 635 <- wrt source file
2025-07-17T07:05:47.1168790Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv3d:0
2025-07-17T07:05:47.1169570Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose1d:0, line 892 <- wrt source file
2025-07-17T07:05:47.1170360Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose1d:0
2025-07-17T07:05:47.1171180Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose2d:0, line 1014 <- wrt source file
2025-07-17T07:05:47.1171980Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose2d:0
2025-07-17T07:05:47.1172810Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose3d:0, line 1140 <- wrt source file
2025-07-17T07:05:47.1173600Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose3d:0
2025-07-17T07:05:47.1174420Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::Embedding:0, line 111 <- wrt source file
2025-07-17T07:05:47.1175240Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::Embedding:0
2025-07-17T07:05:47.1176060Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::EmbeddingBag:0, line 275 <- wrt source file
2025-07-17T07:05:47.1176900Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::EmbeddingBag:0
2025-07-17T07:05:47.1177700Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTMCell:0, line 30 <- wrt source file
2025-07-17T07:05:47.1178470Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTMCell:0
2025-07-17T07:05:47.1179220Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTM:0, line 413 <- wrt source file
2025-07-17T07:05:47.1179970Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTM:0
2025-07-17T07:05:47.1180780Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/intrinsic/qat/modules/linear_relu.py::LinearReLU:0, line 30 <- wrt source file
2025-07-17T07:05:47.1181650Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/intrinsic/qat/modules/linear_relu.py::LinearReLU:0
2025-07-17T07:05:47.1182570Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.py::LinearReLU:0, line 24 <- wrt source file
2025-07-17T07:05:47.1183490Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.py::LinearReLU:0
2025-07-17T07:05:47.1184380Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearReLU:0, line 25 <- wrt source file
2025-07-17T07:05:47.1185270Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearReLU:0
2025-07-17T07:05:47.1186180Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearLeakyReLU:0, line 67 <- wrt source file
2025-07-17T07:05:47.1187080Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearLeakyReLU:0
2025-07-17T07:05:47.1187970Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearTanh:0, line 142 <- wrt source file
2025-07-17T07:05:47.1188850Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearTanh:0
2025-07-17T07:05:47.1189660Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/observer.py::_with_args:0, line 110 <- wrt source file
2025-07-17T07:05:47.1190430Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/observer.py::_with_args:0
2025-07-17T07:05:47.1192920Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/observer.py::_with_callable_args:0, line 132 <- wrt source file
2025-07-17T07:05:47.1195250Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/observer.py::_with_callable_args:0
2025-07-17T07:05:47.1197510Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fuse_modules.py::fuse_modules:0, line 176 <- wrt source file
2025-07-17T07:05:47.1199800Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fuse_modules.py::fuse_modules:0
2025-07-17T07:05:47.1202020Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/utils.py::get_combined_dict:0, line 149 <- wrt source file
2025-07-17T07:05:47.1204200Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/utils.py::get_combined_dict:0
2025-07-17T07:05:47.1206390Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_path_of_module:0, line 521 <- wrt source file
2025-07-17T07:05:47.1208590Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_path_of_module:0
2025-07-17T07:05:47.1211140Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_signature_locals:0, line 543 <- wrt source file
2025-07-17T07:05:47.1213380Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_signature_locals:0
2025-07-17T07:05:47.1215720Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_default_kwargs:0, line 557 <- wrt source file
2025-07-17T07:05:47.1220800Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_default_kwargs:0
2025-07-17T07:05:47.1223200Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_normalize_kwargs:0, line 579 <- wrt source file
2025-07-17T07:05:47.1225590Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_normalize_kwargs:0
2025-07-17T07:05:47.1227880Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_num_pos_args:0, line 706 <- wrt source file
2025-07-17T07:05:47.1230040Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/utils.py::_get_num_pos_args:0
2025-07-17T07:05:47.1232300Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn:0, line 31 <- wrt source file
2025-07-17T07:05:47.1234640Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn:0
2025-07-17T07:05:47.1237020Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn_relu:0, line 76 <- wrt source file
2025-07-17T07:05:47.1239440Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn_relu:0
2025-07-17T07:05:47.1241850Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_linear_bn:0, line 130 <- wrt source file
2025-07-17T07:05:47.1244230Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_linear_bn:0
2025-07-17T07:05:47.1246650Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_convtranspose_bn:0, line 163 <- wrt source file
2025-07-17T07:05:47.1249130Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_convtranspose_bn:0
2025-07-17T07:05:47.1251490Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_pt2e:0, line 51 <- wrt source file
2025-07-17T07:05:47.1253720Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_pt2e:0
2025-07-17T07:05:47.1255990Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_qat_pt2e:0, line 130 <- wrt source file
2025-07-17T07:05:47.1258290Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_qat_pt2e:0
2025-07-17T07:05:47.1259970Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_pt2e.py::convert_pt2e:0, line 228 <- wrt source file
2025-07-17T07:05:47.1260890Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_pt2e.py::convert_pt2e:0
2025-07-17T07:05:47.1261690Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::fuse_fx:0, line 218 <- wrt source file
2025-07-17T07:05:47.1262550Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::fuse_fx:0
2025-07-17T07:05:47.1263330Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::prepare_fx:0, line 288 <- wrt source file
2025-07-17T07:05:47.1264140Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::prepare_fx:0
2025-07-17T07:05:47.1264970Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::prepare_qat_fx:0, line 427 <- wrt source file
2025-07-17T07:05:47.1265810Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::prepare_qat_fx:0
2025-07-17T07:05:47.1266590Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::convert_fx:0, line 608 <- wrt source file
2025-07-17T07:05:47.1267370Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::convert_fx:0
2025-07-17T07:05:47.1268190Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::convert_to_reference_fx:0, line 668 <- wrt source file
2025-07-17T07:05:47.1269040Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::convert_to_reference_fx:0
2025-07-17T07:05:47.1269920Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::_convert_to_reference_decomposed_fx:0, line 720 <- wrt source file
2025-07-17T07:05:47.1270830Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/quantize_fx.py::_convert_to_reference_decomposed_fx:0
2025-07-17T07:05:47.1271770Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/backend_config/onednn.py::_fuse_linear_bn_leaky_relu:0, line 85 <- wrt source file
2025-07-17T07:05:47.1272710Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/backend_config/onednn.py::_fuse_linear_bn_leaky_relu:0
2025-07-17T07:05:47.1273700Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/pt2e/utils.py::_replace_literals_with_new_placeholders:0, line 436 <- wrt source file
2025-07-17T07:05:47.1274710Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/pt2e/utils.py::_replace_literals_with_new_placeholders:0
2025-07-17T07:05:47.1275690Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_get_reduction_params:0, line 102 <- wrt source file
2025-07-17T07:05:47.1276650Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_get_reduction_params:0
2025-07-17T07:05:47.1277580Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_register_custom_op:0, line 148 <- wrt source file
2025-07-17T07:05:47.1278590Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_register_custom_op:0
2025-07-17T07:05:47.1279590Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/pt2e/prepare.py::_get_edge_or_node_to_group_id:0, line 188 <- wrt source file
2025-07-17T07:05:47.1280560Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/pt2e/prepare.py::_get_edge_or_node_to_group_id:0
2025-07-17T07:05:47.1281490Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier:0, line 47 <- wrt source file
2025-07-17T07:05:47.1282390Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier:0
2025-07-17T07:05:47.1283390Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/pruning/_experimental/data_sparsifier/base_data_sparsifier.py::BaseDataSparsifier:0, line 55 <- wrt source file
2025-07-17T07:05:47.1284500Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/pruning/_experimental/data_sparsifier/base_data_sparsifier.py::BaseDataSparsifier:0
2025-07-17T07:05:47.1285450Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/pruning/scheduler/lambda_scheduler.py::LambdaSL:0, line 24 <- wrt source file
2025-07-17T07:05:47.1286320Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/pruning/scheduler/lambda_scheduler.py::LambdaSL:0
2025-07-17T07:05:47.1287220Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/profiler/profiler.py::_KinetoProfile.toggle_collection_dynamic:0, line 295 <- wrt source file
2025-07-17T07:05:47.1288160Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/profiler/profiler.py::_KinetoProfile.toggle_collection_dynamic:0
2025-07-17T07:05:47.1289000Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/profiler/profiler.py::profile:0, line 617 <- wrt source file
2025-07-17T07:05:47.1289770Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/profiler/profiler.py::profile:0
2025-07-17T07:05:47.1290580Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/sparse/semi_structured.py::to_sparse_semi_structured:0, line 339 <- wrt source file
2025-07-17T07:05:47.1291450Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/sparse/semi_structured.py::to_sparse_semi_structured:0
2025-07-17T07:05:47.1292250Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::Dim:0, line 103 <- wrt source file
2025-07-17T07:05:47.1292990Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::Dim:0
2025-07-17T07:05:47.1293800Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:0, line 715 <- wrt source file
2025-07-17T07:05:47.1294590Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:0
2025-07-17T07:05:47.1295350Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:1, line 731 <- wrt source file
2025-07-17T07:05:47.1296180Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:1
2025-07-17T07:05:47.1297010Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::AdditionalInputs:0, line 815 <- wrt source file
2025-07-17T07:05:47.1297800Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/export/dynamic_shapes.py::AdditionalInputs:0
2025-07-17T07:05:47.1298640Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/inverse_gamma.py::InverseGamma:0, line 24 <- wrt source file
2025-07-17T07:05:47.1300560Z Running test_autoload_disable 1/1 ... [2025-07-17 07:05:47.126662]
2025-07-17T07:05:47.1301100Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/inverse_gamma.py::InverseGamma:0
2025-07-17T07:05:47.1301970Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/laplace.py::Laplace:0, line 20 <- wrt source file
2025-07-17T07:05:47.1302710Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/laplace.py::Laplace:0
2025-07-17T07:05:47.1303460Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/categorical.py::Categorical:0, line 42 <- wrt source file
2025-07-17T07:05:47.1304240Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/categorical.py::Categorical:0
2025-07-17T07:05:47.1305050Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/transforms.py::CatTransform:0, line 1065 <- wrt source file
2025-07-17T07:05:47.1305820Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/transforms.py::CatTransform:0
2025-07-17T07:05:47.1306600Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/transforms.py::StackTransform:0, line 1177 <- wrt source file
2025-07-17T07:05:47.1307390Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/transforms.py::StackTransform:0
2025-07-17T07:05:47.1308230Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/transforms.py::CumulativeDistributionTransform:0, line 1253 <- wrt source file
2025-07-17T07:05:47.1309170Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/transforms.py::CumulativeDistributionTransform:0
2025-07-17T07:05:47.1310000Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/dirichlet.py::Dirichlet:0, line 42 <- wrt source file
2025-07-17T07:05:47.1310810Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/dirichlet.py::Dirichlet:0
2025-07-17T07:05:47.1311580Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/log_normal.py::LogNormal:0, line 23 <- wrt source file
2025-07-17T07:05:47.1312320Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/log_normal.py::LogNormal:0
2025-07-17T07:05:47.1313050Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/geometric.py::Geometric:0, line 36 <- wrt source file
2025-07-17T07:05:47.1313790Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/geometric.py::Geometric:0
2025-07-17T07:05:47.1314600Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/generalized_pareto.py::GeneralizedPareto:0, line 26 <- wrt source file
2025-07-17T07:05:47.1315450Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/generalized_pareto.py::GeneralizedPareto:0
2025-07-17T07:05:47.1316280Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/weibull.py::Weibull:0, line 22 <- wrt source file
2025-07-17T07:05:47.1316990Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/weibull.py::Weibull:0
2025-07-17T07:05:47.1317710Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/studentT.py::StudentT:0, line 22 <- wrt source file
2025-07-17T07:05:47.1318440Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/studentT.py::StudentT:0
2025-07-17T07:05:47.1319280Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/multivariate_normal.py::MultivariateNormal:0, line 103 <- wrt source file
2025-07-17T07:05:47.1320160Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/multivariate_normal.py::MultivariateNormal:0
2025-07-17T07:05:47.1320940Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/normal.py::Normal:0, line 22 <- wrt source file
2025-07-17T07:05:47.1321650Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/normal.py::Normal:0
2025-07-17T07:05:47.1322390Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/poisson.py::Poisson:0, line 25 <- wrt source file
2025-07-17T07:05:47.1323110Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/poisson.py::Poisson:0
2025-07-17T07:05:47.1323810Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/beta.py::Beta:0, line 21 <- wrt source file
2025-07-17T07:05:47.1324490Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/beta.py::Beta:0
2025-07-17T07:05:47.1325220Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/kumaraswamy.py::Kumaraswamy:0, line 30 <- wrt source file
2025-07-17T07:05:47.1325970Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/kumaraswamy.py::Kumaraswamy:0
2025-07-17T07:05:47.1326750Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/half_normal.py::HalfNormal:0, line 24 <- wrt source file
2025-07-17T07:05:47.1327510Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/half_normal.py::HalfNormal:0
2025-07-17T07:05:47.1328250Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/half_cauchy.py::HalfCauchy:0, line 24 <- wrt source file
2025-07-17T07:05:47.1329000Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/half_cauchy.py::HalfCauchy:0
2025-07-17T07:05:47.1329750Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/lkj_cholesky.py::LKJCholesky:0, line 43 <- wrt source file
2025-07-17T07:05:47.1330510Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/lkj_cholesky.py::LKJCholesky:0
2025-07-17T07:05:47.1331290Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/independent.py::Independent:0, line 27 <- wrt source file
2025-07-17T07:05:47.1332110Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/independent.py::Independent:0
2025-07-17T07:05:47.1332950Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/multinomial.py::Multinomial:0, line 38 <- wrt source file
2025-07-17T07:05:47.1333770Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/multinomial.py::Multinomial:0
2025-07-17T07:05:47.1334580Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/exponential.py::Exponential:0, line 20 <- wrt source file
2025-07-17T07:05:47.1335390Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/exponential.py::Exponential:0
2025-07-17T07:05:47.1336150Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/pareto.py::Pareto:0, line 20 <- wrt source file
2025-07-17T07:05:47.1336870Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/pareto.py::Pareto:0
2025-07-17T07:05:47.1337630Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/cauchy.py::Cauchy:0, line 23 <- wrt source file
2025-07-17T07:05:47.1338400Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/cauchy.py::Cauchy:0
2025-07-17T07:05:47.1339130Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/von_mises.py::VonMises:0, line 117 <- wrt source file
2025-07-17T07:05:47.1339880Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/von_mises.py::VonMises:0
2025-07-17T07:05:47.1340610Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/gumbel.py::Gumbel:0, line 23 <- wrt source file
2025-07-17T07:05:47.1356620Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/gumbel.py::Gumbel:0
2025-07-17T07:05:47.1357330Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/utils.py::clamp_probs:0, line 114 <- wrt source file
2025-07-17T07:05:47.1358060Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/utils.py::clamp_probs:0
2025-07-17T07:05:47.1358860Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/continuous_bernoulli.py::ContinuousBernoulli:0, line 35 <- wrt source file
2025-07-17T07:05:47.1359740Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/continuous_bernoulli.py::ContinuousBernoulli:0
2025-07-17T07:05:47.1360600Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/fishersnedecor.py::FisherSnedecor:0, line 21 <- wrt source file
2025-07-17T07:05:47.1361420Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/fishersnedecor.py::FisherSnedecor:0
2025-07-17T07:05:47.1362200Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/constraints.py::is_dependent:0, line 166 <- wrt source file
2025-07-17T07:05:47.1362970Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/constraints.py::is_dependent:0
2025-07-17T07:05:47.1364110Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/constraints.py::_DependentProperty:0, line 187 <- wrt source file
2025-07-17T07:05:47.1364930Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/constraints.py::_DependentProperty:0
2025-07-17T07:05:47.1365740Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/uniform.py::Uniform:0, line 21 <- wrt source file
2025-07-17T07:05:47.1366450Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/uniform.py::Uniform:0
2025-07-17T07:05:47.1367180Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/bernoulli.py::Bernoulli:0, line 30 <- wrt source file
2025-07-17T07:05:47.1367950Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/bernoulli.py::Bernoulli:0
2025-07-17T07:05:47.1368740Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/logistic_normal.py::LogisticNormal:0, line 28 <- wrt source file
2025-07-17T07:05:47.1369540Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/logistic_normal.py::LogisticNormal:0
2025-07-17T07:05:47.1370350Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/one_hot_categorical.py::OneHotCategorical:0, line 34 <- wrt source file
2025-07-17T07:05:47.1371180Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/one_hot_categorical.py::OneHotCategorical:0
2025-07-17T07:05:47.1371960Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/wishart.py::Wishart:0, line 39 <- wrt source file
2025-07-17T07:05:47.1372670Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/wishart.py::Wishart:0
2025-07-17T07:05:47.1373370Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/gamma.py::Gamma:0, line 24 <- wrt source file
2025-07-17T07:05:47.1374060Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/gamma.py::Gamma:0
2025-07-17T07:05:47.1374740Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/chi2.py::Chi2:0, line 18 <- wrt source file
2025-07-17T07:05:47.1375420Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/chi2.py::Chi2:0
2025-07-17T07:05:47.1376120Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/binomial.py::Binomial:0, line 31 <- wrt source file
2025-07-17T07:05:47.1376850Z * SUCCESS: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/binomial.py::Binomial:0
2025-07-17T07:05:47.1377560Z * DOCTEST : /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/package/glob_group.py::GlobGroup:0, line 22 <- wrt source file
2025-07-17T07:05:47.1378260Z * SKIPPED: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/package/glob_group.py::GlobGroup:0
2025-07-17T07:05:47.1378810Z ============
2025-07-17T07:05:47.1378960Z Finished doctests
2025-07-17T07:05:47.1379090Z 342 / 719 passed
2025-07-17T07:05:47.1379230Z 
2025-07-17T07:05:47.1379400Z === Found 136 parse-time warnings ===
2025-07-17T07:05:47.1379640Z --- Parse Warning: 1 / 136 ---
2025-07-17T07:05:47.1380470Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Library.fallback in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py line=374.
2025-07-17T07:05:47.1381330Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:47.1381750Z     Registers the function implementation as the fallback for the given key.
2025-07-17T07:05:47.1382020Z     
2025-07-17T07:05:47.1382230Z             This function only works for a library with global namespace ("_").
2025-07-17T07:05:47.1382520Z     
2025-07-17T07:05:47.1382630Z             Args:
2025-07-17T07:05:47.1382880Z                 fn: function used as fallback for the given dispatch key or :func:`~fallthrough_kernel`
2025-07-17T07:05:47.1383180Z                     to register a fallthrough.
2025-07-17T07:05:47.1383530Z                 dispatch_key: dispatch key that the input function should be registered for. By default, it uses
2025-07-17T07:05:47.1383910Z                               the dispatch key that the library was created with.
2025-07-17T07:05:47.1384300Z                 with_keyset: flag controlling if the current dispatcher call keyset should be passed as the first argument
2025-07-17T07:05:47.1384770Z                              to :attr:`fn` when calling. This should be used to create the appropriate keyset for redispatch calls.
2025-07-17T07:05:47.1385070Z     
2025-07-17T07:05:47.1385180Z             Example::
2025-07-17T07:05:47.1385310Z     
2025-07-17T07:05:47.1385440Z                 >>> my_lib = Library("_", "IMPL")
2025-07-17T07:05:47.1385650Z                 >>> def fallback_kernel(op, *args, **kwargs):
2025-07-17T07:05:47.1385880Z                 >>>     # Handle all autocast ops generically
2025-07-17T07:05:47.1386080Z                 >>>     # ...
2025-07-17T07:05:47.1386270Z                 >>> my_lib.fallback(fallback_kernel, "Autocast")
2025-07-17T07:05:47.1386470Z             
2025-07-17T07:05:47.1386900Z     Original Error: IndentationError('expected an indented block after function definition on line 2', ('<source_block>', 5, 1, 'my_lib.fallback(fallback_kernel, "Autocast")\n', 5, 7))
2025-07-17T07:05:47.1387370Z     
2025-07-17T07:05:47.1387500Z     my_lib.fallback(fallback_kernel, "Autocast")
2025-07-17T07:05:47.1387690Z     ^
2025-07-17T07:05:47.1387810Z       warnings.warn(msg)
2025-07-17T07:05:47.1387950Z     
2025-07-17T07:05:47.1388110Z --- Parse Warning: 2 / 136 ---
2025-07-17T07:05:47.1388870Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_fake in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py line=933.
2025-07-17T07:05:47.1389690Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:47.1390050Z     Register a FakeTensor implementation ("fake impl") for this operator.
2025-07-17T07:05:47.1390290Z     
2025-07-17T07:05:47.1390460Z         Also sometimes known as a "meta kernel", "abstract impl".
2025-07-17T07:05:47.1390670Z     
2025-07-17T07:05:47.1390870Z         An "FakeTensor implementation" specifies the behavior of this operator on
2025-07-17T07:05:47.1391220Z         Tensors that carry no data ("FakeTensor"). Given some input Tensors with
2025-07-17T07:05:47.1391560Z         certain properties (sizes/strides/storage_offset/device), it specifies
2025-07-17T07:05:47.1391850Z         what the properties of the output Tensors are.
2025-07-17T07:05:47.1392040Z     
2025-07-17T07:05:47.1392240Z         The FakeTensor implementation has the same signature as the operator.
2025-07-17T07:05:47.1392570Z         It is run for both FakeTensors and meta tensors. To write a FakeTensor
2025-07-17T07:05:47.1392900Z         implementation, assume that all Tensor inputs to the operator are
2025-07-17T07:05:47.1393220Z         regular CPU/CUDA/Meta tensors, but they do not have storage, and
2025-07-17T07:05:47.1393570Z         you are trying to return regular CPU/CUDA/Meta tensor(s) as output.
2025-07-17T07:05:47.1393940Z         The FakeTensor implementation must consist of only PyTorch operations
2025-07-17T07:05:47.1394260Z         (and may not directly access the storage or data of any input or
2025-07-17T07:05:47.1394530Z         intermediate Tensors).
2025-07-17T07:05:47.1394680Z     
2025-07-17T07:05:47.1394860Z         This API may be used as a decorator (see examples).
2025-07-17T07:05:47.1395090Z     
2025-07-17T07:05:47.1395260Z         For a detailed guide on custom ops, please see
2025-07-17T07:05:47.1395590Z         https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html
2025-07-17T07:05:47.1395860Z     
2025-07-17T07:05:47.1395990Z         Args:
2025-07-17T07:05:47.1396230Z             op_name: Operator name (along with the overload) or OpOverload object.
2025-07-17T07:05:47.1396530Z             func: Fake tensor implementation.
2025-07-17T07:05:47.1396840Z             lib (Optional[Library]): Library to register the fake tensor to.
2025-07-17T07:05:47.1397200Z             allow_override: Flag controlling if we want to override an
2025-07-17T07:05:47.1397490Z                             existing registered fake impl. This is by default off,
2025-07-17T07:05:47.1397780Z                             and will error you're trying to register a fake impl to
2025-07-17T07:05:47.1398070Z                             an operator that already has a fake impl. This also only
2025-07-17T07:05:47.1398350Z                             applies if the custom operator was not created via
2025-07-17T07:05:47.1398660Z                             torch.library.custom_op, as overriding and existing fake
2025-07-17T07:05:47.1398920Z                             impl is already allowed.
2025-07-17T07:05:47.1399100Z     
2025-07-17T07:05:47.1399210Z         Examples:
2025-07-17T07:05:47.1399370Z             >>> import torch
2025-07-17T07:05:47.1399530Z             >>> import numpy as np
2025-07-17T07:05:47.1399710Z             >>> from torch import Tensor
2025-07-17T07:05:47.1399880Z             >>>
2025-07-17T07:05:47.1400070Z             >>> # Example 1: an operator without data-dependent output shape
2025-07-17T07:05:47.1400390Z             >>> @torch.library.custom_op("mylib::custom_linear", mutates_args=())
2025-07-17T07:05:47.1400720Z             >>> def custom_linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor:
2025-07-17T07:05:47.1401030Z             >>>     raise NotImplementedError("Implementation goes here")
2025-07-17T07:05:47.1401270Z             >>>
2025-07-17T07:05:47.1401450Z             >>> @torch.library.register_fake("mylib::custom_linear")
2025-07-17T07:05:47.1401680Z             >>> def _(x, weight, bias):
2025-07-17T07:05:47.1401860Z             >>>     assert x.dim() == 2
2025-07-17T07:05:47.1402050Z             >>>     assert weight.dim() == 2
2025-07-17T07:05:47.1402250Z             >>>     assert bias.dim() == 1
2025-07-17T07:05:47.1402450Z             >>>     assert x.shape[1] == weight.shape[1]
2025-07-17T07:05:47.1402680Z             >>>     assert weight.shape[0] == bias.shape[0]
2025-07-17T07:05:47.1402940Z             >>>     assert x.device == weight.device
2025-07-17T07:05:47.1403120Z             >>>
2025-07-17T07:05:47.1403270Z             >>>     return (x @ weight.t()) + bias
2025-07-17T07:05:47.1403470Z             >>>
2025-07-17T07:05:47.1403650Z             >>> with torch._subclasses.fake_tensor.FakeTensorMode():
2025-07-17T07:05:47.1403880Z             >>>     x = torch.randn(2, 3)
2025-07-17T07:05:47.1404060Z             >>>     w = torch.randn(3, 3)
2025-07-17T07:05:47.1404240Z             >>>     b = torch.randn(3)
2025-07-17T07:05:47.1404480Z             >>>     y = torch.ops.mylib.custom_linear(x, w, b)
2025-07-17T07:05:47.1404670Z             >>>
2025-07-17T07:05:47.1404800Z             >>> assert y.shape == (2, 3)
2025-07-17T07:05:47.1404970Z             >>>
2025-07-17T07:05:47.1405150Z             >>> # Example 2: an operator with data-dependent output shape
2025-07-17T07:05:47.1405480Z             >>> @torch.library.custom_op("mylib::custom_nonzero", mutates_args=())
2025-07-17T07:05:47.1405760Z             >>> def custom_nonzero(x: Tensor) -> Tensor:
2025-07-17T07:05:47.1405970Z             >>>     x_np = x.numpy(force=True)
2025-07-17T07:05:47.1406210Z             >>>     res = np.stack(np.nonzero(x_np), axis=1)
2025-07-17T07:05:47.1406450Z             >>>     return torch.tensor(res, device=x.device)
2025-07-17T07:05:47.1406640Z             >>>
2025-07-17T07:05:47.1406830Z             >>> @torch.library.register_fake("mylib::custom_nonzero")
2025-07-17T07:05:47.1407050Z             >>> def _(x):
2025-07-17T07:05:47.1407240Z             >>> # Number of nonzero-elements is data-dependent.
2025-07-17T07:05:47.1407500Z             >>> # Since we cannot peek at the data in an fake impl,
2025-07-17T07:05:47.1407760Z             >>> # we use the ctx object to construct a new symint that
2025-07-17T07:05:47.1408020Z             >>> # represents the data-dependent size.
2025-07-17T07:05:47.1408260Z             >>>     ctx = torch.library.get_ctx()
2025-07-17T07:05:47.1408460Z             >>>     nnz = ctx.new_dynamic_size()
2025-07-17T07:05:47.1408660Z             >>>     shape = [nnz, x.dim()]
2025-07-17T07:05:47.1408880Z             >>>     result = x.new_empty(shape, dtype=torch.int64)
2025-07-17T07:05:47.1409090Z             >>>     return result
2025-07-17T07:05:47.1409250Z             >>>
2025-07-17T07:05:47.1409440Z             >>> from torch.fx.experimental.proxy_tensor import make_fx
2025-07-17T07:05:47.1409660Z             >>>
2025-07-17T07:05:47.1409810Z             >>> x = torch.tensor([0, 1, 2, 3, 4, 0])
2025-07-17T07:05:47.1410090Z             >>> trace = make_fx(torch.ops.mylib.custom_nonzero, tracing_mode="symbolic")(x)
2025-07-17T07:05:47.1410370Z             >>> trace.print_readable()
2025-07-17T07:05:47.1410530Z             >>>
2025-07-17T07:05:47.1410750Z             >>> assert torch.allclose(trace(x), torch.ops.mylib.custom_nonzero(x))
2025-07-17T07:05:47.1411000Z     
2025-07-17T07:05:47.1411100Z         
2025-07-17T07:05:47.1411470Z     Original Error: IndentationError('expected an indented block after function definition on line 37', ('<source_block>', 38, 1, '_._ = None\n', 38, 2))
2025-07-17T07:05:47.1411880Z     
2025-07-17T07:05:47.1411990Z     _._ = None
2025-07-17T07:05:47.1412100Z     ^
2025-07-17T07:05:47.1412210Z       warnings.warn(msg)
2025-07-17T07:05:47.1412350Z     
2025-07-17T07:05:47.1412520Z --- Parse Warning: 3 / 136 ---
2025-07-17T07:05:47.1413310Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_autograd in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py line=1068.
2025-07-17T07:05:47.1414160Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1414480Z     Register a backward formula for this custom op.
2025-07-17T07:05:47.1414670Z     
2025-07-17T07:05:47.1414860Z         In order for an operator to work with autograd, you need to register
2025-07-17T07:05:47.1415110Z         a backward formula:
2025-07-17T07:05:47.1415340Z         1. You must tell us how to compute gradients during the backward pass
2025-07-17T07:05:47.1415600Z         by providing us a "backward" function.
2025-07-17T07:05:47.1415860Z         2. If you need any values from the forward to compute gradients, you can
2025-07-17T07:05:47.1416140Z         use `setup_context` to save values for backward.
2025-07-17T07:05:47.1416330Z     
2025-07-17T07:05:47.1416530Z         ``backward`` runs during the backward pass. It accepts ``(ctx, *grads)``:
2025-07-17T07:05:47.1416850Z         - ``grads`` is one or more gradients. The number of gradients matches
2025-07-17T07:05:47.1417110Z         the number of outputs of the operator.
2025-07-17T07:05:47.1417380Z         The ``ctx`` object is `the same ctx object <context_method_mixins>`_ used by
2025-07-17T07:05:47.1417800Z         :class:`torch.autograd.Function`. The semantics of ``backward_fn`` are the
2025-07-17T07:05:47.1418110Z         same as :meth:`torch.autograd.Function.backward`.
2025-07-17T07:05:47.1418320Z     
2025-07-17T07:05:47.1418510Z         ``setup_context(ctx, inputs, output)`` runs during the forward pass.
2025-07-17T07:05:47.1418860Z         Please save quantities needed for backward onto the ``ctx`` object via
2025-07-17T07:05:47.1419200Z         either :meth:`torch.autograd.function.FunctionCtx.save_for_backward`
2025-07-17T07:05:47.1419320Z         or assigning them as attributes of ``ctx``. If your custom op has
2025-07-17T07:05:47.1419460Z         kwarg-only arguments, we expect the signature of ``setup_context``
2025-07-17T07:05:47.1419580Z         to be ``setup_context(ctx, inputs, keyword_only_inputs, output)``.
2025-07-17T07:05:47.1419620Z     
2025-07-17T07:05:47.1419770Z         Both ``setup_context_fn`` and ``backward_fn`` must be traceable. That is,
2025-07-17T07:05:47.1419930Z         they may not directly access :meth:`torch.Tensor.data_ptr` and they must
2025-07-17T07:05:47.1420080Z         not depend on or mutate global state. If you need a non-traceable backward,
2025-07-17T07:05:47.1420210Z         you can make it a separate custom_op that you call inside ``backward_fn``.
2025-07-17T07:05:47.1420250Z     
2025-07-17T07:05:47.1420380Z         If you need different autograd behavior on different devices, then we
2025-07-17T07:05:47.1420520Z         recommend creating two different custom operators, one for each device
2025-07-17T07:05:47.1420650Z         that needs different behavior, and switching between them at runtime.
2025-07-17T07:05:47.1420700Z     
2025-07-17T07:05:47.1420740Z         Examples:
2025-07-17T07:05:47.1420800Z             >>> import torch
2025-07-17T07:05:47.1420850Z             >>> import numpy as np
2025-07-17T07:05:47.1420910Z             >>> from torch import Tensor
2025-07-17T07:05:47.1420960Z             >>>
2025-07-17T07:05:47.1421080Z             >>> @torch.library.custom_op("mylib::numpy_sin", mutates_args=())
2025-07-17T07:05:47.1421160Z             >>> def numpy_sin(x: Tensor) -> Tensor:
2025-07-17T07:05:47.1421220Z             >>>     x_np = x.cpu().numpy()
2025-07-17T07:05:47.1421280Z             >>>     y_np = np.sin(x_np)
2025-07-17T07:05:47.1421380Z             >>>     return torch.from_numpy(y_np).to(device=x.device)
2025-07-17T07:05:47.1421430Z             >>>
2025-07-17T07:05:47.1421520Z             >>> def setup_context(ctx, inputs, output) -> Tensor:
2025-07-17T07:05:47.1421580Z             >>>     x, = inputs
2025-07-17T07:05:47.1421640Z             >>>     ctx.save_for_backward(x)
2025-07-17T07:05:47.1421680Z             >>>
2025-07-17T07:05:47.1421740Z             >>> def backward(ctx, grad):
2025-07-17T07:05:47.1421800Z             >>>     x, = ctx.saved_tensors
2025-07-17T07:05:47.1421850Z             >>>     return grad * x.cos()
2025-07-17T07:05:47.1421890Z             >>>
2025-07-17T07:05:47.1422050Z             >>> torch.library.register_autograd(
2025-07-17T07:05:47.1422200Z             ...     "mylib::numpy_sin", backward, setup_context=setup_context
2025-07-17T07:05:47.1422260Z             ... )
2025-07-17T07:05:47.1422300Z             >>>
2025-07-17T07:05:47.1422390Z             >>> x = torch.randn(3, requires_grad=True)
2025-07-17T07:05:47.1422490Z             >>> y = numpy_sin(x)
2025-07-17T07:05:47.1422610Z             >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y))
2025-07-17T07:05:47.1422680Z             >>> assert torch.allclose(grad_x, x.cos())
2025-07-17T07:05:47.1422740Z             >>>
2025-07-17T07:05:47.1422820Z             >>> # Example with a keyword-only arg
2025-07-17T07:05:47.1422940Z             >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=())
2025-07-17T07:05:47.1423050Z             >>> def numpy_mul(x: Tensor, *, val: float) -> Tensor:
2025-07-17T07:05:47.1423120Z             >>>     x_np = x.cpu().numpy()
2025-07-17T07:05:47.1423190Z             >>>     y_np = x_np * val
2025-07-17T07:05:47.1423350Z             >>>     return torch.from_numpy(y_np).to(device=x.device)
2025-07-17T07:05:47.1423410Z             >>>
2025-07-17T07:05:47.1423560Z             >>> def setup_context(ctx, inputs, keyword_only_inputs, output) -> Tensor:
2025-07-17T07:05:47.1423690Z             >>>     ctx.val = keyword_only_inputs["val"]
2025-07-17T07:05:47.1423730Z             >>>
2025-07-17T07:05:47.1423810Z             >>> def backward(ctx, grad):
2025-07-17T07:05:47.1423870Z             >>>     return grad * ctx.val
2025-07-17T07:05:47.1423930Z             >>>
2025-07-17T07:05:47.1424000Z             >>> torch.library.register_autograd(
2025-07-17T07:05:47.1424120Z             ...     "mylib::numpy_mul", backward, setup_context=setup_context
2025-07-17T07:05:47.1424170Z             ... )
2025-07-17T07:05:47.1424220Z             >>>
2025-07-17T07:05:47.1424300Z             >>> x = torch.randn(3, requires_grad=True)
2025-07-17T07:05:47.1424410Z             >>> y = numpy_mul(x, val=3.14)
2025-07-17T07:05:47.1424550Z             >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y))
2025-07-17T07:05:47.1424660Z             >>> assert torch.allclose(grad_x, torch.full_like(x, 3.14))
2025-07-17T07:05:47.1424710Z     
2025-07-17T07:05:47.1424760Z         
2025-07-17T07:05:47.1424930Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1424970Z     
2025-07-17T07:05:47.1425030Z       warnings.warn(msg)
2025-07-17T07:05:47.1425080Z     
2025-07-17T07:05:47.1425210Z --- Parse Warning: 4 / 136 ---
2025-07-17T07:05:47.1425830Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=opcheck in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py line=1482.
2025-07-17T07:05:47.1425990Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1426140Z     Given an operator and some sample arguments, tests if the operator is
2025-07-17T07:05:47.1426210Z         registered correctly.
2025-07-17T07:05:47.1426250Z     
2025-07-17T07:05:47.1426390Z         That is, when you use the torch.library/TORCH_LIBRARY APIs to create a
2025-07-17T07:05:47.1426550Z         custom op, you specified metadata (e.g. mutability info) about the custom op
2025-07-17T07:05:47.1426680Z         and these APIs require that the functions you pass them satisfy certain
2025-07-17T07:05:47.1426830Z         properties (e.g. no data pointer access in the fake/meta/abstract kernel)
2025-07-17T07:05:47.1426930Z         ``opcheck`` tests these metadata and properties.
2025-07-17T07:05:47.1426990Z     
2025-07-17T07:05:47.1427050Z         Concretely, we test the following:
2025-07-17T07:05:47.1427120Z     
2025-07-17T07:05:47.1427240Z         - test_schema: If the schema matches the implementation of
2025-07-17T07:05:47.1427410Z           the operator. For example: if the schema specifies a Tensor is mutated,
2025-07-17T07:05:47.1427540Z           then we check the implementation mutates the Tensor. If the schema
2025-07-17T07:05:47.1427670Z           specifies that we return a new Tensor, then we check that the
2025-07-17T07:05:47.1427810Z           implementation returns a new Tensor (instead of an existing one or
2025-07-17T07:05:47.1427890Z           a view of an existing one).
2025-07-17T07:05:47.1428010Z         - test_autograd_registration: If the operator supports training
2025-07-17T07:05:47.1428140Z           (autograd): we check that its autograd formula is registered via
2025-07-17T07:05:47.1428280Z           torch.library.register_autograd or a manual registration to one
2025-07-17T07:05:47.1428410Z           or more DispatchKey::Autograd keys. Any other DispatchKey-based
2025-07-17T07:05:47.1428500Z           registrations may lead to undefined behavior.
2025-07-17T07:05:47.1428620Z         - test_faketensor: If the operator has a FakeTensor kernel
2025-07-17T07:05:47.1428740Z           (and if it is correct). The FakeTensor kernel is necessary (
2025-07-17T07:05:47.1428930Z           but not sufficient) for the operator to work with PyTorch compilation
2025-07-17T07:05:47.1429070Z           APIs (torch.compile/export/FX). We check that a FakeTensor kernel
2025-07-17T07:05:47.1429230Z           (also sometimes known as a meta kernel) was registered for the
2025-07-17T07:05:47.1429350Z           operator and that it is correct. This test takes the result of
2025-07-17T07:05:47.1429470Z           running the operator on real tensors and the result of running
2025-07-17T07:05:47.1429600Z           the operator on FakeTensors and checks that they have the same
2025-07-17T07:05:47.1429700Z           Tensor metadata (sizes/strides/dtype/device/etc).
2025-07-17T07:05:47.1429840Z         - test_aot_dispatch_dynamic: If the operator has correct behavior
2025-07-17T07:05:47.1429950Z           with PyTorch compilation APIs (torch.compile/export/FX).
2025-07-17T07:05:47.1430150Z           This checks that the outputs (and gradients, if applicable) are the
2025-07-17T07:05:47.1430280Z           same under eager-mode PyTorch and torch.compile.
2025-07-17T07:05:47.1430410Z           This test is a superset of ``test_faketensor`` and is an e2e test;
2025-07-17T07:05:47.1430530Z           other things it tests are that the operator supports
2025-07-17T07:05:47.1430670Z           functionalization and that the backward pass (if it exists) also
2025-07-17T07:05:47.1430750Z           supports FakeTensor and functionalization.
2025-07-17T07:05:47.1430800Z     
2025-07-17T07:05:47.1430930Z         For best results, please call ``opcheck`` multiple times with a
2025-07-17T07:05:47.1431060Z         representative set of inputs. If your operator supports
2025-07-17T07:05:47.1431200Z         autograd, please use ``opcheck`` with inputs with ``requires_grad = True``;
2025-07-17T07:05:47.1431340Z         if your operator supports multiple devices (e.g. CPU and CUDA), please
2025-07-17T07:05:47.1431450Z         use ``opcheck`` with inputs on all supported devices.
2025-07-17T07:05:47.1431500Z     
2025-07-17T07:05:47.1431550Z         Args:
2025-07-17T07:05:47.1431670Z             op: The operator. Must either be a function decorated with
2025-07-17T07:05:47.1431820Z                 :func:`torch.library.custom_op` or an OpOverload/OpOverloadPacket
2025-07-17T07:05:47.1431950Z                 found in torch.ops.* (e.g. torch.ops.aten.sin, torch.ops.mylib.foo)
2025-07-17T07:05:47.1432030Z             args: The args to the operator
2025-07-17T07:05:47.1432110Z             kwargs: The kwargs to the operator
2025-07-17T07:05:47.1432250Z             test_utils: Tests that we should run. Default: all of them.
2025-07-17T07:05:47.1432330Z                 Example: ("test_schema", "test_faketensor")
2025-07-17T07:05:47.1432460Z             raise_exception: If we should raise an exception on the first
2025-07-17T07:05:47.1432570Z                 error. If False, we will return a dict with information
2025-07-17T07:05:47.1432660Z                 on if each test passed or not.
2025-07-17T07:05:47.1432800Z             rtol (Optional[float]): Relative tolerance for floating point comparisons.
2025-07-17T07:05:47.1432900Z                 If specified ``atol`` must also be specified.
2025-07-17T07:05:47.1433030Z                 If omitted, default values based on the ``dtype`` are selected
2025-07-17T07:05:47.1433150Z                 (see the table in :func:`torch.testing.assert_close`).
2025-07-17T07:05:47.1433290Z             atol (Optional[float]): Absolute tolerance for floating point comparisons.
2025-07-17T07:05:47.1433380Z                 If specified ``rtol`` must also be specified.
2025-07-17T07:05:47.1433510Z                 If omitted, default values based on the ``dtype`` are selected
2025-07-17T07:05:47.1433610Z                 (see the table in :func:`torch.testing.assert_close`).
2025-07-17T07:05:47.1433670Z     
2025-07-17T07:05:47.1433720Z         .. warning::
2025-07-17T07:05:47.1433770Z     
2025-07-17T07:05:47.1433920Z             opcheck and :func:`torch.autograd.gradcheck` test different things;
2025-07-17T07:05:47.1434070Z             opcheck tests if your usage of torch.library APIs is correct while
2025-07-17T07:05:47.1434210Z             :func:`torch.autograd.gradcheck` tests if your autograd formula is
2025-07-17T07:05:47.1434380Z             mathematically correct. Use both to test custom ops that support
2025-07-17T07:05:47.1434430Z             gradient computation.
2025-07-17T07:05:47.1434490Z     
2025-07-17T07:05:47.1434560Z         Example:
2025-07-17T07:05:47.1434610Z     
2025-07-17T07:05:47.1434700Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-07-17T07:05:47.1434830Z             >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=())
2025-07-17T07:05:47.1434960Z             >>> def numpy_mul(x: Tensor, y: float) -> Tensor:
2025-07-17T07:05:47.1435030Z             >>>     x_np = x.numpy(force=True)
2025-07-17T07:05:47.1441640Z             >>>     z_np = x_np * y
2025-07-17T07:05:47.1442020Z             >>>     return torch.from_numpy(z_np).to(x.device)
2025-07-17T07:05:47.1442130Z             >>>
2025-07-17T07:05:47.1442190Z             >>> @numpy_mul.register_fake
2025-07-17T07:05:47.1442250Z             >>> def _(x, y):
2025-07-17T07:05:47.1442320Z             >>>     return torch.empty_like(x)
2025-07-17T07:05:47.1442360Z             >>>
2025-07-17T07:05:47.1442440Z             >>> def setup_context(ctx, inputs, output):
2025-07-17T07:05:47.1442490Z             >>>     y, = inputs
2025-07-17T07:05:47.1442540Z             >>>     ctx.y = y
2025-07-17T07:05:47.1442590Z             >>>
2025-07-17T07:05:47.1442650Z             >>> def backward(ctx, grad):
2025-07-17T07:05:47.1442710Z             >>>     return grad * ctx.y, None
2025-07-17T07:05:47.1442750Z             >>>
2025-07-17T07:05:47.1442890Z             >>> numpy_mul.register_autograd(backward, setup_context=setup_context)
2025-07-17T07:05:47.1442930Z             >>>
2025-07-17T07:05:47.1442990Z             >>> sample_inputs = [
2025-07-17T07:05:47.1443050Z             >>>     (torch.randn(3), 3.14),
2025-07-17T07:05:47.1443130Z             >>>     (torch.randn(2, 3, device='cuda'), 2.718),
2025-07-17T07:05:47.1443230Z             >>>     (torch.randn(1, 10, requires_grad=True), 1.234),
2025-07-17T07:05:47.1443350Z             >>>     (torch.randn(64, 64, device='cuda', requires_grad=True), 90.18),
2025-07-17T07:05:47.1443390Z             >>> ]
2025-07-17T07:05:47.1443440Z             >>>
2025-07-17T07:05:47.1443500Z             >>> for args in sample_inputs:
2025-07-17T07:05:47.1443580Z             >>>     torch.library.opcheck(numpy_mul, args)
2025-07-17T07:05:47.1443620Z     
2025-07-17T07:05:47.1443670Z         
2025-07-17T07:05:47.1443820Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1443860Z     
2025-07-17T07:05:47.1443910Z       warnings.warn(msg)
2025-07-17T07:05:47.1443950Z     
2025-07-17T07:05:47.1444120Z --- Parse Warning: 5 / 136 ---
2025-07-17T07:05:47.1444770Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Tensor.dim_order in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py line=1493.
2025-07-17T07:05:47.1444930Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1444970Z     
2025-07-17T07:05:47.1445040Z     dim_order(ambiguity_check=False) -> tuple
2025-07-17T07:05:47.1445080Z     
2025-07-17T07:05:47.1445220Z     Returns the uniquely determined tuple of int describing the dim order or
2025-07-17T07:05:47.1445290Z     physical layout of :attr:`self`.
2025-07-17T07:05:47.1445330Z     
2025-07-17T07:05:47.1445480Z     The dim order represents how dimensions are laid out in memory of dense tensors,
2025-07-17T07:05:47.1445580Z     starting from the outermost to the innermost dimension.
2025-07-17T07:05:47.1445630Z     
2025-07-17T07:05:47.1445800Z     Note that the dim order may not always be uniquely determined.
2025-07-17T07:05:47.1446050Z     If `ambiguity_check` is True, this function raises a RuntimeError when the dim order cannot be uniquely determined;
2025-07-17T07:05:47.1446280Z     If `ambiguity_check` is a list of memory formats, this function raises a RuntimeError when tensor can not be interpreted
2025-07-17T07:05:47.1446470Z     into exactly one of the given memory formats, or it cannot be uniquely determined.
2025-07-17T07:05:47.1446660Z     If `ambiguity_check` is False, it will return one of legal dim order(s) without checking its uniqueness.
2025-07-17T07:05:47.1446720Z     Otherwise, it will raise TypeError.
2025-07-17T07:05:47.1446760Z     
2025-07-17T07:05:47.1446810Z     Args:
2025-07-17T07:05:47.1447000Z         ambiguity_check (bool or List[torch.memory_format]): The check method for ambiguity of dim order.
2025-07-17T07:05:47.1447040Z     
2025-07-17T07:05:47.1447090Z     Examples::
2025-07-17T07:05:47.1447150Z     
2025-07-17T07:05:47.1447250Z         >>> torch.empty((2, 3, 5, 7)).dim_order()
2025-07-17T07:05:47.1447290Z         (0, 1, 2, 3)
2025-07-17T07:05:47.1447390Z         >>> torch.empty((2, 3, 5, 7)).transpose(1, 2).dim_order()
2025-07-17T07:05:47.1447430Z         (0, 2, 1, 3)
2025-07-17T07:05:47.1447560Z         >>> torch.empty((2, 3, 5, 7), memory_format=torch.channels_last).dim_order()
2025-07-17T07:05:47.1447600Z         (0, 2, 3, 1)
2025-07-17T07:05:47.1447670Z         >>> torch.empty((1, 2, 3, 4)).dim_order()
2025-07-17T07:05:47.1447720Z         (0, 1, 2, 3)
2025-07-17T07:05:47.1447760Z         >>> try:
2025-07-17T07:05:47.1447860Z         ...     torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check=True)
2025-07-17T07:05:47.1447930Z         ... except RuntimeError as e:
2025-07-17T07:05:47.1447980Z         ...     print(e)
2025-07-17T07:05:47.1448160Z         The tensor does not have unique dim order, or cannot map to exact one of the given memory formats.
2025-07-17T07:05:47.1448240Z         >>> torch.empty((1, 2, 3, 4)).dim_order(
2025-07-17T07:05:47.1448370Z         ...     ambiguity_check=[torch.contiguous_format, torch.channels_last]
2025-07-17T07:05:47.1448450Z         ... )  # It can be mapped to contiguous format
2025-07-17T07:05:47.1448490Z         (0, 1, 2, 3)
2025-07-17T07:05:47.1448540Z         >>> try:
2025-07-17T07:05:47.1448650Z         ...     torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check="ILLEGAL")
2025-07-17T07:05:47.1448710Z         ... except TypeError as e:
2025-07-17T07:05:47.1448760Z         ...     print(e)
2025-07-17T07:05:47.1448900Z         The ambiguity_check argument must be a bool or a list of memory formats.
2025-07-17T07:05:47.1448940Z     
2025-07-17T07:05:47.1448980Z     .. warning::
2025-07-17T07:05:47.1449100Z         The dim_order tensor API is experimental and subject to change.
2025-07-17T07:05:47.1449150Z     
2025-07-17T07:05:47.1449290Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1449330Z     
2025-07-17T07:05:47.1449390Z       warnings.warn(msg)
2025-07-17T07:05:47.1449430Z     
2025-07-17T07:05:47.1449530Z --- Parse Warning: 6 / 136 ---
2025-07-17T07:05:47.1450150Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/hub.py line=560.
2025-07-17T07:05:47.1450310Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1450360Z     
2025-07-17T07:05:47.1450450Z     Load a model from a github repo or a local directory.
2025-07-17T07:05:47.1450490Z     
2025-07-17T07:05:47.1450630Z     Note: Loading a model is the typical use case, but this can also be used to
2025-07-17T07:05:47.1450760Z     for loading other objects such as tokenizers, loss functions, etc.
2025-07-17T07:05:47.1450800Z     
2025-07-17T07:05:47.1450900Z     If ``source`` is 'github', ``repo_or_dir`` is expected to be
2025-07-17T07:05:47.1451040Z     of the form ``repo_owner/repo_name[:ref]`` with an optional
2025-07-17T07:05:47.1451100Z     ref (a tag or a branch).
2025-07-17T07:05:47.1451140Z     
2025-07-17T07:05:47.1451250Z     If ``source`` is 'local', ``repo_or_dir`` is expected to be a
2025-07-17T07:05:47.1451340Z     path to a local directory.
2025-07-17T07:05:47.1451380Z     
2025-07-17T07:05:47.1451430Z     Args:
2025-07-17T07:05:47.1451520Z         repo_or_dir (str): If ``source`` is 'github',
2025-07-17T07:05:47.1451690Z             this should correspond to a github repo with format ``repo_owner/repo_name[:ref]`` with
2025-07-17T07:05:47.1451880Z             an optional ref (tag or branch), for example 'pytorch/vision:0.10'. If ``ref`` is not specified,
2025-07-17T07:05:47.1452040Z             the default branch is assumed to be ``main`` if it exists, and otherwise ``master``.
2025-07-17T07:05:47.1452190Z             If ``source`` is 'local'  then it should be a path to a local directory.
2025-07-17T07:05:47.1452330Z         model (str): the name of a callable (entrypoint) defined in the
2025-07-17T07:05:47.1452400Z             repo/dir's ``hubconf.py``.
2025-07-17T07:05:47.1452530Z         *args (optional): the corresponding args for callable ``model``.
2025-07-17T07:05:47.1452660Z         source (str, optional): 'github' or 'local'. Specifies how
2025-07-17T07:05:47.1452760Z             ``repo_or_dir`` is to be interpreted. Default is 'github'.
2025-07-17T07:05:47.1452900Z         trust_repo (bool, str or None): ``"check"``, ``True``, ``False`` or ``None``.
2025-07-17T07:05:47.1453050Z             This parameter was introduced in v1.12 and helps ensuring that users
2025-07-17T07:05:47.1453130Z             only run code from repos that they trust.
2025-07-17T07:05:47.1453180Z     
2025-07-17T07:05:47.1453300Z             - If ``False``, a prompt will ask the user whether the repo should
2025-07-17T07:05:47.1453360Z               be trusted.
2025-07-17T07:05:47.1453480Z             - If ``True``, the repo will be added to the trusted list and loaded
2025-07-17T07:05:47.1453570Z               without requiring explicit confirmation.
2025-07-17T07:05:47.1453680Z             - If ``"check"``, the repo will be checked against the list of
2025-07-17T07:05:47.1453820Z               trusted repos in the cache. If it is not present in that list, the
2025-07-17T07:05:47.1453940Z               behaviour will fall back onto the ``trust_repo=False`` option.
2025-07-17T07:05:47.1454060Z             - If ``None``: this will raise a warning, inviting the user to set
2025-07-17T07:05:47.1454180Z               ``trust_repo`` to either ``False``, ``True`` or ``"check"``. This
2025-07-17T07:05:47.1454320Z               is only present for backward compatibility and will be removed in
2025-07-17T07:05:47.1454360Z               v2.0.
2025-07-17T07:05:47.1454410Z     
2025-07-17T07:05:47.1454530Z             Default is ``None`` and will eventually change to ``"check"`` in v2.0.
2025-07-17T07:05:47.1454680Z         force_reload (bool, optional): whether to force a fresh download of
2025-07-17T07:05:47.1454810Z             the github repo unconditionally. Does not have any effect if
2025-07-17T07:05:47.1454900Z             ``source = 'local'``. Default is ``False``.
2025-07-17T07:05:47.1455040Z         verbose (bool, optional): If ``False``, mute messages about hitting
2025-07-17T07:05:47.1455180Z             local caches. Note that the message about first download cannot be
2025-07-17T07:05:47.1455290Z             muted. Does not have any effect if ``source = 'local'``.
2025-07-17T07:05:47.1455350Z             Default is ``True``.
2025-07-17T07:05:47.1455550Z         skip_validation (bool, optional): if ``False``, torchhub will check that the branch or commit
2025-07-17T07:05:47.1455740Z             specified by the ``github`` argument properly belongs to the repo owner. This will make
2025-07-17T07:05:47.1455920Z             requests to the GitHub API; you can specify a non-default GitHub token by setting the
2025-07-17T07:05:47.1456070Z             ``GITHUB_TOKEN`` environment variable. Default is ``False``.
2025-07-17T07:05:47.1456220Z         **kwargs (optional): the corresponding kwargs for callable ``model``.
2025-07-17T07:05:47.1456260Z     
2025-07-17T07:05:47.1456310Z     Returns:
2025-07-17T07:05:47.1456460Z         The output of the ``model`` callable when called with the given
2025-07-17T07:05:47.1456530Z         ``*args`` and ``**kwargs``.
2025-07-17T07:05:47.1456580Z     
2025-07-17T07:05:47.1456630Z     Example:
2025-07-17T07:05:47.1456720Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB)
2025-07-17T07:05:47.1456780Z         >>> # from a github repo
2025-07-17T07:05:47.1456840Z         >>> repo = "pytorch/vision"
2025-07-17T07:05:47.1456900Z         >>> model = torch.hub.load(
2025-07-17T07:05:47.1457020Z         ...     repo, "resnet50", weights="ResNet50_Weights.IMAGENET1K_V1"
2025-07-17T07:05:47.1457060Z         ... )
2025-07-17T07:05:47.1457150Z         >>> # from a local directory
2025-07-17T07:05:47.1457260Z         >>> path = "/some/local/path/pytorch/vision"
2025-07-17T07:05:47.1457320Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1457460Z         >>> model = torch.hub.load(path, "resnet50", weights="ResNet50_Weights.DEFAULT")
2025-07-17T07:05:47.1457510Z     
2025-07-17T07:05:47.1457660Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1457710Z     
2025-07-17T07:05:47.1457760Z       warnings.warn(msg)
2025-07-17T07:05:47.1457810Z     
2025-07-17T07:05:47.1457910Z --- Parse Warning: 7 / 136 ---
2025-07-17T07:05:47.1458570Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_load_local in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/hub.py line=652.
2025-07-17T07:05:47.1458730Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1458780Z     
2025-07-17T07:05:47.1458890Z     Load a model from a local directory with a ``hubconf.py``.
2025-07-17T07:05:47.1458940Z     
2025-07-17T07:05:47.1458980Z     Args:
2025-07-17T07:05:47.1459100Z         hubconf_dir (str): path to a local directory that contains a
2025-07-17T07:05:47.1459160Z             ``hubconf.py``.
2025-07-17T07:05:47.1459280Z         model (str): name of an entrypoint defined in the directory's
2025-07-17T07:05:47.1459340Z             ``hubconf.py``.
2025-07-17T07:05:47.1459470Z         *args (optional): the corresponding args for callable ``model``.
2025-07-17T07:05:47.1459610Z         **kwargs (optional): the corresponding kwargs for callable ``model``.
2025-07-17T07:05:47.1459650Z     
2025-07-17T07:05:47.1459700Z     Returns:
2025-07-17T07:05:47.1459810Z         a single model with corresponding pretrained weights.
2025-07-17T07:05:47.1459860Z     
2025-07-17T07:05:47.1459900Z     Example:
2025-07-17T07:05:47.1459980Z         >>> # xdoctest: +SKIP("stub local path")
2025-07-17T07:05:47.1460060Z         >>> path = "/some/local/path/pytorch/vision"
2025-07-17T07:05:47.1460130Z         >>> model = _load_local(
2025-07-17T07:05:47.1460180Z         ...     path,
2025-07-17T07:05:47.1460230Z         ...     "resnet50",
2025-07-17T07:05:47.1460330Z         ...     weights="ResNet50_Weights.IMAGENET1K_V1",
2025-07-17T07:05:47.1460370Z         ... )
2025-07-17T07:05:47.1460420Z     
2025-07-17T07:05:47.1460580Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1460630Z     
2025-07-17T07:05:47.1460680Z       warnings.warn(msg)
2025-07-17T07:05:47.1460730Z     
2025-07-17T07:05:47.1460840Z --- Parse Warning: 8 / 136 ---
2025-07-17T07:05:47.1461500Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=download_url_to_file in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/hub.py line=691.
2025-07-17T07:05:47.1461690Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1461780Z     Download object at the given URL to a local path.
2025-07-17T07:05:47.1461820Z     
2025-07-17T07:05:47.1461870Z         Args:
2025-07-17T07:05:47.1461980Z             url (str): URL of the object to download
2025-07-17T07:05:47.1462120Z             dst (str): Full path where object will be saved, e.g. ``/tmp/temporary_file``
2025-07-17T07:05:47.1462330Z             hash_prefix (str, optional): If not None, the SHA256 downloaded file should start with ``hash_prefix``.
2025-07-17T07:05:47.1462380Z                 Default: None
2025-07-17T07:05:47.1462540Z             progress (bool, optional): whether or not to display a progress bar to stderr
2025-07-17T07:05:47.1462590Z                 Default: True
2025-07-17T07:05:47.1462630Z     
2025-07-17T07:05:47.1462670Z         Example:
2025-07-17T07:05:47.1462780Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB)
2025-07-17T07:05:47.1462880Z             >>> # xdoctest: +REQUIRES(POSIX)
2025-07-17T07:05:47.1462950Z             >>> torch.hub.download_url_to_file(
2025-07-17T07:05:47.1463100Z             ...     "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth",
2025-07-17T07:05:47.1463160Z             ...     "/tmp/temporary_file",
2025-07-17T07:05:47.1463200Z             ... )
2025-07-17T07:05:47.1463240Z     
2025-07-17T07:05:47.1463290Z         
2025-07-17T07:05:47.1463430Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1463480Z     
2025-07-17T07:05:47.1463530Z       warnings.warn(msg)
2025-07-17T07:05:47.1463570Z     
2025-07-17T07:05:47.1463670Z --- Parse Warning: 9 / 136 ---
2025-07-17T07:05:47.1464310Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_state_dict_from_url in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/hub.py line=816.
2025-07-17T07:05:47.1464470Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1464570Z     Loads the Torch serialized object at the given URL.
2025-07-17T07:05:47.1464610Z     
2025-07-17T07:05:47.1464720Z         If downloaded file is a zip file, it will be automatically
2025-07-17T07:05:47.1464770Z         decompressed.
2025-07-17T07:05:47.1464810Z     
2025-07-17T07:05:47.1464940Z         If the object is already present in `model_dir`, it's deserialized and
2025-07-17T07:05:47.1464990Z         returned.
2025-07-17T07:05:47.1465110Z         The default value of ``model_dir`` is ``<hub_dir>/checkpoints`` where
2025-07-17T07:05:47.1465230Z         ``hub_dir`` is the directory returned by :func:`~torch.hub.get_dir`.
2025-07-17T07:05:47.1465270Z     
2025-07-17T07:05:47.1465310Z         Args:
2025-07-17T07:05:47.1465390Z             url (str): URL of the object to download
2025-07-17T07:05:47.1465510Z             model_dir (str, optional): directory in which to save the object
2025-07-17T07:05:47.1465730Z             map_location (optional): a function or a dict specifying how to remap storage locations (see torch.load)
2025-07-17T07:05:47.1465880Z             progress (bool, optional): whether or not to display a progress bar to stderr.
2025-07-17T07:05:47.1465930Z                 Default: True
2025-07-17T07:05:47.1466130Z             check_hash(bool, optional): If True, the filename part of the URL should follow the naming convention
2025-07-17T07:05:47.1466270Z                 ``filename-<sha256>.ext`` where ``<sha256>`` is the first eight or more
2025-07-17T07:05:47.1466410Z                 digits of the SHA256 hash of the contents of the file. The hash is used to
2025-07-17T07:05:47.1466530Z                 ensure unique names and to verify the contents of the file.
2025-07-17T07:05:47.1466580Z                 Default: False
2025-07-17T07:05:47.1466850Z             file_name (str, optional): name for the downloaded file. Filename from ``url`` will be used if not set.
2025-07-17T07:05:47.1467040Z             weights_only(bool, optional): If True, only weights will be loaded and no complex pickled objects.
2025-07-17T07:05:47.1467200Z                 Recommended for untrusted sources. See :func:`~torch.load` for more details.
2025-07-17T07:05:47.1467260Z     
2025-07-17T07:05:47.1467310Z         Example:
2025-07-17T07:05:47.1467400Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB)
2025-07-17T07:05:47.1467490Z             >>> state_dict = torch.hub.load_state_dict_from_url(
2025-07-17T07:05:47.1467620Z             ...     "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth"
2025-07-17T07:05:47.1467670Z             ... )
2025-07-17T07:05:47.1467710Z     
2025-07-17T07:05:47.1467750Z         
2025-07-17T07:05:47.1467900Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1467940Z     
2025-07-17T07:05:47.1468010Z       warnings.warn(msg)
2025-07-17T07:05:47.1468080Z     
2025-07-17T07:05:47.1468190Z --- Parse Warning: 10 / 136 ---
2025-07-17T07:05:47.1468810Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=meshgrid in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py line=446.
2025-07-17T07:05:47.1468970Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1469120Z     Creates grids of coordinates specified by the 1D inputs in `attr`:tensors.
2025-07-17T07:05:47.1469160Z     
2025-07-17T07:05:47.1469270Z             This is helpful when you want to visualize data over some
2025-07-17T07:05:47.1469370Z             range of inputs. See below for a plotting example.
2025-07-17T07:05:47.1469410Z     
2025-07-17T07:05:47.1469510Z             Given :math:`N` 1D tensors :math:`T_0 \ldots T_{N-1}` as
2025-07-17T07:05:47.1469630Z             inputs with corresponding sizes :math:`S_0 \ldots S_{N-1}`,
2025-07-17T07:05:47.1469750Z             this creates :math:`N` N-dimensional tensors :math:`G_0 \ldots
2025-07-17T07:05:47.1469850Z             G_{N-1}`, each with shape :math:`(S_0, ..., S_{N-1})` where
2025-07-17T07:05:47.1469970Z             the output :math:`G_i` is constructed by expanding :math:`T_i`
2025-07-17T07:05:47.1470030Z             to the result shape.
2025-07-17T07:05:47.1470070Z     
2025-07-17T07:05:47.1470120Z             .. note::
2025-07-17T07:05:47.1470210Z                 0D inputs are treated equivalently to 1D inputs of a
2025-07-17T07:05:47.1470270Z                 single element.
2025-07-17T07:05:47.1470310Z     
2025-07-17T07:05:47.1470360Z             .. warning::
2025-07-17T07:05:47.1470480Z                 `torch.meshgrid(*tensors)` currently has the same behavior
2025-07-17T07:05:47.1470580Z                 as calling `numpy.meshgrid(*arrays, indexing='ij')`.
2025-07-17T07:05:47.1470620Z     
2025-07-17T07:05:47.1470720Z                 In the future `torch.meshgrid` will transition to
2025-07-17T07:05:47.1470790Z                 `indexing='xy'` as the default.
2025-07-17T07:05:47.1470830Z     
2025-07-17T07:05:47.1470940Z                 https://github.com/pytorch/pytorch/issues/50276 tracks
2025-07-17T07:05:47.1471060Z                 this issue with the goal of migrating to NumPy's behavior.
2025-07-17T07:05:47.1471100Z     
2025-07-17T07:05:47.1471150Z             .. seealso::
2025-07-17T07:05:47.1471200Z     
2025-07-17T07:05:47.1471300Z                 :func:`torch.cartesian_prod` has the same effect but it
2025-07-17T07:05:47.1471390Z                 collects the data in a tensor of vectors.
2025-07-17T07:05:47.1471430Z     
2025-07-17T07:05:47.1471470Z             Args:
2025-07-17T07:05:47.1471630Z                 tensors (list of Tensor): list of scalars or 1 dimensional tensors. Scalars will be
2025-07-17T07:05:47.1471740Z                     treated as tensors of size :math:`(1,)` automatically
2025-07-17T07:05:47.1471780Z     
2025-07-17T07:05:47.1471920Z                 indexing: (str, optional): the indexing mode, either "xy"
2025-07-17T07:05:47.1472030Z                     or "ij", defaults to "ij". See warning for future changes.
2025-07-17T07:05:47.1472100Z     
2025-07-17T07:05:47.1472200Z                     If "xy" is selected, the first dimension corresponds
2025-07-17T07:05:47.1472300Z                     to the cardinality of the second input and the second
2025-07-17T07:05:47.1472410Z                     dimension corresponds to the cardinality of the first
2025-07-17T07:05:47.1472460Z                     input.
2025-07-17T07:05:47.1472510Z     
2025-07-17T07:05:47.1472600Z                     If "ij" is selected, the dimensions are in the same
2025-07-17T07:05:47.1472680Z                     order as the cardinality of the inputs.
2025-07-17T07:05:47.1472720Z     
2025-07-17T07:05:47.1472770Z             Returns:
2025-07-17T07:05:47.1472890Z                 seq (sequence of Tensors): If the input has :math:`N`
2025-07-17T07:05:47.1473010Z                 tensors of size :math:`S_0 \ldots S_{N-1}``, then the
2025-07-17T07:05:47.1473130Z                 output will also have :math:`N` tensors, where each tensor
2025-07-17T07:05:47.1473210Z                 is of shape :math:`(S_0, ..., S_{N-1})`.
2025-07-17T07:05:47.1473250Z     
2025-07-17T07:05:47.1473300Z             Example::
2025-07-17T07:05:47.1473340Z     
2025-07-17T07:05:47.1473410Z                 >>> x = torch.tensor([1, 2, 3])
2025-07-17T07:05:47.1473480Z                 >>> y = torch.tensor([4, 5, 6])
2025-07-17T07:05:47.1473520Z     
2025-07-17T07:05:47.1473630Z                 Observe the element-wise pairings across the grid, (1, 4),
2025-07-17T07:05:47.1473710Z                 (1, 5), ..., (3, 6). This is the same thing as the
2025-07-17T07:05:47.1473770Z                 cartesian product.
2025-07-17T07:05:47.1473870Z                 >>> grid_x, grid_y = torch.meshgrid(x, y, indexing='ij')
2025-07-17T07:05:47.1473930Z                 >>> grid_x
2025-07-17T07:05:47.1473980Z                 tensor([[1, 1, 1],
2025-07-17T07:05:47.1474030Z                         [2, 2, 2],
2025-07-17T07:05:47.1474080Z                         [3, 3, 3]])
2025-07-17T07:05:47.1474130Z                 >>> grid_y
2025-07-17T07:05:47.1474190Z                 tensor([[4, 5, 6],
2025-07-17T07:05:47.1474230Z                         [4, 5, 6],
2025-07-17T07:05:47.1474290Z                         [4, 5, 6]])
2025-07-17T07:05:47.1474330Z     
2025-07-17T07:05:47.1474430Z                 This correspondence can be seen when these grids are
2025-07-17T07:05:47.1474490Z                 stacked properly.
2025-07-17T07:05:47.1474610Z                 >>> torch.equal(torch.cat(tuple(torch.dstack([grid_x, grid_y]))),
2025-07-17T07:05:47.1474690Z                 ...             torch.cartesian_prod(x, y))
2025-07-17T07:05:47.1474740Z                 True
2025-07-17T07:05:47.1474780Z     
2025-07-17T07:05:47.1474890Z                 `torch.meshgrid` is commonly used to produce a grid for
2025-07-17T07:05:47.1474940Z                 plotting.
2025-07-17T07:05:47.1475020Z                 >>> # xdoctest: +REQUIRES(module:matplotlib)
2025-07-17T07:05:47.1475100Z                 >>> # xdoctest: +REQUIRES(env:DOCTEST_SHOW)
2025-07-17T07:05:47.1475180Z                 >>> import matplotlib.pyplot as plt
2025-07-17T07:05:47.1475260Z                 >>> xs = torch.linspace(-5, 5, steps=100)
2025-07-17T07:05:47.1475330Z                 >>> ys = torch.linspace(-5, 5, steps=100)
2025-07-17T07:05:47.1475410Z                 >>> x, y = torch.meshgrid(xs, ys, indexing='xy')
2025-07-17T07:05:47.1475490Z                 >>> z = torch.sin(torch.sqrt(x * x + y * y))
2025-07-17T07:05:47.1475570Z                 >>> ax = plt.axes(projection='3d')
2025-07-17T07:05:47.1475670Z                 >>> ax.plot_surface(x.numpy(), y.numpy(), z.numpy())
2025-07-17T07:05:47.1475730Z                 >>> plt.show()
2025-07-17T07:05:47.1475770Z     
2025-07-17T07:05:47.1475850Z             .. image:: ../_static/img/meshgrid.png
2025-07-17T07:05:47.1475930Z                 :width: 512
2025-07-17T07:05:47.1475980Z     
2025-07-17T07:05:47.1476020Z             
2025-07-17T07:05:47.1476180Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1476250Z     
2025-07-17T07:05:47.1476300Z       warnings.warn(msg)
2025-07-17T07:05:47.1476350Z     
2025-07-17T07:05:47.1476450Z --- Parse Warning: 11 / 136 ---
2025-07-17T07:05:47.1477100Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_unique_impl in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/functional.py line=842.
2025-07-17T07:05:47.1477260Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1477530Z     unique(input, sorted=True, return_inverse=False, return_counts=False, dim=None) -> tuple[Tensor, Tensor, Tensor]
2025-07-17T07:05:47.1477600Z     
2025-07-17T07:05:47.1477690Z         Returns the unique elements of the input tensor.
2025-07-17T07:05:47.1477740Z     
2025-07-17T07:05:47.1477920Z         .. note:: This function is different from :func:`torch.unique_consecutive` in the sense that
2025-07-17T07:05:47.1478050Z             this function also eliminates non-consecutive duplicate values.
2025-07-17T07:05:47.1478100Z     
2025-07-17T07:05:47.1478250Z         .. note:: Currently in the CUDA implementation and the CPU implementation,
2025-07-17T07:05:47.1478430Z             `torch.unique` always sort the tensor at the beginning regardless of the `sort` argument.
2025-07-17T07:05:47.1478600Z             Sorting could be slow, so if your input tensor is already sorted, it is recommended to use
2025-07-17T07:05:47.1478710Z             :func:`torch.unique_consecutive` which avoids the sorting.
2025-07-17T07:05:47.1478750Z     
2025-07-17T07:05:47.1478800Z         Args:
2025-07-17T07:05:47.1478870Z             input (Tensor): the input tensor
2025-07-17T07:05:47.1479000Z             sorted (bool): Whether to sort the unique elements in ascending order
2025-07-17T07:05:47.1479070Z                 before returning as output.
2025-07-17T07:05:47.1479200Z             return_inverse (bool): Whether to also return the indices for where
2025-07-17T07:05:47.1479340Z                 elements in the original input ended up in the returned unique list.
2025-07-17T07:05:47.1479470Z             return_counts (bool): Whether to also return the counts for each unique
2025-07-17T07:05:47.1479520Z                 element.
2025-07-17T07:05:47.1479640Z             dim (int, optional): the dimension to operate upon. If ``None``, the
2025-07-17T07:05:47.1479770Z                 unique of the flattened input is returned. Otherwise, each of the
2025-07-17T07:05:47.1479900Z                 tensors indexed by the given dimension is treated as one of the
2025-07-17T07:05:47.1480030Z                 elements to apply the unique operation upon. See examples for more
2025-07-17T07:05:47.1480100Z                 details. Default: ``None``
2025-07-17T07:05:47.1480140Z     
2025-07-17T07:05:47.1480180Z         Returns:
2025-07-17T07:05:47.1480360Z             (Tensor, Tensor (optional), Tensor (optional)): A tensor or a tuple of tensors containing
2025-07-17T07:05:47.1480400Z     
2025-07-17T07:05:47.1480530Z                 - **output** (*Tensor*): the output list of unique scalar elements.
2025-07-17T07:05:47.1480610Z                 - **inverse_indices** (*Tensor*): (optional) if
2025-07-17T07:05:47.1480730Z                   :attr:`return_inverse` is True, there will be an additional
2025-07-17T07:05:47.1480850Z                   returned tensor (same shape as input) representing the indices
2025-07-17T07:05:47.1480980Z                   for where elements in the original input map to in the output;
2025-07-17T07:05:47.1481100Z                   otherwise, this function will only return a single tensor.
2025-07-17T07:05:47.1481180Z                 - **counts** (*Tensor*): (optional) if
2025-07-17T07:05:47.1481320Z                   :attr:`return_counts` is True, there will be an additional
2025-07-17T07:05:47.1481440Z                   returned tensor (same shape as output or output.size(dim),
2025-07-17T07:05:47.1481590Z                   if dim was specified) representing the number of occurrences
2025-07-17T07:05:47.1481660Z                   for each unique value or tensor.
2025-07-17T07:05:47.1481710Z     
2025-07-17T07:05:47.1481760Z         Example::
2025-07-17T07:05:47.1481800Z     
2025-07-17T07:05:47.1481940Z             >>> output = torch.unique(torch.tensor([1, 3, 2, 3], dtype=torch.long))
2025-07-17T07:05:47.1482000Z             >>> output
2025-07-17T07:05:47.1482050Z             tensor([1, 2, 3])
2025-07-17T07:05:47.1482090Z     
2025-07-17T07:05:47.1482170Z             >>> output, inverse_indices = torch.unique(
2025-07-17T07:05:47.1482380Z             ...     torch.tensor([1, 3, 2, 3], dtype=torch.long), sorted=True, return_inverse=True)
2025-07-17T07:05:47.1482460Z             >>> output
2025-07-17T07:05:47.1482510Z             tensor([1, 2, 3])
2025-07-17T07:05:47.1482560Z             >>> inverse_indices
2025-07-17T07:05:47.1482620Z             tensor([0, 2, 1, 2])
2025-07-17T07:05:47.1482660Z     
2025-07-17T07:05:47.1482740Z             >>> output, inverse_indices = torch.unique(
2025-07-17T07:05:47.1482900Z             ...     torch.tensor([[1, 3], [2, 3]], dtype=torch.long), sorted=True, return_inverse=True)
2025-07-17T07:05:47.1482950Z             >>> output
2025-07-17T07:05:47.1483000Z             tensor([1, 2, 3])
2025-07-17T07:05:47.1483050Z             >>> inverse_indices
2025-07-17T07:05:47.1483100Z             tensor([[0, 2],
2025-07-17T07:05:47.1483150Z                     [1, 2]])
2025-07-17T07:05:47.1483190Z     
2025-07-17T07:05:47.1483250Z             >>> a = torch.tensor([
2025-07-17T07:05:47.1483300Z             ...     [
2025-07-17T07:05:47.1483360Z             ...         [1, 1, 0, 0],
2025-07-17T07:05:47.1483410Z             ...         [1, 1, 0, 0],
2025-07-17T07:05:47.1483470Z             ...         [0, 0, 1, 1],
2025-07-17T07:05:47.1483510Z             ...     ],
2025-07-17T07:05:47.1483560Z             ...     [
2025-07-17T07:05:47.1483610Z             ...         [0, 0, 1, 1],
2025-07-17T07:05:47.1483670Z             ...         [0, 0, 1, 1],
2025-07-17T07:05:47.1483720Z             ...         [1, 1, 1, 1],
2025-07-17T07:05:47.1483760Z             ...     ],
2025-07-17T07:05:47.1483810Z             ...     [
2025-07-17T07:05:47.1483860Z             ...         [1, 1, 0, 0],
2025-07-17T07:05:47.1483910Z             ...         [1, 1, 0, 0],
2025-07-17T07:05:47.1483960Z             ...         [0, 0, 1, 1],
2025-07-17T07:05:47.1484010Z             ...     ],
2025-07-17T07:05:47.1484050Z             ... ])
2025-07-17T07:05:47.1484100Z     
2025-07-17T07:05:47.1484230Z             >>> # If we call `torch.unique(a, dim=0)`, each of the tensors `a[idx, :, :]`
2025-07-17T07:05:47.1484370Z             >>> # will be compared. We can see that `a[0, :, :]` and `a[2, :, :]` match
2025-07-17T07:05:47.1484460Z             >>> # each other, so one of them will be removed.
2025-07-17T07:05:47.1484530Z             >>> (a[0, :, :] == a[2, :, :]).all()
2025-07-17T07:05:47.1484580Z             tensor(True)
2025-07-17T07:05:47.1484660Z             >>> a_unique_dim0 = torch.unique(a, dim=0)
2025-07-17T07:05:47.1484720Z             >>> a_unique_dim0
2025-07-17T07:05:47.1484770Z             tensor([[[0, 0, 1, 1],
2025-07-17T07:05:47.1484830Z                      [0, 0, 1, 1],
2025-07-17T07:05:47.1484880Z                      [1, 1, 1, 1]],
2025-07-17T07:05:47.1484930Z                     [[1, 1, 0, 0],
2025-07-17T07:05:47.1484980Z                      [1, 1, 0, 0],
2025-07-17T07:05:47.1485030Z                      [0, 0, 1, 1]]])
2025-07-17T07:05:47.1485070Z     
2025-07-17T07:05:47.1485210Z             >>> # Notice which sub-tensors from `a` match with the sub-tensors from
2025-07-17T07:05:47.1485260Z             >>> # `a_unique_dim0`:
2025-07-17T07:05:47.1485420Z             >>> (a_unique_dim0[0, :, :] == a[1, :, :]).all()
2025-07-17T07:05:47.1485470Z             tensor(True)
2025-07-17T07:05:47.1485560Z             >>> (a_unique_dim0[1, :, :] == a[0, :, :]).all()
2025-07-17T07:05:47.1485630Z             tensor(True)
2025-07-17T07:05:47.1485670Z     
2025-07-17T07:05:47.1485800Z             >>> # For `torch.unique(a, dim=1)`, each of the tensors `a[:, idx, :]` are
2025-07-17T07:05:47.1485920Z             >>> # compared. `a[:, 0, :]` and `a[:, 1, :]` match each other, so one of
2025-07-17T07:05:47.1485980Z             >>> # them will be removed.
2025-07-17T07:05:47.1486050Z             >>> (a[:, 0, :] == a[:, 1, :]).all()
2025-07-17T07:05:47.1486100Z             tensor(True)
2025-07-17T07:05:47.1486160Z             >>> torch.unique(a, dim=1)
2025-07-17T07:05:47.1486210Z             tensor([[[0, 0, 1, 1],
2025-07-17T07:05:47.1486260Z                      [1, 1, 0, 0]],
2025-07-17T07:05:47.1486340Z                     [[1, 1, 1, 1],
2025-07-17T07:05:47.1486420Z                      [0, 0, 1, 1]],
2025-07-17T07:05:47.1486470Z                     [[0, 0, 1, 1],
2025-07-17T07:05:47.1486520Z                      [1, 1, 0, 0]]])
2025-07-17T07:05:47.1486560Z     
2025-07-17T07:05:47.1486700Z             >>> # For `torch.unique(a, dim=2)`, the tensors `a[:, :, idx]` are compared.
2025-07-17T07:05:47.1486800Z             >>> # `a[:, :, 0]` and `a[:, :, 1]` match each other. Also, `a[:, :, 2]` and
2025-07-17T07:05:47.1486920Z             >>> # `a[:, :, 3]` match each other as well. So in this case, two of the
2025-07-17T07:05:47.1486990Z             >>> # sub-tensors will be removed.
2025-07-17T07:05:47.1487060Z             >>> (a[:, :, 0] == a[:, :, 1]).all()
2025-07-17T07:05:47.1487110Z             tensor(True)
2025-07-17T07:05:47.1487180Z             >>> (a[:, :, 2] == a[:, :, 3]).all()
2025-07-17T07:05:47.1487230Z             tensor(True)
2025-07-17T07:05:47.1487290Z             >>> torch.unique(a, dim=2)
2025-07-17T07:05:47.1487350Z             tensor([[[0, 1],
2025-07-17T07:05:47.1487400Z                      [0, 1],
2025-07-17T07:05:47.1487450Z                      [1, 0]],
2025-07-17T07:05:47.1487500Z                     [[1, 0],
2025-07-17T07:05:47.1487550Z                      [1, 0],
2025-07-17T07:05:47.1487600Z                      [1, 1]],
2025-07-17T07:05:47.1487650Z                     [[0, 1],
2025-07-17T07:05:47.1487700Z                      [0, 1],
2025-07-17T07:05:47.1487750Z                      [1, 0]]])
2025-07-17T07:05:47.1487790Z         
2025-07-17T07:05:47.1487950Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1487990Z     
2025-07-17T07:05:47.1488050Z       warnings.warn(msg)
2025-07-17T07:05:47.1488090Z     
2025-07-17T07:05:47.1488210Z --- Parse Warning: 12 / 136 ---
2025-07-17T07:05:47.1488870Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/serialization.py line=1285.
2025-07-17T07:05:47.1489040Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1489240Z     load(f, map_location=None, pickle_module=pickle, *, weights_only=True, mmap=None, **pickle_load_args)
2025-07-17T07:05:47.1489280Z     
2025-07-17T07:05:47.1489390Z         Loads an object saved with :func:`torch.save` from a file.
2025-07-17T07:05:47.1489430Z     
2025-07-17T07:05:47.1489570Z         :func:`torch.load` uses Python's unpickling facilities but treats storages,
2025-07-17T07:05:47.1489710Z         which underlie tensors, specially. They are first deserialized on the
2025-07-17T07:05:47.1489840Z         CPU and are then moved to the device they were saved from. If this fails
2025-07-17T07:05:47.1489980Z         (e.g. because the run time system doesn't have certain devices), an exception
2025-07-17T07:05:47.1490150Z         is raised. However, storages can be dynamically remapped to an alternative
2025-07-17T07:05:47.1490260Z         set of devices using the :attr:`map_location` argument.
2025-07-17T07:05:47.1490300Z     
2025-07-17T07:05:47.1490450Z         If :attr:`map_location` is a callable, it will be called once for each serialized
2025-07-17T07:05:47.1490620Z         storage with two arguments: storage and location. The storage argument
2025-07-17T07:05:47.1490760Z         will be the initial deserialization of the storage, residing on the CPU.
2025-07-17T07:05:47.1490890Z         Each serialized storage has a location tag associated with it which
2025-07-17T07:05:47.1491020Z         identifies the device it was saved from, and this tag is the second
2025-07-17T07:05:47.1491170Z         argument passed to :attr:`map_location`. The builtin location tags are ``'cpu'``
2025-07-17T07:05:47.1491300Z         for CPU tensors and ``'cuda:device_id'`` (e.g. ``'cuda:2'``) for CUDA tensors.
2025-07-17T07:05:47.1491450Z         :attr:`map_location` should return either ``None`` or a storage. If
2025-07-17T07:05:47.1491620Z         :attr:`map_location` returns a storage, it will be used as the final deserialized
2025-07-17T07:05:47.1491820Z         object, already moved to the right device. Otherwise, :func:`torch.load` will
2025-07-17T07:05:47.1504490Z         fall back to the default behavior, as if :attr:`map_location` wasn't specified.
2025-07-17T07:05:47.1504550Z     
2025-07-17T07:05:47.1504710Z         If :attr:`map_location` is a :class:`torch.device` object or a string containing
2025-07-17T07:05:47.1504860Z         a device tag, it indicates the location where all tensors should be loaded.
2025-07-17T07:05:47.1504900Z     
2025-07-17T07:05:47.1505050Z         Otherwise, if :attr:`map_location` is a dict, it will be used to remap location tags
2025-07-17T07:05:47.1505180Z         appearing in the file (keys), to ones that specify where to put the
2025-07-17T07:05:47.1505230Z         storages (values).
2025-07-17T07:05:47.1505280Z     
2025-07-17T07:05:47.1505420Z         User extensions can register their own location tags and tagging and
2025-07-17T07:05:47.1505580Z         deserialization methods using :func:`torch.serialization.register_package`.
2025-07-17T07:05:47.1505620Z     
2025-07-17T07:05:47.1505770Z         See :ref:`layout-control` for more advanced tools to manipulate a checkpoint.
2025-07-17T07:05:47.1505810Z     
2025-07-17T07:05:47.1505850Z         Args:
2025-07-17T07:05:47.1506050Z             f: a file-like object (has to implement :meth:`read`, :meth:`readline`, :meth:`tell`, and :meth:`seek`),
2025-07-17T07:05:47.1506160Z                 or a string or os.PathLike object containing a file name
2025-07-17T07:05:47.1506350Z             map_location: a function, :class:`torch.device`, string or a dict specifying how to remap storage
2025-07-17T07:05:47.1506400Z                 locations
2025-07-17T07:05:47.1506540Z             pickle_module: module used for unpickling metadata and objects (has to
2025-07-17T07:05:47.1506650Z                 match the :attr:`pickle_module` used to serialize file)
2025-07-17T07:05:47.1506780Z             weights_only: Indicates whether unpickler should be restricted to
2025-07-17T07:05:47.1506880Z                 loading only tensors, primitive types, dictionaries
2025-07-17T07:05:47.1507010Z                 and any types added via :func:`torch.serialization.add_safe_globals`.
2025-07-17T07:05:47.1507100Z                 See :ref:`weights-only` for more details.
2025-07-17T07:05:47.1507290Z             mmap: Indicates whether the file should be mapped rather than loading all the storages into memory.
2025-07-17T07:05:47.1507500Z                 Typically, tensor storages in the file will first be moved from disk to CPU memory, after which they
2025-07-17T07:05:47.1507690Z                 are moved to the location that they were tagged with when saving, or specified by ``map_location``. This
2025-07-17T07:05:47.1507890Z                 second step is a no-op if the final location is CPU. When the ``mmap`` flag is set, instead of copying the
2025-07-17T07:05:47.1508220Z                 tensor storages from disk to CPU memory in the first step, ``f`` is mapped, which means tensor storages
2025-07-17T07:05:47.1508320Z                 will be lazily loaded when their data is accessed.
2025-07-17T07:05:47.1508500Z             pickle_load_args: (Python 3 only) optional keyword arguments passed over to
2025-07-17T07:05:47.1508640Z                 :func:`pickle_module.load` and :func:`pickle_module.Unpickler`, e.g.,
2025-07-17T07:05:47.1508690Z                 :attr:`errors=...`.
2025-07-17T07:05:47.1508730Z     
2025-07-17T07:05:47.1508780Z         .. warning::
2025-07-17T07:05:47.1508910Z             :func:`torch.load()` unless `weights_only` parameter is set to `True`,
2025-07-17T07:05:47.1509030Z             uses ``pickle`` module implicitly, which is known to be insecure.
2025-07-17T07:05:47.1509240Z             It is possible to construct malicious pickle data which will execute arbitrary code
2025-07-17T07:05:47.1509410Z             during unpickling. Never load data that could have come from an untrusted
2025-07-17T07:05:47.1509590Z             source in an unsafe mode, or that could have been tampered with. **Only load data you trust**.
2025-07-17T07:05:47.1509630Z     
2025-07-17T07:05:47.1509680Z         .. note::
2025-07-17T07:05:47.1509840Z             When you call :func:`torch.load()` on a file which contains GPU tensors, those tensors
2025-07-17T07:05:47.1510010Z             will be loaded to GPU by default. You can call ``torch.load(.., map_location='cpu')``
2025-07-17T07:05:47.1510170Z             and then :meth:`load_state_dict` to avoid GPU RAM surge when loading a model checkpoint.
2025-07-17T07:05:47.1510210Z     
2025-07-17T07:05:47.1510260Z         .. note::
2025-07-17T07:05:47.1510410Z             By default, we decode byte strings as ``utf-8``.  This is to avoid a common error
2025-07-17T07:05:47.1510550Z             case ``UnicodeDecodeError: 'ascii' codec can't decode byte 0x...``
2025-07-17T07:05:47.1510680Z             when loading files saved by Python 2 in Python 3.  If this default
2025-07-17T07:05:47.1510840Z             is incorrect, you may use an extra :attr:`encoding` keyword argument to specify how
2025-07-17T07:05:47.1510980Z             these objects should be loaded, e.g., :attr:`encoding='latin1'` decodes them
2025-07-17T07:05:47.1511130Z             to strings using ``latin1`` encoding, and :attr:`encoding='bytes'` keeps them
2025-07-17T07:05:47.1511270Z             as byte arrays which can be decoded later with ``byte_array.decode(...)``.
2025-07-17T07:05:47.1511320Z     
2025-07-17T07:05:47.1511360Z         Example:
2025-07-17T07:05:47.1511440Z             >>> # xdoctest: +SKIP("undefined filepaths")
2025-07-17T07:05:47.1511530Z             >>> torch.load("tensors.pt", weights_only=True)
2025-07-17T07:05:47.1511590Z             # Load all tensors onto the CPU
2025-07-17T07:05:47.1511640Z             >>> torch.load(
2025-07-17T07:05:47.1511700Z             ...     "tensors.pt",
2025-07-17T07:05:47.1511780Z             ...     map_location=torch.device("cpu"),
2025-07-17T07:05:47.1511850Z             ...     weights_only=True,
2025-07-17T07:05:47.1511890Z             ... )
2025-07-17T07:05:47.1511980Z             # Load all tensors onto the CPU, using a function
2025-07-17T07:05:47.1512040Z             >>> torch.load(
2025-07-17T07:05:47.1512090Z             ...     "tensors.pt",
2025-07-17T07:05:47.1512190Z             ...     map_location=lambda storage, loc: storage,
2025-07-17T07:05:47.1512240Z             ...     weights_only=True,
2025-07-17T07:05:47.1512280Z             ... )
2025-07-17T07:05:47.1512350Z             # Load all tensors onto GPU 1
2025-07-17T07:05:47.1512390Z             >>> torch.load(
2025-07-17T07:05:47.1512450Z             ...     "tensors.pt",
2025-07-17T07:05:47.1512550Z             ...     map_location=lambda storage, loc: storage.cuda(1),
2025-07-17T07:05:47.1512610Z             ...     weights_only=True,
2025-07-17T07:05:47.1512680Z             ... )  # type: ignore[attr-defined]
2025-07-17T07:05:47.1512780Z             # Map tensors from GPU 1 to GPU 0
2025-07-17T07:05:47.1512830Z             >>> torch.load(
2025-07-17T07:05:47.1512890Z             ...     "tensors.pt",
2025-07-17T07:05:47.1512970Z             ...     map_location={"cuda:1": "cuda:0"},
2025-07-17T07:05:47.1513080Z             ...     weights_only=True,
2025-07-17T07:05:47.1513120Z             ... )
2025-07-17T07:05:47.1513200Z             # Load tensor from io.BytesIO object
2025-07-17T07:05:47.1513350Z             # Loading from a buffer setting weights_only=False, warning this can be unsafe
2025-07-17T07:05:47.1513420Z             >>> with open("tensor.pt", "rb") as f:
2025-07-17T07:05:47.1513490Z             ...     buffer = io.BytesIO(f.read())
2025-07-17T07:05:47.1513560Z             >>> torch.load(buffer, weights_only=False)
2025-07-17T07:05:47.1513660Z             # Load a module with 'ascii' encoding for unpickling
2025-07-17T07:05:47.1513830Z             # Loading from a module setting weights_only=False, warning this can be unsafe
2025-07-17T07:05:47.1513970Z             >>> torch.load("module.pt", encoding="ascii", weights_only=False)
2025-07-17T07:05:47.1514020Z         
2025-07-17T07:05:47.1514170Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1514210Z     
2025-07-17T07:05:47.1514260Z       warnings.warn(msg)
2025-07-17T07:05:47.1514300Z     
2025-07-17T07:05:47.1514460Z --- Parse Warning: 13 / 136 ---
2025-07-17T07:05:47.1515120Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Future.then in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/futures/__init__.py line=101.
2025-07-17T07:05:47.1515280Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1515320Z     
2025-07-17T07:05:47.1515460Z     Append the given callback function to this ``Future``, which will be run
2025-07-17T07:05:47.1515590Z     when the ``Future`` is completed.  Multiple callbacks can be added to
2025-07-17T07:05:47.1515720Z     the same ``Future``, but the order in which they will be executed cannot
2025-07-17T07:05:47.1515830Z     be guaranteed (to enforce a certain order consider chaining:
2025-07-17T07:05:47.1515960Z     ``fut.then(cb1).then(cb2)``). The callback must take one argument, which
2025-07-17T07:05:47.1516080Z     is the reference to this ``Future``. The callback function can use the
2025-07-17T07:05:47.1516200Z     :meth:`value` method to get the value. Note that if this ``Future`` is
2025-07-17T07:05:47.1516340Z     already completed, the given callback will be run immediately inline.
2025-07-17T07:05:47.1516380Z     
2025-07-17T07:05:47.1516500Z     If the ``Future``'s value contains tensors that reside on GPUs, the
2025-07-17T07:05:47.1516630Z     callback might be invoked while the async kernels that are populating
2025-07-17T07:05:47.1516770Z     those tensors haven't yet finished executing on the device. However, the
2025-07-17T07:05:47.1516890Z     callback will be invoked with some dedicated streams set as current
2025-07-17T07:05:47.1517020Z     (fetched from a global pool) which will be synchronized with those
2025-07-17T07:05:47.1517160Z     kernels. Hence any operation performed by the callback on these tensors
2025-07-17T07:05:47.1517280Z     will be scheduled on the device after the kernels complete. In other
2025-07-17T07:05:47.1517400Z     words, as long as the callback doesn't switch streams, it can safely
2025-07-17T07:05:47.1517540Z     manipulate the result without any additional synchronization. This is
2025-07-17T07:05:47.1517640Z     similar to the non-blocking behavior of :meth:`wait`.
2025-07-17T07:05:47.1517680Z     
2025-07-17T07:05:47.1517800Z     Similarly, if the callback returns a value that contains tensors that
2025-07-17T07:05:47.1517920Z     reside on a GPU, it can do so even if the kernels that are producing
2025-07-17T07:05:47.1518080Z     these tensors are still running on the device, as long as the callback
2025-07-17T07:05:47.1518210Z     didn't change streams during its execution. If one wants to change
2025-07-17T07:05:47.1518340Z     streams, one must be careful to re-synchronize them with the original
2025-07-17T07:05:47.1518490Z     streams, that is, those that were current when the callback was invoked.
2025-07-17T07:05:47.1518530Z     
2025-07-17T07:05:47.1518570Z     Args:
2025-07-17T07:05:47.1518690Z         callback(``Callable``): a ``Callable`` that takes this ``Future`` as
2025-07-17T07:05:47.1518760Z                                 the only argument.
2025-07-17T07:05:47.1518800Z     
2025-07-17T07:05:47.1518840Z     Returns:
2025-07-17T07:05:47.1518950Z         A new ``Future`` object that holds the return value of the
2025-07-17T07:05:47.1519050Z         ``callback`` and will be marked as completed when the given
2025-07-17T07:05:47.1519130Z         ``callback`` finishes.
2025-07-17T07:05:47.1519190Z     
2025-07-17T07:05:47.1519300Z     .. note:: Note that if the callback function throws, either
2025-07-17T07:05:47.1519420Z         through the original future being completed with an exception and
2025-07-17T07:05:47.1519550Z         calling ``fut.wait()``, or through other code in the callback, the
2025-07-17T07:05:47.1519670Z         future returned by ``then`` will be marked appropriately with the
2025-07-17T07:05:47.1519790Z         encountered error. However, if this callback later completes
2025-07-17T07:05:47.1519910Z         additional futures, those futures are not marked as completed with
2025-07-17T07:05:47.1520030Z         an error and the user is responsible for handling completion/waiting
2025-07-17T07:05:47.1520100Z         on those futures independently.
2025-07-17T07:05:47.1520140Z     
2025-07-17T07:05:47.1520180Z     Example::
2025-07-17T07:05:47.1520220Z     
2025-07-17T07:05:47.1520310Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES)
2025-07-17T07:05:47.1520370Z         >>> def callback(fut):
2025-07-17T07:05:47.1520460Z         ...     print(f"RPC return value is {fut.wait()}.")
2025-07-17T07:05:47.1520520Z         >>> fut = torch.futures.Future()
2025-07-17T07:05:47.1520630Z         >>> # The inserted callback will print the return value when
2025-07-17T07:05:47.1520700Z         >>> # receiving the response from "worker1"
2025-07-17T07:05:47.1520760Z         >>> cb_fut = fut.then(callback)
2025-07-17T07:05:47.1520820Z         >>> chain_cb_fut = cb_fut.then(
2025-07-17T07:05:47.1520910Z         ...     lambda x : print(f"Chained cb done. {x.wait()}")
2025-07-17T07:05:47.1520950Z         ... )
2025-07-17T07:05:47.1521000Z         >>> fut.set_result(5)
2025-07-17T07:05:47.1521060Z         RPC return value is 5.
2025-07-17T07:05:47.1521110Z         Chained cb done. None
2025-07-17T07:05:47.1521150Z     
2025-07-17T07:05:47.1521310Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1521350Z     
2025-07-17T07:05:47.1521400Z       warnings.warn(msg)
2025-07-17T07:05:47.1521450Z     
2025-07-17T07:05:47.1521550Z --- Parse Warning: 14 / 136 ---
2025-07-17T07:05:47.1522210Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Future.set_result in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/futures/__init__.py line=211.
2025-07-17T07:05:47.1522370Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1522410Z     
2025-07-17T07:05:47.1522540Z     Set the result for this ``Future``, which will mark this ``Future`` as
2025-07-17T07:05:47.1522670Z     completed and trigger all attached callbacks. Note that a ``Future``
2025-07-17T07:05:47.1522730Z     cannot be marked completed twice.
2025-07-17T07:05:47.1522770Z     
2025-07-17T07:05:47.1522900Z     If the result contains tensors that reside on GPUs, this method can be
2025-07-17T07:05:47.1523040Z     called even if the asynchronous kernels that are populating those
2025-07-17T07:05:47.1523180Z     tensors haven't yet completed running on the device, provided that the
2025-07-17T07:05:47.1523320Z     streams on which those kernels were enqueued are set as the current ones
2025-07-17T07:05:47.1523480Z     when this method is called. Put simply, it's safe to call this method
2025-07-17T07:05:47.1523610Z     immediately after launching those kernels, without any additional
2025-07-17T07:05:47.1523750Z     synchronization, as long as one doesn't change streams in between. This
2025-07-17T07:05:47.1523880Z     method will record events on all the relevant current streams and will
2025-07-17T07:05:47.1524000Z     use them to ensure proper scheduling for all the consumers of this
2025-07-17T07:05:47.1524050Z     ``Future``.
2025-07-17T07:05:47.1524090Z     
2025-07-17T07:05:47.1524130Z     Args:
2025-07-17T07:05:47.1524250Z         result (object): the result object of this ``Future``.
2025-07-17T07:05:47.1524310Z     
2025-07-17T07:05:47.1524360Z     Example::
2025-07-17T07:05:47.1524390Z     
2025-07-17T07:05:47.1524490Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES)
2025-07-17T07:05:47.1524540Z         >>> import threading
2025-07-17T07:05:47.1524590Z         >>> import time
2025-07-17T07:05:47.1524650Z         >>> def slow_set_future(fut, value):
2025-07-17T07:05:47.1524710Z         ...     time.sleep(0.5)
2025-07-17T07:05:47.1524770Z         ...     fut.set_result(value)
2025-07-17T07:05:47.1524830Z         >>> fut = torch.futures.Future()
2025-07-17T07:05:47.1524890Z         >>> t = threading.Thread(
2025-07-17T07:05:47.1524950Z         ...     target=slow_set_future,
2025-07-17T07:05:47.1525020Z         ...     args=(fut, torch.ones(2) * 3)
2025-07-17T07:05:47.1525060Z         ... )
2025-07-17T07:05:47.1525100Z         >>> t.start()
2025-07-17T07:05:47.1525160Z         >>> print(fut.wait())
2025-07-17T07:05:47.1525210Z         tensor([3., 3.])
2025-07-17T07:05:47.1525250Z         >>> t.join()
2025-07-17T07:05:47.1525300Z     
2025-07-17T07:05:47.1525450Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1525480Z     
2025-07-17T07:05:47.1525540Z       warnings.warn(msg)
2025-07-17T07:05:47.1525580Z     
2025-07-17T07:05:47.1525680Z --- Parse Warning: 15 / 136 ---
2025-07-17T07:05:47.1526330Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=compile_shader in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/mps/__init__.py line=145.
2025-07-17T07:05:47.1526490Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1526620Z     Compiles compute shader from source and allows one to invoke kernels
2025-07-17T07:05:47.1526710Z         defined there from the comfort of Python runtime
2025-07-17T07:05:47.1526750Z         Example::
2025-07-17T07:05:47.1526800Z     
2025-07-17T07:05:47.1526880Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_MPS)
2025-07-17T07:05:47.1526950Z             >>> lib = torch.mps.compile_shader(
2025-07-17T07:05:47.1527180Z             ... "kernel void full(device float* out, constant float& val, uint idx [[thread_position_in_grid]]) { out[idx] = val; }"
2025-07-17T07:05:47.1527230Z             ...  )
2025-07-17T07:05:47.1527290Z             >>> x = torch.zeros(16, device="mps")
2025-07-17T07:05:47.1527350Z             >>> lib.full(x, 3.14)
2025-07-17T07:05:47.1527390Z         
2025-07-17T07:05:47.1527540Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1527590Z     
2025-07-17T07:05:47.1527630Z       warnings.warn(msg)
2025-07-17T07:05:47.1527680Z     
2025-07-17T07:05:47.1527780Z --- Parse Warning: 16 / 136 ---
2025-07-17T07:05:47.1528540Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=compute_required_storage_length in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_prims_common/__init__.py line=1848.
2025-07-17T07:05:47.1528720Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1528850Z     Computes the minimum storage size to hold the given tensor geometry.
2025-07-17T07:05:47.1528890Z     
2025-07-17T07:05:47.1528940Z         Example
2025-07-17T07:05:47.1528980Z         =======
2025-07-17T07:05:47.1529020Z     
2025-07-17T07:05:47.1529150Z         This is the size of a newly allocated tensor's storage, in units of elements
2025-07-17T07:05:47.1529200Z     
2025-07-17T07:05:47.1529250Z         >>> t = torch.empty((10, 20))
2025-07-17T07:05:47.1529400Z         >>> compute_required_storage_length(t.shape, t.stride(), t.storage_offset())
2025-07-17T07:05:47.1529440Z         200
2025-07-17T07:05:47.1529510Z     
2025-07-17T07:05:47.1529600Z         >>> # xdoctest: +SKIP(failing)
2025-07-17T07:05:47.1529690Z         >>> t2 = torch.empty_strided((1, 2, 3), (5, 7, 11))
2025-07-17T07:05:47.1529760Z         >>> size = compute_required_storage_length(
2025-07-17T07:05:47.1529850Z         ...     t2.shape, t2.stride(), t2.storage_offset()
2025-07-17T07:05:47.1529890Z         ... )
2025-07-17T07:05:47.1529950Z         >>> size == t.storage().size()
2025-07-17T07:05:47.1530000Z         True
2025-07-17T07:05:47.1530030Z     
2025-07-17T07:05:47.1530150Z         A valid tensor may have a larger storage size, but never smaller
2025-07-17T07:05:47.1530200Z     
2025-07-17T07:05:47.1530260Z         >>> slice = torch.empty(100)[20:40]
2025-07-17T07:05:47.1530320Z         >>> slice.storage().size()
2025-07-17T07:05:47.1530360Z         100
2025-07-17T07:05:47.1530410Z     
2025-07-17T07:05:47.1530470Z         >>> compute_required_storage_length(
2025-07-17T07:05:47.1530580Z         ...     slice.shape, slice.stride(), slice.storage_offset()
2025-07-17T07:05:47.1530620Z         ... )
2025-07-17T07:05:47.1530670Z         40
2025-07-17T07:05:47.1530710Z     
2025-07-17T07:05:47.1530750Z         
2025-07-17T07:05:47.1530900Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1530940Z     
2025-07-17T07:05:47.1530990Z       warnings.warn(msg)
2025-07-17T07:05:47.1531030Z     
2025-07-17T07:05:47.1531130Z --- Parse Warning: 17 / 136 ---
2025-07-17T07:05:47.1531750Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=cudart in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/cuda/__init__.py line=434.
2025-07-17T07:05:47.1531900Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:47.1531970Z     Retrieves the CUDA runtime API module.
2025-07-17T07:05:47.1532010Z     
2025-07-17T07:05:47.1532050Z     
2025-07-17T07:05:47.1532210Z         This function initializes the CUDA runtime environment if it is not already
2025-07-17T07:05:47.1532350Z         initialized and returns the CUDA runtime API module (_cudart). The CUDA
2025-07-17T07:05:47.1532490Z         runtime API module provides access to various CUDA runtime functions.
2025-07-17T07:05:47.1532530Z     
2025-07-17T07:05:47.1532570Z         Args:
2025-07-17T07:05:47.1532620Z             ``None``
2025-07-17T07:05:47.1532660Z     
2025-07-17T07:05:47.1532700Z         Returns:
2025-07-17T07:05:47.1532780Z             module: The CUDA runtime API module (_cudart).
2025-07-17T07:05:47.1532830Z     
2025-07-17T07:05:47.1532870Z         Raises:
2025-07-17T07:05:47.1533010Z             RuntimeError: If CUDA cannot be re-initialized in a forked subprocess.
2025-07-17T07:05:47.1533220Z             AssertionError: If PyTorch is not compiled with CUDA support or if libcudart functions are unavailable.
2025-07-17T07:05:47.1533270Z     
2025-07-17T07:05:47.1533370Z         Example of CUDA operations with profiling:
2025-07-17T07:05:47.1533430Z             >>> import torch
2025-07-17T07:05:47.1533510Z             >>> from torch.cuda import cudart, check_error
2025-07-17T07:05:47.1533560Z             >>> import os
2025-07-17T07:05:47.1533620Z             >>>
2025-07-17T07:05:47.1533700Z             >>> os.environ["CUDA_PROFILE"] = "1"
2025-07-17T07:05:47.1533740Z             >>>
2025-07-17T07:05:47.1533820Z             >>> def perform_cuda_operations_with_streams():
2025-07-17T07:05:47.1533900Z             >>>     stream = torch.cuda.Stream()
2025-07-17T07:05:47.1533960Z             >>>     with torch.cuda.stream(stream):
2025-07-17T07:05:47.1534050Z             >>>         x = torch.randn(100, 100, device='cuda')
2025-07-17T07:05:47.1534130Z             >>>         y = torch.randn(100, 100, device='cuda')
2025-07-17T07:05:47.1534190Z             >>>         z = torch.mul(x, y)
2025-07-17T07:05:47.1534230Z             >>>     return z
2025-07-17T07:05:47.1534410Z             >>>
2025-07-17T07:05:47.1534540Z             >>> torch.cuda.synchronize()
2025-07-17T07:05:47.1534630Z             >>> print("====== Start nsys profiling ======")
2025-07-17T07:05:47.1534710Z             >>> check_error(cudart().cudaProfilerStart())
2025-07-17T07:05:47.1534800Z             >>> with torch.autograd.profiler.emit_nvtx():
2025-07-17T07:05:47.1534890Z             >>>     result = perform_cuda_operations_with_streams()
2025-07-17T07:05:47.1534970Z             >>>     print("CUDA operations completed.")
2025-07-17T07:05:47.1535070Z             >>> check_error(torch.cuda.cudart().cudaProfilerStop())
2025-07-17T07:05:47.1535150Z             >>> print("====== End nsys profiling ======")
2025-07-17T07:05:47.1535190Z     
2025-07-17T07:05:47.1535310Z         To run this example and save the profiling information, execute:
2025-07-17T07:05:47.1535530Z             >>> $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py
2025-07-17T07:05:47.1535570Z     
2025-07-17T07:05:47.1535730Z         This command profiles the CUDA operations in the provided script and saves
2025-07-17T07:05:47.1535840Z         the profiling information to a file named `trace_name.prof`.
2025-07-17T07:05:47.1535990Z         The `--profile-from-start off` option ensures that profiling starts only
2025-07-17T07:05:47.1536080Z         after the `cudaProfilerStart` call in the script.
2025-07-17T07:05:47.1536210Z         The `--csv` and `--print-summary` options format the profiling output as a
2025-07-17T07:05:47.1536290Z         CSV file and print a summary, respectively.
2025-07-17T07:05:47.1536440Z         The `-o` option specifies the output file name, and the `-f` option forces the
2025-07-17T07:05:47.1536530Z         overwrite of the output file if it already exists.
2025-07-17T07:05:47.1536570Z         
2025-07-17T07:05:47.1536960Z     Original Error: SyntaxError('invalid syntax', ('<source_block>', 1, 1, '$ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py\n', 1, 2))
2025-07-17T07:05:47.1537000Z     
2025-07-17T07:05:47.1537210Z     $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py
2025-07-17T07:05:47.1537250Z     ^
2025-07-17T07:05:47.1537300Z       warnings.warn(msg)
2025-07-17T07:05:47.1537340Z     
2025-07-17T07:05:47.1537450Z --- Parse Warning: 18 / 136 ---
2025-07-17T07:05:47.1538110Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=is_available in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/accelerator/__init__.py line=66.
2025-07-17T07:05:47.1538260Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:47.1538410Z     Check if the current accelerator is available at runtime: it was build, all the
2025-07-17T07:05:47.1538540Z         required drivers are available and at least one device is visible.
2025-07-17T07:05:47.1538670Z         See :ref:`accelerator<accelerators>` for details.
2025-07-17T07:05:47.1538710Z     
2025-07-17T07:05:47.1538760Z         Returns:
2025-07-17T07:05:47.1538930Z             bool: A boolean indicating if there is an available :ref:`accelerator<accelerators>`.
2025-07-17T07:05:47.1538990Z     
2025-07-17T07:05:47.1539150Z         .. note:: This API delegates to the device-specific version of `is_available`.
2025-07-17T07:05:47.1539310Z             On CUDA, when the environment variable ``PYTORCH_NVML_BASED_CUDA_CHECK=1`` is set,
2025-07-17T07:05:47.1539460Z             this function will NOT poison fork. Otherwise, it will. For more details, see
2025-07-17T07:05:47.1539550Z             :ref:`multiprocessing-poison-fork-note`.
2025-07-17T07:05:47.1539600Z     
2025-07-17T07:05:47.1539640Z         Example::
2025-07-17T07:05:47.1539680Z     
2025-07-17T07:05:47.1539860Z             >>> assert torch.accelerator.is_available() "No available accelerators detected."
2025-07-17T07:05:47.1539930Z         
2025-07-17T07:05:47.1540260Z     Original Error: SyntaxError('invalid syntax', ('<source_block>', 1, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 1, 78))
2025-07-17T07:05:47.1540300Z     
2025-07-17T07:05:47.1540460Z     assert torch.accelerator.is_available() "No available accelerators detected."
2025-07-17T07:05:47.1540520Z                                             ^
2025-07-17T07:05:47.1540570Z       warnings.warn(msg)
2025-07-17T07:05:47.1540610Z     
2025-07-17T07:05:47.1540710Z --- Parse Warning: 19 / 136 ---
2025-07-17T07:05:47.1541370Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=synchronize in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/accelerator/__init__.py line=212.
2025-07-17T07:05:47.1541520Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:47.1541650Z     Wait for all kernels in all streams on the given device to complete.
2025-07-17T07:05:47.1541690Z     
2025-07-17T07:05:47.1541730Z         Args:
2025-07-17T07:05:47.1541930Z             device (:class:`torch.device`, str, int, optional): device for which to synchronize. It must match
2025-07-17T07:05:47.1542070Z                 the current :ref:`accelerator<accelerators>` device type. If not given,
2025-07-17T07:05:47.1542190Z                 use :func:`torch.accelerator.current_device_index` by default.
2025-07-17T07:05:47.1542230Z     
2025-07-17T07:05:47.1542410Z         .. note:: This function is a no-op if the current :ref:`accelerator<accelerators>` is not initialized.
2025-07-17T07:05:47.1542450Z     
2025-07-17T07:05:47.1542500Z         Example::
2025-07-17T07:05:47.1542540Z     
2025-07-17T07:05:47.1542620Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-07-17T07:05:47.1542790Z             >>> assert torch.accelerator.is_available() "No available accelerators detected."
2025-07-17T07:05:47.1542880Z             >>> start_event = torch.Event(enable_timing=True)
2025-07-17T07:05:47.1542970Z             >>> end_event = torch.Event(enable_timing=True)
2025-07-17T07:05:47.1543030Z             >>> start_event.record()
2025-07-17T07:05:47.1543180Z             >>> tensor = torch.randn(100, device=torch.accelerator.current_accelerator())
2025-07-17T07:05:47.1543240Z             >>> sum = torch.sum(tensor)
2025-07-17T07:05:47.1543300Z             >>> end_event.record()
2025-07-17T07:05:47.1543380Z             >>> torch.accelerator.synchronize()
2025-07-17T07:05:47.1543480Z             >>> elapsed_time_ms = start_event.elapsed_time(end_event)
2025-07-17T07:05:47.1543520Z         
2025-07-17T07:05:47.1543850Z     Original Error: SyntaxError('invalid syntax', ('<source_block>', 2, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 2, 78))
2025-07-17T07:05:47.1543890Z     
2025-07-17T07:05:47.1544090Z     assert torch.accelerator.is_available() "No available accelerators detected."
2025-07-17T07:05:47.1544150Z                                             ^
2025-07-17T07:05:47.1544210Z       warnings.warn(msg)
2025-07-17T07:05:47.1544280Z     
2025-07-17T07:05:47.1544380Z --- Parse Warning: 20 / 136 ---
2025-07-17T07:05:47.1545000Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=sum in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/sparse/__init__.py line=202.
2025-07-17T07:05:47.1545150Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1545250Z     Return the sum of each row of the given sparse tensor.
2025-07-17T07:05:47.1545290Z     
2025-07-17T07:05:47.1545450Z         Returns the sum of each row of the sparse tensor :attr:`input` in the given
2025-07-17T07:05:47.1545590Z         dimensions :attr:`dim`. If :attr:`dim` is a list of dimensions,
2025-07-17T07:05:47.1545720Z         reduce over all of them. When sum over all ``sparse_dim``, this method
2025-07-17T07:05:47.1545810Z         returns a dense tensor instead of a sparse tensor.
2025-07-17T07:05:47.1545850Z     
2025-07-17T07:05:47.1546010Z         All summed :attr:`dim` are squeezed (see :func:`torch.squeeze`), resulting an output
2025-07-17T07:05:47.1546130Z         tensor having :attr:`dim` fewer dimensions than :attr:`input`.
2025-07-17T07:05:47.1546170Z     
2025-07-17T07:05:47.1546300Z         During backward, only gradients at ``nnz`` locations of :attr:`input`
2025-07-17T07:05:47.1546450Z         will propagate back. Note that the gradients of :attr:`input` is coalesced.
2025-07-17T07:05:47.1546490Z     
2025-07-17T07:05:47.1546530Z         Args:
2025-07-17T07:05:47.1546600Z             input (Tensor): the input sparse tensor
2025-07-17T07:05:47.1546770Z             dim (int or tuple of ints): a dimension or a list of dimensions to reduce. Default: reduce
2025-07-17T07:05:47.1546820Z                 over all dims.
2025-07-17T07:05:47.1546980Z             dtype (:class:`torch.dtype`, optional): the desired data type of returned Tensor.
2025-07-17T07:05:47.1547050Z                 Default: dtype of :attr:`input`.
2025-07-17T07:05:47.1547100Z     
2025-07-17T07:05:47.1547140Z         Example::
2025-07-17T07:05:47.1547180Z     
2025-07-17T07:05:47.1547230Z             >>> nnz = 3
2025-07-17T07:05:47.1547280Z             >>> dims = [5, 5, 2, 3]
2025-07-17T07:05:47.1547380Z             >>> I = torch.cat([torch.randint(0, dims[0], size=(nnz,)),
2025-07-17T07:05:47.1547500Z                                torch.randint(0, dims[1], size=(nnz,))], 0).reshape(2, nnz)
2025-07-17T07:05:47.1547570Z             >>> V = torch.randn(nnz, dims[2], dims[3])
2025-07-17T07:05:47.1547630Z             >>> size = torch.Size(dims)
2025-07-17T07:05:47.1547720Z             >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-07-17T07:05:47.1547800Z             >>> S = torch.sparse_coo_tensor(I, V, size)
2025-07-17T07:05:47.1547840Z             >>> S
2025-07-17T07:05:47.1547910Z             tensor(indices=tensor([[2, 0, 3],
2025-07-17T07:05:47.1547970Z                                    [2, 4, 1]]),
2025-07-17T07:05:47.1548050Z                    values=tensor([[[-0.6438, -1.6467,  1.4004],
2025-07-17T07:05:47.1548130Z                                    [ 0.3411,  0.0918, -0.2312]],
2025-07-17T07:05:47.1548170Z     
2025-07-17T07:05:47.1548230Z                                   [[ 0.5348,  0.0634, -2.0494],
2025-07-17T07:05:47.1548300Z                                    [-0.7125, -1.0646,  2.1844]],
2025-07-17T07:05:47.1548350Z     
2025-07-17T07:05:47.1548420Z                                   [[ 0.1276,  0.1874, -0.6334],
2025-07-17T07:05:47.1548490Z                                    [-1.9682, -0.5340,  0.7483]]]),
2025-07-17T07:05:47.1548580Z                    size=(5, 5, 2, 3), nnz=3, layout=torch.sparse_coo)
2025-07-17T07:05:47.1548620Z     
2025-07-17T07:05:47.1548760Z             # when sum over only part of sparse_dims, return a sparse tensor
2025-07-17T07:05:47.1548830Z             >>> torch.sparse.sum(S, [1, 3])
2025-07-17T07:05:47.1548900Z             tensor(indices=tensor([[0, 2, 3]]),
2025-07-17T07:05:47.1548990Z                    values=tensor([[-1.4512,  0.4073],
2025-07-17T07:05:47.1549050Z                                   [-0.8901,  0.2017],
2025-07-17T07:05:47.1549120Z                                   [-0.3183, -1.7539]]),
2025-07-17T07:05:47.1549200Z                    size=(5, 2), nnz=3, layout=torch.sparse_coo)
2025-07-17T07:05:47.1549240Z     
2025-07-17T07:05:47.1549340Z             # when sum over all sparse dim, return a dense tensor
2025-07-17T07:05:47.1549390Z             # with summed dims squeezed
2025-07-17T07:05:47.1549460Z             >>> torch.sparse.sum(S, [0, 1, 3])
2025-07-17T07:05:47.1549520Z             tensor([-2.6596, -1.1450])
2025-07-17T07:05:47.1549560Z         
2025-07-17T07:05:47.1549740Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1549810Z     
2025-07-17T07:05:47.1549860Z       warnings.warn(msg)
2025-07-17T07:05:47.1549900Z     
2025-07-17T07:05:47.1550000Z --- Parse Warning: 21 / 136 ---
2025-07-17T07:05:47.1550630Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=vmap in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/apis.py line=39.
2025-07-17T07:05:47.1550780Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1550820Z     
2025-07-17T07:05:47.1550960Z     vmap is the vectorizing map; ``vmap(func)`` returns a new function that
2025-07-17T07:05:47.1551070Z     maps ``func`` over some dimension of the inputs. Semantically, vmap
2025-07-17T07:05:47.1551210Z     pushes the map into PyTorch operations called by ``func``, effectively
2025-07-17T07:05:47.1551270Z     vectorizing those operations.
2025-07-17T07:05:47.1551320Z     
2025-07-17T07:05:47.1551450Z     vmap is useful for handling batch dimensions: one can write a function
2025-07-17T07:05:47.1551570Z     ``func`` that runs on examples and then lift it to a function that can
2025-07-17T07:05:47.1551690Z     take batches of examples with ``vmap(func)``. vmap can also be used to
2025-07-17T07:05:47.1551800Z     compute batched gradients when composed with autograd.
2025-07-17T07:05:47.1551840Z     
2025-07-17T07:05:47.1551880Z     .. note::
2025-07-17T07:05:47.1551990Z         :func:`torch.vmap` is aliased to :func:`torch.func.vmap` for
2025-07-17T07:05:47.1552070Z         convenience. Use whichever one you'd like.
2025-07-17T07:05:47.1552110Z     
2025-07-17T07:05:47.1552150Z     Args:
2025-07-17T07:05:47.1552280Z         func (function): A Python function that takes one or more arguments.
2025-07-17T07:05:47.1552340Z             Must return one or more Tensors.
2025-07-17T07:05:47.1552470Z         in_dims (int or nested structure): Specifies which dimension of the
2025-07-17T07:05:47.1552580Z             inputs should be mapped over. ``in_dims`` should have a
2025-07-17T07:05:47.1552700Z             structure like the inputs. If the ``in_dim`` for a particular
2025-07-17T07:05:47.1552810Z             input is None, then that indicates there is no map dimension.
2025-07-17T07:05:47.1552860Z             Default: 0.
2025-07-17T07:05:47.1552980Z         out_dims (int or Tuple[int]): Specifies where the mapped dimension
2025-07-17T07:05:47.1553100Z             should appear in the outputs. If ``out_dims`` is a Tuple, then
2025-07-17T07:05:47.1553190Z             it should have one element per output. Default: 0.
2025-07-17T07:05:47.1553300Z         randomness (str): Specifies whether the randomness in this
2025-07-17T07:05:47.1553430Z             vmap should be the same or different across batches. If 'different',
2025-07-17T07:05:47.1553550Z             the randomness for each batch will be different. If 'same', the
2025-07-17T07:05:47.1553700Z             randomness will be the same across batches. If 'error', any calls to
2025-07-17T07:05:47.1553820Z             random functions will error. Default: 'error'. WARNING: this flag
2025-07-17T07:05:47.1553970Z             only applies to random PyTorch operations and does not apply to
2025-07-17T07:05:47.1554050Z             Python's random module or numpy randomness.
2025-07-17T07:05:47.1554190Z         chunk_size (None or int): If None (default), apply a single vmap over inputs.
2025-07-17T07:05:47.1554320Z             If not None, then compute the vmap :attr:`chunk_size` samples at a time.
2025-07-17T07:05:47.1554480Z             Note that :attr:`chunk_size=1` is equivalent to computing the vmap with a for-loop.
2025-07-17T07:05:47.1554640Z             If you run into memory issues computing the vmap, please try a non-None chunk_size.
2025-07-17T07:05:47.1554680Z     
2025-07-17T07:05:47.1554740Z     Returns:
2025-07-17T07:05:47.1554890Z         Returns a new "batched" function. It takes the same inputs as
2025-07-17T07:05:47.1555000Z         ``func``, except each input has an extra dimension at the index
2025-07-17T07:05:47.1555120Z         specified by ``in_dims``. It takes returns the same outputs as
2025-07-17T07:05:47.1555240Z         ``func``, except each output has an extra dimension at the index
2025-07-17T07:05:47.1555300Z         specified by ``out_dims``.
2025-07-17T07:05:47.1555340Z     
2025-07-17T07:05:47.1555380Z     .. warning:
2025-07-17T07:05:47.1555500Z         :func:`vmap` works best with functional-style code. Please do not
2025-07-17T07:05:47.1555620Z         perform any side-effects in ``func``, with the exception of
2025-07-17T07:05:47.1555760Z         in-place PyTorch operations. Examples of side-effects include mutating
2025-07-17T07:05:47.1555890Z         Python data structures and assigning values to variables not captured
2025-07-17T07:05:47.1555940Z         in ``func``.
2025-07-17T07:05:47.1555980Z     
2025-07-17T07:05:47.1556130Z     One example of using :func:`vmap` is to compute batched dot products. PyTorch
2025-07-17T07:05:47.1556260Z     doesn't provide a batched ``torch.dot`` API; instead of unsuccessfully
2025-07-17T07:05:47.1556390Z     rummaging through docs, use :func:`vmap` to construct a new function.
2025-07-17T07:05:47.1556430Z     
2025-07-17T07:05:47.1556490Z         >>> torch.dot  # [D], [D] -> []
2025-07-17T07:05:47.1556610Z         >>> batched_dot = torch.func.vmap(torch.dot)  # [N, D], [N, D] -> [N]
2025-07-17T07:05:47.1556690Z         >>> x, y = torch.randn(2, 5), torch.randn(2, 5)
2025-07-17T07:05:47.1556740Z         >>> batched_dot(x, y)
2025-07-17T07:05:47.1556780Z     
2025-07-17T07:05:47.1556920Z     :func:`vmap` can be helpful in hiding batch dimensions, leading to a simpler
2025-07-17T07:05:47.1556980Z     model authoring experience.
2025-07-17T07:05:47.1557020Z     
2025-07-17T07:05:47.1557090Z         >>> batch_size, feature_size = 3, 5
2025-07-17T07:05:47.1557190Z         >>> weights = torch.randn(feature_size, requires_grad=True)
2025-07-17T07:05:47.1557240Z         >>>
2025-07-17T07:05:47.1557300Z         >>> def model(feature_vec):
2025-07-17T07:05:47.1557370Z         >>> # Very simple linear model with activation
2025-07-17T07:05:47.1557450Z         >>>     return feature_vec.dot(weights).relu()
2025-07-17T07:05:47.1557500Z         >>>
2025-07-17T07:05:47.1561590Z         >>> examples = torch.randn(batch_size, feature_size)
2025-07-17T07:05:47.1561700Z         >>> result = torch.vmap(model)(examples)
2025-07-17T07:05:47.1561740Z     
2025-07-17T07:05:47.1561890Z     :func:`vmap` can also help vectorize computations that were previously difficult
2025-07-17T07:05:47.1562030Z     or impossible to batch. One example is higher-order gradient computation.
2025-07-17T07:05:47.1562170Z     The PyTorch autograd engine computes vjps (vector-Jacobian products).
2025-07-17T07:05:47.1562320Z     Computing a full Jacobian matrix for some function f: R^N -> R^N usually
2025-07-17T07:05:47.1562570Z     requires N calls to ``autograd.grad``, one per Jacobian row. Using :func:`vmap`,
2025-07-17T07:05:47.1562720Z     we can vectorize the whole computation, computing the Jacobian in a single
2025-07-17T07:05:47.1562780Z     call to ``autograd.grad``.
2025-07-17T07:05:47.1562840Z     
2025-07-17T07:05:47.1562890Z         >>> # Setup
2025-07-17T07:05:47.1562930Z         >>> N = 5
2025-07-17T07:05:47.1562990Z         >>> f = lambda x: x**2
2025-07-17T07:05:47.1563070Z         >>> x = torch.randn(N, requires_grad=True)
2025-07-17T07:05:47.1563120Z         >>> y = f(x)
2025-07-17T07:05:47.1563180Z         >>> I_N = torch.eye(N)
2025-07-17T07:05:47.1563220Z         >>>
2025-07-17T07:05:47.1563280Z         >>> # Sequential approach
2025-07-17T07:05:47.1563420Z         >>> jacobian_rows = [torch.autograd.grad(y, x, v, retain_graph=True)[0]
2025-07-17T07:05:47.1563490Z         >>>                  for v in I_N.unbind()]
2025-07-17T07:05:47.1563590Z         >>> jacobian = torch.stack(jacobian_rows)
2025-07-17T07:05:47.1563650Z         >>>
2025-07-17T07:05:47.1563730Z         >>> # vectorized gradient computation
2025-07-17T07:05:47.1563780Z         >>> def get_vjp(v):
2025-07-17T07:05:47.1563850Z         >>>     return torch.autograd.grad(y, x, v)
2025-07-17T07:05:47.1563930Z         >>> jacobian = torch.vmap(get_vjp)(I_N)
2025-07-17T07:05:47.1563970Z     
2025-07-17T07:05:47.1564130Z     :func:`vmap` can also be nested, producing an output with multiple batched dimensions
2025-07-17T07:05:47.1564170Z     
2025-07-17T07:05:47.1564230Z         >>> torch.dot  # [D], [D] -> []
2025-07-17T07:05:47.1564290Z         >>> batched_dot = torch.vmap(
2025-07-17T07:05:47.1564350Z         ...     torch.vmap(torch.dot)
2025-07-17T07:05:47.1564420Z         ... )  # [N1, N0, D], [N1, N0, D] -> [N1, N0]
2025-07-17T07:05:47.1564510Z         >>> x, y = torch.randn(2, 3, 5), torch.randn(2, 3, 5)
2025-07-17T07:05:47.1564580Z         >>> batched_dot(x, y)  # tensor of size [2, 3]
2025-07-17T07:05:47.1564620Z     
2025-07-17T07:05:47.1564770Z     If the inputs are not batched along the first dimension, ``in_dims`` specifies
2025-07-17T07:05:47.1564860Z     the dimension that each inputs are batched along as
2025-07-17T07:05:47.1564900Z     
2025-07-17T07:05:47.1564950Z         >>> torch.dot  # [N], [N] -> []
2025-07-17T07:05:47.1565090Z         >>> batched_dot = torch.vmap(torch.dot, in_dims=1)  # [N, D], [N, D] -> [D]
2025-07-17T07:05:47.1565170Z         >>> x, y = torch.randn(2, 5), torch.randn(2, 5)
2025-07-17T07:05:47.1565220Z         >>> batched_dot(
2025-07-17T07:05:47.1565260Z         ...     x, y
2025-07-17T07:05:47.1565380Z         ... )  # output is [5] instead of [2] if batched along the 0th dimension
2025-07-17T07:05:47.1565420Z     
2025-07-17T07:05:47.1565580Z     If there are multiple inputs each of which is batched along different dimensions,
2025-07-17T07:05:47.1565700Z     ``in_dims`` must be a tuple with the batch dimension for each input as
2025-07-17T07:05:47.1565740Z     
2025-07-17T07:05:47.1565800Z         >>> torch.dot  # [D], [D] -> []
2025-07-17T07:05:47.1565940Z         >>> batched_dot = torch.vmap(torch.dot, in_dims=(0, None))  # [N, D], [D] -> [N]
2025-07-17T07:05:47.1566020Z         >>> x, y = torch.randn(2, 5), torch.randn(5)
2025-07-17T07:05:47.1566060Z         >>> batched_dot(
2025-07-17T07:05:47.1566110Z         ...     x, y
2025-07-17T07:05:47.1566230Z         ... )  # second arg doesn't have a batch dim because in_dim[1] was None
2025-07-17T07:05:47.1566270Z     
2025-07-17T07:05:47.1566410Z     If the input is a Python struct, ``in_dims`` must be a tuple containing a struct
2025-07-17T07:05:47.1566470Z     matching the shape of the input:
2025-07-17T07:05:47.1566510Z     
2025-07-17T07:05:47.1566590Z         >>> f = lambda dict: torch.dot(dict["x"], dict["y"])
2025-07-17T07:05:47.1566660Z         >>> x, y = torch.randn(2, 5), torch.randn(5)
2025-07-17T07:05:47.1566720Z         >>> input = {"x": x, "y": y}
2025-07-17T07:05:47.1566830Z         >>> batched_dot = torch.vmap(f, in_dims=({"x": 0, "y": None},))
2025-07-17T07:05:47.1566900Z         >>> batched_dot(input)
2025-07-17T07:05:47.1566950Z     
2025-07-17T07:05:47.1567110Z     By default, the output is batched along the first dimension. However, it can be batched
2025-07-17T07:05:47.1567190Z     along any dimension by using ``out_dims``
2025-07-17T07:05:47.1567260Z     
2025-07-17T07:05:47.1567320Z         >>> f = lambda x: x**2
2025-07-17T07:05:47.1567370Z         >>> x = torch.randn(2, 5)
2025-07-17T07:05:47.1567450Z         >>> batched_pow = torch.vmap(f, out_dims=1)
2025-07-17T07:05:47.1567500Z         >>> batched_pow(x)  # [5, 2]
2025-07-17T07:05:47.1567540Z     
2025-07-17T07:05:47.1567720Z     For any function that uses kwargs, the returned function will not batch the kwargs but will
2025-07-17T07:05:47.1567760Z     accept kwargs
2025-07-17T07:05:47.1567800Z     
2025-07-17T07:05:47.1567860Z         >>> x = torch.randn([2, 5])
2025-07-17T07:05:47.1567920Z         >>> def fn(x, scale=4.):
2025-07-17T07:05:47.1567980Z         >>>   return x * scale
2025-07-17T07:05:47.1568040Z         >>>
2025-07-17T07:05:47.1568110Z         >>> batched_pow = torch.vmap(fn)
2025-07-17T07:05:47.1568200Z         >>> assert torch.allclose(batched_pow(x), x * 4)
2025-07-17T07:05:47.1568330Z         >>> batched_pow(x, scale=x)  # scale is not batched, output has shape [2, 2, 5]
2025-07-17T07:05:47.1568370Z     
2025-07-17T07:05:47.1568420Z     .. note::
2025-07-17T07:05:47.1568550Z         vmap does not provide general autobatching or handle variable-length
2025-07-17T07:05:47.1568610Z         sequences out of the box.
2025-07-17T07:05:47.1568650Z     
2025-07-17T07:05:47.1568800Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1568840Z     
2025-07-17T07:05:47.1568900Z       warnings.warn(msg)
2025-07-17T07:05:47.1568930Z     
2025-07-17T07:05:47.1569060Z --- Parse Warning: 22 / 136 ---
2025-07-17T07:05:47.1569690Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=grad in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_functorch/apis.py line=306.
2025-07-17T07:05:47.1569850Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1569990Z     ``grad`` operator helps computing gradients of ``func`` with respect to the
2025-07-17T07:05:47.1570120Z         input(s) specified by ``argnums``. This operator can be nested to
2025-07-17T07:05:47.1570180Z         compute higher-order gradients.
2025-07-17T07:05:47.1570220Z     
2025-07-17T07:05:47.1570260Z         Args:
2025-07-17T07:05:47.1570390Z             func (Callable): A Python function that takes one or more arguments.
2025-07-17T07:05:47.1570550Z                 Must return a single-element Tensor. If specified ``has_aux`` equals ``True``,
2025-07-17T07:05:47.1570710Z                 function can return a tuple of single-element Tensor and other auxiliary objects:
2025-07-17T07:05:47.1570770Z                 ``(output, aux)``.
2025-07-17T07:05:47.1570940Z             argnums (int or Tuple[int]): Specifies arguments to compute gradients with respect to.
2025-07-17T07:05:47.1571060Z                 ``argnums`` can be single integer or tuple of integers. Default: 0.
2025-07-17T07:05:47.1571190Z             has_aux (bool): Flag indicating that ``func`` returns a tensor and other
2025-07-17T07:05:47.1571300Z                 auxiliary objects: ``(output, aux)``. Default: False.
2025-07-17T07:05:47.1571340Z     
2025-07-17T07:05:47.1571380Z         Returns:
2025-07-17T07:05:47.1571550Z             Function to compute gradients with respect to its inputs. By default, the output of
2025-07-17T07:05:47.1571690Z             the function is the gradient tensor(s) with respect to the first argument.
2025-07-17T07:05:47.1571850Z             If specified ``has_aux`` equals ``True``, tuple of gradients and output auxiliary objects
2025-07-17T07:05:47.1572030Z             is returned. If ``argnums`` is a tuple of integers, a tuple of output gradients with
2025-07-17T07:05:47.1572120Z             respect to each ``argnums`` value is returned.
2025-07-17T07:05:47.1572160Z     
2025-07-17T07:05:47.1572210Z         Example of using ``grad``:
2025-07-17T07:05:47.1572280Z     
2025-07-17T07:05:47.1572330Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1572390Z             >>> from torch.func import grad
2025-07-17T07:05:47.1572450Z             >>> x = torch.randn([])
2025-07-17T07:05:47.1572530Z             >>> cos_x = grad(lambda x: torch.sin(x))(x)
2025-07-17T07:05:47.1572600Z             >>> assert torch.allclose(cos_x, x.cos())
2025-07-17T07:05:47.1572640Z             >>>
2025-07-17T07:05:47.1572710Z             >>> # Second-order gradients
2025-07-17T07:05:47.1572800Z             >>> neg_sin_x = grad(grad(lambda x: torch.sin(x)))(x)
2025-07-17T07:05:47.1572880Z             >>> assert torch.allclose(neg_sin_x, -x.sin())
2025-07-17T07:05:47.1572920Z     
2025-07-17T07:05:47.1573100Z         When composed with ``vmap``, ``grad`` can be used to compute per-sample-gradients:
2025-07-17T07:05:47.1573170Z     
2025-07-17T07:05:47.1573230Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1573300Z             >>> from torch.func import grad, vmap
2025-07-17T07:05:47.1573370Z             >>> batch_size, feature_size = 3, 5
2025-07-17T07:05:47.1573410Z             >>>
2025-07-17T07:05:47.1573480Z             >>> def model(weights, feature_vec):
2025-07-17T07:05:47.1573560Z             >>> # Very simple linear model with activation
2025-07-17T07:05:47.1573630Z             >>>     assert feature_vec.dim() == 1
2025-07-17T07:05:47.1573700Z             >>>     return feature_vec.dot(weights).relu()
2025-07-17T07:05:47.1573740Z             >>>
2025-07-17T07:05:47.1573830Z             >>> def compute_loss(weights, example, target):
2025-07-17T07:05:47.1573890Z             >>>     y = model(weights, example)
2025-07-17T07:05:47.1573980Z             >>>     return ((y - target) ** 2).mean()  # MSELoss
2025-07-17T07:05:47.1574020Z             >>>
2025-07-17T07:05:47.1574130Z             >>> weights = torch.randn(feature_size, requires_grad=True)
2025-07-17T07:05:47.1574220Z             >>> examples = torch.randn(batch_size, feature_size)
2025-07-17T07:05:47.1574290Z             >>> targets = torch.randn(batch_size)
2025-07-17T07:05:47.1574370Z             >>> inputs = (weights, examples, targets)
2025-07-17T07:05:47.1574510Z             >>> grad_weight_per_example = vmap(grad(compute_loss), in_dims=(None, 0, 0))(
2025-07-17T07:05:47.1574560Z             ...     *inputs
2025-07-17T07:05:47.1574600Z             ... )
2025-07-17T07:05:47.1574640Z     
2025-07-17T07:05:47.1574750Z         Example of using ``grad`` with ``has_aux`` and ``argnums``:
2025-07-17T07:05:47.1574790Z     
2025-07-17T07:05:47.1574840Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1574900Z             >>> from torch.func import grad
2025-07-17T07:05:47.1574970Z             >>> def my_loss_func(y, y_pred):
2025-07-17T07:05:47.1575050Z             >>>    loss_per_sample = (0.5 * y_pred - y) ** 2
2025-07-17T07:05:47.1575120Z             >>>    loss = loss_per_sample.mean()
2025-07-17T07:05:47.1575200Z             >>>    return loss, (y_pred, loss_per_sample)
2025-07-17T07:05:47.1575240Z             >>>
2025-07-17T07:05:47.1575340Z             >>> fn = grad(my_loss_func, argnums=(0, 1), has_aux=True)
2025-07-17T07:05:47.1575390Z             >>> y_true = torch.rand(4)
2025-07-17T07:05:47.1575470Z             >>> y_preds = torch.rand(4, requires_grad=True)
2025-07-17T07:05:47.1575530Z             >>> out = fn(y_true, y_preds)
2025-07-17T07:05:47.1575690Z             >>> # > output is ((grads w.r.t y_true, grads w.r.t y_preds), (y_pred, loss_per_sample))
2025-07-17T07:05:47.1575730Z     
2025-07-17T07:05:47.1575770Z         .. note::
2025-07-17T07:05:47.1575870Z             Using PyTorch ``torch.no_grad`` together with ``grad``.
2025-07-17T07:05:47.1575910Z     
2025-07-17T07:05:47.1576010Z             Case 1: Using ``torch.no_grad`` inside a function:
2025-07-17T07:05:47.1576050Z     
2025-07-17T07:05:47.1576120Z                 >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1576180Z                 >>> def f(x):
2025-07-17T07:05:47.1576240Z                 >>>     with torch.no_grad():
2025-07-17T07:05:47.1576310Z                 >>>         c = x ** 2
2025-07-17T07:05:47.1576370Z                 >>>     return x - c
2025-07-17T07:05:47.1576410Z     
2025-07-17T07:05:47.1576530Z             In this case, ``grad(f)(x)`` will respect the inner ``torch.no_grad``.
2025-07-17T07:05:47.1576570Z     
2025-07-17T07:05:47.1576680Z             Case 2: Using ``grad`` inside ``torch.no_grad`` context manager:
2025-07-17T07:05:47.1576720Z     
2025-07-17T07:05:47.1576780Z                 >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1576840Z                 >>> with torch.no_grad():
2025-07-17T07:05:47.1576890Z                 >>>     grad(f)(x)
2025-07-17T07:05:47.1576930Z     
2025-07-17T07:05:47.1577080Z             In this case, ``grad`` will respect the inner ``torch.no_grad``, but not the
2025-07-17T07:05:47.1577240Z             outer one. This is because ``grad`` is a "function transform": its result
2025-07-17T07:05:47.1577370Z             should not depend on the result of a context manager outside of ``f``.
2025-07-17T07:05:47.1577420Z     
2025-07-17T07:05:47.1577460Z         
2025-07-17T07:05:47.1577610Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1577650Z     
2025-07-17T07:05:47.1577700Z       warnings.warn(msg)
2025-07-17T07:05:47.1577740Z     
2025-07-17T07:05:47.1577840Z --- Parse Warning: 23 / 136 ---
2025-07-17T07:05:47.1578520Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=print_assert_equal in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=286.
2025-07-17T07:05:47.1578680Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1578720Z     
2025-07-17T07:05:47.1578850Z     Test if two objects are equal, and print an error message if test fails.
2025-07-17T07:05:47.1578900Z     
2025-07-17T07:05:47.1578990Z     The test is performed with ``actual == desired``.
2025-07-17T07:05:47.1579030Z     
2025-07-17T07:05:47.1579070Z     Parameters
2025-07-17T07:05:47.1579120Z     ----------
2025-07-17T07:05:47.1579160Z     test_string : str
2025-07-17T07:05:47.1579230Z         The message supplied to AssertionError.
2025-07-17T07:05:47.1579280Z     actual : object
2025-07-17T07:05:47.1579370Z         The object to test for equality against `desired`.
2025-07-17T07:05:47.1579410Z     desired : object
2025-07-17T07:05:47.1579470Z         The expected result.
2025-07-17T07:05:47.1579510Z     
2025-07-17T07:05:47.1579550Z     Examples
2025-07-17T07:05:47.1579600Z     --------
2025-07-17T07:05:47.1579660Z     >>> np.testing.print_assert_equal(
2025-07-17T07:05:47.1579730Z     ...     "Test XYZ of func xyz", [0, 1], [0, 1]
2025-07-17T07:05:47.1579780Z     ... )  # doctest: +SKIP
2025-07-17T07:05:47.1579850Z     >>> np.testing.print_assert_equal(
2025-07-17T07:05:47.1579910Z     ...     "Test XYZ of func xyz", [0, 1], [0, 2]
2025-07-17T07:05:47.1579970Z     ... )  # doctest: +SKIP
2025-07-17T07:05:47.1580030Z     Traceback (most recent call last):
2025-07-17T07:05:47.1580070Z     ...
2025-07-17T07:05:47.1580140Z     AssertionError: Test XYZ of func xyz failed
2025-07-17T07:05:47.1580180Z     ACTUAL:
2025-07-17T07:05:47.1580230Z     [0, 1]
2025-07-17T07:05:47.1580270Z     DESIRED:
2025-07-17T07:05:47.1580310Z     [0, 2]
2025-07-17T07:05:47.1580350Z     
2025-07-17T07:05:47.1580390Z     
2025-07-17T07:05:47.1580540Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1580590Z     
2025-07-17T07:05:47.1580640Z       warnings.warn(msg)
2025-07-17T07:05:47.1580670Z     
2025-07-17T07:05:47.1580770Z --- Parse Warning: 24 / 136 ---
2025-07-17T07:05:47.1581470Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_almost_equal in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=331.
2025-07-17T07:05:47.1581640Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1581680Z     
2025-07-17T07:05:47.1581810Z     Raises an AssertionError if two items are not equal up to desired
2025-07-17T07:05:47.1581850Z     precision.
2025-07-17T07:05:47.1581890Z     
2025-07-17T07:05:47.1581990Z     .. note:: It is recommended to use one of `assert_allclose`,
2025-07-17T07:05:47.1582110Z               `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
2025-07-17T07:05:47.1582220Z               instead of this function for more consistent floating point
2025-07-17T07:05:47.1582290Z               comparisons.
2025-07-17T07:05:47.1582350Z     
2025-07-17T07:05:47.1582480Z     The test verifies that the elements of `actual` and `desired` satisfy.
2025-07-17T07:05:47.1582520Z     
2025-07-17T07:05:47.1582620Z         ``abs(desired-actual) < float64(1.5 * 10**(-decimal))``
2025-07-17T07:05:47.1582660Z     
2025-07-17T07:05:47.1582800Z     That is a looser test than originally documented, but agrees with what the
2025-07-17T07:05:47.1582940Z     actual implementation in `assert_array_almost_equal` did up to rounding
2025-07-17T07:05:47.1583080Z     vagaries. An exception is raised at conflicting values. For ndarrays this
2025-07-17T07:05:47.1583140Z     delegates to assert_array_almost_equal
2025-07-17T07:05:47.1583190Z     
2025-07-17T07:05:47.1583230Z     Parameters
2025-07-17T07:05:47.1583270Z     ----------
2025-07-17T07:05:47.1583320Z     actual : array_like
2025-07-17T07:05:47.1583370Z         The object to check.
2025-07-17T07:05:47.1583420Z     desired : array_like
2025-07-17T07:05:47.1583480Z         The expected object.
2025-07-17T07:05:47.1583540Z     decimal : int, optional
2025-07-17T07:05:47.1583600Z         Desired precision, default is 7.
2025-07-17T07:05:47.1583650Z     err_msg : str, optional
2025-07-17T07:05:47.1583740Z         The error message to be printed in case of failure.
2025-07-17T07:05:47.1583790Z     verbose : bool, optional
2025-07-17T07:05:47.1583920Z         If True, the conflicting values are appended to the error message.
2025-07-17T07:05:47.1583960Z     
2025-07-17T07:05:47.1584000Z     Raises
2025-07-17T07:05:47.1584040Z     ------
2025-07-17T07:05:47.1584090Z     AssertionError
2025-07-17T07:05:47.1584200Z       If actual and desired are not equal up to specified precision.
2025-07-17T07:05:47.1584250Z     
2025-07-17T07:05:47.1584290Z     See Also
2025-07-17T07:05:47.1584330Z     --------
2025-07-17T07:05:47.1584470Z     assert_allclose: Compare two array_like objects for equality with desired
2025-07-17T07:05:47.1584550Z                      relative and/or absolute precision.
2025-07-17T07:05:47.1584680Z     assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-07-17T07:05:47.1584720Z     
2025-07-17T07:05:47.1584760Z     Examples
2025-07-17T07:05:47.1584800Z     --------
2025-07-17T07:05:47.1584900Z     >>> from torch._numpy.testing import assert_almost_equal
2025-07-17T07:05:47.1584980Z     >>> assert_almost_equal(2.3333333333333, 2.33333334)
2025-07-17T07:05:47.1585090Z     >>> assert_almost_equal(2.3333333333333, 2.33333334, decimal=10)
2025-07-17T07:05:47.1585150Z     Traceback (most recent call last):
2025-07-17T07:05:47.1585190Z         ...
2025-07-17T07:05:47.1585240Z     AssertionError:
2025-07-17T07:05:47.1585310Z     Arrays are not almost equal to 10 decimals
2025-07-17T07:05:47.1585360Z      ACTUAL: 2.3333333333333
2025-07-17T07:05:47.1585410Z      DESIRED: 2.33333334
2025-07-17T07:05:47.1585450Z     
2025-07-17T07:05:47.1585500Z     >>> assert_almost_equal(
2025-07-17T07:05:47.1585620Z     ...     np.array([1.0, 2.3333333333333]), np.array([1.0, 2.33333334]), decimal=9
2025-07-17T07:05:47.1585660Z     ... )
2025-07-17T07:05:47.1585750Z     Traceback (most recent call last):
2025-07-17T07:05:47.1585790Z         ...
2025-07-17T07:05:47.1585840Z     AssertionError:
2025-07-17T07:05:47.1585910Z     Arrays are not almost equal to 9 decimals
2025-07-17T07:05:47.1585980Z     <BLANKLINE>
2025-07-17T07:05:47.1586040Z     Mismatched elements: 1 / 2 (50%)
2025-07-17T07:05:47.1586110Z     Max absolute difference: 6.666699636781459e-09
2025-07-17T07:05:47.1586190Z     Max relative difference: 2.8571569790287484e-09
2025-07-17T07:05:47.1586270Z      x: torch.ndarray([1.0000, 2.3333], dtype=float64)
2025-07-17T07:05:47.1586350Z      y: torch.ndarray([1.0000, 2.3333], dtype=float64)
2025-07-17T07:05:47.1586390Z     
2025-07-17T07:05:47.1586430Z     
2025-07-17T07:05:47.1586580Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1586630Z     
2025-07-17T07:05:47.1586670Z       warnings.warn(msg)
2025-07-17T07:05:47.1586730Z     
2025-07-17T07:05:47.1586850Z --- Parse Warning: 25 / 136 ---
2025-07-17T07:05:47.1587520Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_approx_equal in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=457.
2025-07-17T07:05:47.1587680Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1587720Z     
2025-07-17T07:05:47.1587850Z     Raises an AssertionError if two items are not equal up to significant
2025-07-17T07:05:47.1587890Z     digits.
2025-07-17T07:05:47.1587930Z     
2025-07-17T07:05:47.1588030Z     .. note:: It is recommended to use one of `assert_allclose`,
2025-07-17T07:05:47.1588140Z               `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
2025-07-17T07:05:47.1588250Z               instead of this function for more consistent floating point
2025-07-17T07:05:47.1588300Z               comparisons.
2025-07-17T07:05:47.1588340Z     
2025-07-17T07:05:47.1588450Z     Given two numbers, check that they are approximately equal.
2025-07-17T07:05:47.1588580Z     Approximately equal is defined as the number of significant digits
2025-07-17T07:05:47.1588630Z     that agree.
2025-07-17T07:05:47.1588670Z     
2025-07-17T07:05:47.1588720Z     Parameters
2025-07-17T07:05:47.1588760Z     ----------
2025-07-17T07:05:47.1588800Z     actual : scalar
2025-07-17T07:05:47.1588850Z         The object to check.
2025-07-17T07:05:47.1588900Z     desired : scalar
2025-07-17T07:05:47.1588950Z         The expected object.
2025-07-17T07:05:47.1589010Z     significant : int, optional
2025-07-17T07:05:47.1589070Z         Desired precision, default is 7.
2025-07-17T07:05:47.1589120Z     err_msg : str, optional
2025-07-17T07:05:47.1589210Z         The error message to be printed in case of failure.
2025-07-17T07:05:47.1589270Z     verbose : bool, optional
2025-07-17T07:05:47.1589390Z         If True, the conflicting values are appended to the error message.
2025-07-17T07:05:47.1589430Z     
2025-07-17T07:05:47.1589470Z     Raises
2025-07-17T07:05:47.1589510Z     ------
2025-07-17T07:05:47.1589560Z     AssertionError
2025-07-17T07:05:47.1589680Z       If actual and desired are not equal up to specified precision.
2025-07-17T07:05:47.1589710Z     
2025-07-17T07:05:47.1589760Z     See Also
2025-07-17T07:05:47.1589800Z     --------
2025-07-17T07:05:47.1589940Z     assert_allclose: Compare two array_like objects for equality with desired
2025-07-17T07:05:47.1590010Z                      relative and/or absolute precision.
2025-07-17T07:05:47.1590140Z     assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-07-17T07:05:47.1590180Z     
2025-07-17T07:05:47.1590220Z     Examples
2025-07-17T07:05:47.1590260Z     --------
2025-07-17T07:05:47.1590320Z     >>> np.testing.assert_approx_equal(
2025-07-17T07:05:47.1590390Z     ...     0.12345677777777e-20, 0.1234567e-20
2025-07-17T07:05:47.1590460Z     ... )  # doctest: +SKIP
2025-07-17T07:05:47.1590530Z     >>> np.testing.assert_approx_equal(
2025-07-17T07:05:47.1590570Z     ...     0.12345670e-20,
2025-07-17T07:05:47.1590640Z     ...     0.12345671e-20,  # doctest: +SKIP
2025-07-17T07:05:47.1590710Z     ...     significant=8,
2025-07-17T07:05:47.1590750Z     ... )
2025-07-17T07:05:47.1590810Z     >>> np.testing.assert_approx_equal(
2025-07-17T07:05:47.1590860Z     ...     0.12345670e-20,
2025-07-17T07:05:47.1590920Z     ...     0.12345672e-20,  # doctest: +SKIP
2025-07-17T07:05:47.1590970Z     ...     significant=8,
2025-07-17T07:05:47.1591010Z     ... )
2025-07-17T07:05:47.1591070Z     Traceback (most recent call last):
2025-07-17T07:05:47.1591110Z         ...
2025-07-17T07:05:47.1591160Z     AssertionError:
2025-07-17T07:05:47.1591230Z     Items are not equal to 8 significant digits:
2025-07-17T07:05:47.1591280Z      ACTUAL: 1.234567e-21
2025-07-17T07:05:47.1591360Z      DESIRED: 1.2345672e-21
2025-07-17T07:05:47.1591430Z     
2025-07-17T07:05:47.1591530Z     the evaluated condition that raises the exception is
2025-07-17T07:05:47.1591570Z     
2025-07-17T07:05:47.1591690Z     >>> abs(0.12345670e-20 / 1e-21 - 0.12345672e-20 / 1e-21) >= 10 ** -(8 - 1)
2025-07-17T07:05:47.1591730Z     True
2025-07-17T07:05:47.1591770Z     
2025-07-17T07:05:47.1591810Z     
2025-07-17T07:05:47.1591960Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1592000Z     
2025-07-17T07:05:47.1592050Z       warnings.warn(msg)
2025-07-17T07:05:47.1592090Z     
2025-07-17T07:05:47.1592180Z --- Parse Warning: 26 / 136 ---
2025-07-17T07:05:47.1592850Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_array_equal in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=744.
2025-07-17T07:05:47.1593010Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1593050Z     
2025-07-17T07:05:47.1593170Z     Raises an AssertionError if two array_like objects are not equal.
2025-07-17T07:05:47.1593210Z     
2025-07-17T07:05:47.1593340Z     Given two array_like objects, check that the shape is equal and all
2025-07-17T07:05:47.1593470Z     elements of these objects are equal (but see the Notes for the special
2025-07-17T07:05:47.1593590Z     handling of a scalar). An exception is raised at shape mismatch or
2025-07-17T07:05:47.1593720Z     conflicting values. In contrast to the standard usage in numpy, NaNs
2025-07-17T07:05:47.1593900Z     are compared like numbers, no assertion is raised if both objects have
2025-07-17T07:05:47.1593960Z     NaNs in the same positions.
2025-07-17T07:05:47.1594000Z     
2025-07-17T07:05:47.1594130Z     The usual caution for verifying equality with floating point numbers is
2025-07-17T07:05:47.1594180Z     advised.
2025-07-17T07:05:47.1594220Z     
2025-07-17T07:05:47.1594260Z     Parameters
2025-07-17T07:05:47.1594310Z     ----------
2025-07-17T07:05:47.1594350Z     x : array_like
2025-07-17T07:05:47.1594410Z         The actual object to check.
2025-07-17T07:05:47.1594450Z     y : array_like
2025-07-17T07:05:47.1594510Z         The desired, expected object.
2025-07-17T07:05:47.1594560Z     err_msg : str, optional
2025-07-17T07:05:47.1594660Z         The error message to be printed in case of failure.
2025-07-17T07:05:47.1594710Z     verbose : bool, optional
2025-07-17T07:05:47.1594830Z         If True, the conflicting values are appended to the error message.
2025-07-17T07:05:47.1594890Z     strict : bool, optional
2025-07-17T07:05:47.1595010Z         If True, raise an AssertionError when either the shape or the data
2025-07-17T07:05:47.1595110Z         type of the array_like objects does not match. The special
2025-07-17T07:05:47.1595230Z         handling for scalars mentioned in the Notes section is disabled.
2025-07-17T07:05:47.1595270Z     
2025-07-17T07:05:47.1595320Z     Raises
2025-07-17T07:05:47.1595380Z     ------
2025-07-17T07:05:47.1595430Z     AssertionError
2025-07-17T07:05:47.1595510Z         If actual and desired objects are not equal.
2025-07-17T07:05:47.1595550Z     
2025-07-17T07:05:47.1595620Z     See Also
2025-07-17T07:05:47.1595660Z     --------
2025-07-17T07:05:47.1595800Z     assert_allclose: Compare two array_like objects for equality with desired
2025-07-17T07:05:47.1595870Z                      relative and/or absolute precision.
2025-07-17T07:05:47.1596000Z     assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-07-17T07:05:47.1596040Z     
2025-07-17T07:05:47.1596080Z     Notes
2025-07-17T07:05:47.1596120Z     -----
2025-07-17T07:05:47.1596230Z     When one of `x` and `y` is a scalar and the other is array_like, the
2025-07-17T07:05:47.1596360Z     function checks that each element of the array_like object is equal to
2025-07-17T07:05:47.1596520Z     the scalar. This behaviour can be disabled with the `strict` parameter.
2025-07-17T07:05:47.1596580Z     
2025-07-17T07:05:47.1596620Z     Examples
2025-07-17T07:05:47.1596660Z     --------
2025-07-17T07:05:47.1596740Z     The first assert does not raise an exception:
2025-07-17T07:05:47.1596780Z     
2025-07-17T07:05:47.1596850Z     >>> np.testing.assert_array_equal(
2025-07-17T07:05:47.1596940Z     ...     [1.0, 2.33333, np.nan], [np.exp(0), 2.33333, np.nan]
2025-07-17T07:05:47.1596980Z     ... )
2025-07-17T07:05:47.1597020Z     
2025-07-17T07:05:47.1597150Z     Use `assert_allclose` or one of the nulp (number of floating point values)
2025-07-17T07:05:47.1597210Z     functions for these cases instead:
2025-07-17T07:05:47.1597250Z     
2025-07-17T07:05:47.1597310Z     >>> np.testing.assert_allclose(
2025-07-17T07:05:47.1597430Z     ...     [1.0, np.pi, np.nan], [1, np.sqrt(np.pi) ** 2, np.nan], rtol=1e-10, atol=0
2025-07-17T07:05:47.1597470Z     ... )
2025-07-17T07:05:47.1597510Z     
2025-07-17T07:05:47.1597640Z     As mentioned in the Notes section, `assert_array_equal` has special
2025-07-17T07:05:47.1597780Z     handling for scalars. Here the test checks that each value in `x` is 3:
2025-07-17T07:05:47.1597810Z     
2025-07-17T07:05:47.1597880Z     >>> x = np.full((2, 5), fill_value=3)
2025-07-17T07:05:47.1597940Z     >>> np.testing.assert_array_equal(x, 3)
2025-07-17T07:05:47.1597990Z     
2025-07-17T07:05:47.1598110Z     Use `strict` to raise an AssertionError when comparing a scalar with an
2025-07-17T07:05:47.1598160Z     array:
2025-07-17T07:05:47.1598190Z     
2025-07-17T07:05:47.1598280Z     >>> np.testing.assert_array_equal(x, 3, strict=True)
2025-07-17T07:05:47.1598340Z     Traceback (most recent call last):
2025-07-17T07:05:47.1598380Z         ...
2025-07-17T07:05:47.1598430Z     AssertionError:
2025-07-17T07:05:47.1598480Z     Arrays are not equal
2025-07-17T07:05:47.1598530Z     <BLANKLINE>
2025-07-17T07:05:47.1598580Z     (shapes (2, 5), () mismatch)
2025-07-17T07:05:47.1598640Z      x: torch.ndarray([[3, 3, 3, 3, 3],
2025-07-17T07:05:47.1598690Z             [3, 3, 3, 3, 3]])
2025-07-17T07:05:47.1598740Z      y: torch.ndarray(3)
2025-07-17T07:05:47.1598780Z     
2025-07-17T07:05:47.1598910Z     The `strict` parameter also ensures that the array data types match:
2025-07-17T07:05:47.1598950Z     
2025-07-17T07:05:47.1599010Z     >>> x = np.array([2, 2, 2])
2025-07-17T07:05:47.1599080Z     >>> y = np.array([2.0, 2.0, 2.0], dtype=np.float32)
2025-07-17T07:05:47.1599170Z     >>> np.testing.assert_array_equal(x, y, strict=True)
2025-07-17T07:05:47.1599230Z     Traceback (most recent call last):
2025-07-17T07:05:47.1599270Z         ...
2025-07-17T07:05:47.1599320Z     AssertionError:
2025-07-17T07:05:47.1599370Z     Arrays are not equal
2025-07-17T07:05:47.1599410Z     <BLANKLINE>
2025-07-17T07:05:47.1599500Z     (dtypes dtype("int64"), dtype("float32") mismatch)
2025-07-17T07:05:47.1599560Z      x: torch.ndarray([2, 2, 2])
2025-07-17T07:05:47.1599610Z      y: torch.ndarray([2., 2., 2.])
2025-07-17T07:05:47.1599650Z     
2025-07-17T07:05:47.1599830Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1599870Z     
2025-07-17T07:05:47.1599920Z       warnings.warn(msg)
2025-07-17T07:05:47.1599960Z     
2025-07-17T07:05:47.1600060Z --- Parse Warning: 27 / 136 ---
2025-07-17T07:05:47.1600760Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_array_almost_equal in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=851.
2025-07-17T07:05:47.1600920Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1600960Z     
2025-07-17T07:05:47.1601090Z     Raises an AssertionError if two objects are not equal up to desired
2025-07-17T07:05:47.1601130Z     precision.
2025-07-17T07:05:47.1601170Z     
2025-07-17T07:05:47.1601290Z     .. note:: It is recommended to use one of `assert_allclose`,
2025-07-17T07:05:47.1601430Z               `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
2025-07-17T07:05:47.1601540Z               instead of this function for more consistent floating point
2025-07-17T07:05:47.1601590Z               comparisons.
2025-07-17T07:05:47.1601630Z     
2025-07-17T07:05:47.1601770Z     The test verifies identical shapes and that the elements of ``actual`` and
2025-07-17T07:05:47.1601820Z     ``desired`` satisfy.
2025-07-17T07:05:47.1601860Z     
2025-07-17T07:05:47.1601940Z         ``abs(desired-actual) < 1.5 * 10**(-decimal)``
2025-07-17T07:05:47.1601980Z     
2025-07-17T07:05:47.1602120Z     That is a looser test than originally documented, but agrees with what the
2025-07-17T07:05:47.1602260Z     actual implementation did up to rounding vagaries. An exception is raised
2025-07-17T07:05:47.1602400Z     at shape mismatch or conflicting values. In contrast to the standard usage
2025-07-17T07:05:47.1602530Z     in numpy, NaNs are compared like numbers, no assertion is raised if both
2025-07-17T07:05:47.1602600Z     objects have NaNs in the same positions.
2025-07-17T07:05:47.1602640Z     
2025-07-17T07:05:47.1602680Z     Parameters
2025-07-17T07:05:47.1602730Z     ----------
2025-07-17T07:05:47.1602770Z     x : array_like
2025-07-17T07:05:47.1602830Z         The actual object to check.
2025-07-17T07:05:47.1602870Z     y : array_like
2025-07-17T07:05:47.1602930Z         The desired, expected object.
2025-07-17T07:05:47.1602980Z     decimal : int, optional
2025-07-17T07:05:47.1603050Z         Desired precision, default is 6.
2025-07-17T07:05:47.1603100Z     err_msg : str, optional
2025-07-17T07:05:47.1603190Z       The error message to be printed in case of failure.
2025-07-17T07:05:47.1603250Z     verbose : bool, optional
2025-07-17T07:05:47.1603370Z         If True, the conflicting values are appended to the error message.
2025-07-17T07:05:47.1603410Z     
2025-07-17T07:05:47.1603450Z     Raises
2025-07-17T07:05:47.1603490Z     ------
2025-07-17T07:05:47.1603530Z     AssertionError
2025-07-17T07:05:47.1603660Z         If actual and desired are not equal up to specified precision.
2025-07-17T07:05:47.1603700Z     
2025-07-17T07:05:47.1607070Z     See Also
2025-07-17T07:05:47.1607130Z     --------
2025-07-17T07:05:47.1607290Z     assert_allclose: Compare two array_like objects for equality with desired
2025-07-17T07:05:47.1607370Z                      relative and/or absolute precision.
2025-07-17T07:05:47.1607490Z     assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
2025-07-17T07:05:47.1607530Z     
2025-07-17T07:05:47.1607580Z     Examples
2025-07-17T07:05:47.1607620Z     --------
2025-07-17T07:05:47.1607700Z     the first assert does not raise an exception
2025-07-17T07:05:47.1607730Z     
2025-07-17T07:05:47.1607890Z     >>> np.testing.assert_array_almost_equal([1.0, 2.333, np.nan], [1.0, 2.333, np.nan])
2025-07-17T07:05:47.1607930Z     
2025-07-17T07:05:47.1608000Z     >>> np.testing.assert_array_almost_equal(
2025-07-17T07:05:47.1608090Z     ...     [1.0, 2.33333, np.nan], [1.0, 2.33339, np.nan], decimal=5
2025-07-17T07:05:47.1608220Z     ... )
2025-07-17T07:05:47.1608280Z     Traceback (most recent call last):
2025-07-17T07:05:47.1608320Z         ...
2025-07-17T07:05:47.1608370Z     AssertionError:
2025-07-17T07:05:47.1608470Z     Arrays are not almost equal to 5 decimals
2025-07-17T07:05:47.1608520Z     <BLANKLINE>
2025-07-17T07:05:47.1608580Z     Mismatched elements: 1 / 3 (33.3%)
2025-07-17T07:05:47.1608650Z     Max absolute difference: 5.999999999994898e-05
2025-07-17T07:05:47.1608730Z     Max relative difference: 2.5713661239633743e-05
2025-07-17T07:05:47.1608820Z      x: torch.ndarray([1.0000, 2.3333,    nan], dtype=float64)
2025-07-17T07:05:47.1608920Z      y: torch.ndarray([1.0000, 2.3334,    nan], dtype=float64)
2025-07-17T07:05:47.1608960Z     
2025-07-17T07:05:47.1609030Z     >>> np.testing.assert_array_almost_equal(
2025-07-17T07:05:47.1609110Z     ...     [1.0, 2.33333, np.nan], [1.0, 2.33333, 5], decimal=5
2025-07-17T07:05:47.1609170Z     ... )
2025-07-17T07:05:47.1609250Z     Traceback (most recent call last):
2025-07-17T07:05:47.1609290Z         ...
2025-07-17T07:05:47.1609340Z     AssertionError:
2025-07-17T07:05:47.1609410Z     Arrays are not almost equal to 5 decimals
2025-07-17T07:05:47.1609450Z     <BLANKLINE>
2025-07-17T07:05:47.1609510Z     x and y nan location mismatch:
2025-07-17T07:05:47.1609600Z      x: torch.ndarray([1.0000, 2.3333,    nan], dtype=float64)
2025-07-17T07:05:47.1609700Z      y: torch.ndarray([1.0000, 2.3333, 5.0000], dtype=float64)
2025-07-17T07:05:47.1609730Z     
2025-07-17T07:05:47.1609770Z     
2025-07-17T07:05:47.1609920Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1609960Z     
2025-07-17T07:05:47.1610010Z       warnings.warn(msg)
2025-07-17T07:05:47.1610050Z     
2025-07-17T07:05:47.1610170Z --- Parse Warning: 28 / 136 ---
2025-07-17T07:05:47.1610850Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=clear_and_catch_warnings in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_numpy/testing/utils.py line=1848.
2025-07-17T07:05:47.1611010Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1611140Z     Context manager that resets warning registry for catching warnings
2025-07-17T07:05:47.1611180Z     
2025-07-17T07:05:47.1611330Z         Warnings can be slippery, because, whenever a warning is triggered, Python
2025-07-17T07:05:47.1611470Z         adds a ``__warningregistry__`` member to the *calling* module.  This makes
2025-07-17T07:05:47.1611620Z         it impossible to retrigger the warning in this module, whatever you put in
2025-07-17T07:05:47.1611760Z         the warnings filters.  This context manager accepts a sequence of `modules`
2025-07-17T07:05:47.1611850Z         as a keyword argument to its constructor and:
2025-07-17T07:05:47.1611890Z     
2025-07-17T07:05:47.1612030Z         * stores and removes any ``__warningregistry__`` entries in given `modules`
2025-07-17T07:05:47.1612080Z           on entry;
2025-07-17T07:05:47.1612190Z         * resets ``__warningregistry__`` to its previous state on exit.
2025-07-17T07:05:47.1612230Z     
2025-07-17T07:05:47.1612370Z         This makes it possible to trigger any warning afresh inside the context
2025-07-17T07:05:47.1612480Z         manager without disturbing the state of warnings outside.
2025-07-17T07:05:47.1612520Z     
2025-07-17T07:05:47.1612660Z         For compatibility with Python 3.0, please consider all arguments to be
2025-07-17T07:05:47.1612700Z         keyword-only.
2025-07-17T07:05:47.1612740Z     
2025-07-17T07:05:47.1612790Z         Parameters
2025-07-17T07:05:47.1612830Z         ----------
2025-07-17T07:05:47.1612890Z         record : bool, optional
2025-07-17T07:05:47.1613000Z             Specifies whether warnings should be captured by a custom
2025-07-17T07:05:47.1613190Z             implementation of ``warnings.showwarning()`` and be appended to a list
2025-07-17T07:05:47.1613320Z             returned by the context manager. Otherwise None is returned by the
2025-07-17T07:05:47.1613450Z             context manager. The objects appended to the list are arguments whose
2025-07-17T07:05:47.1613580Z             attributes mirror the arguments to ``showwarning()``.
2025-07-17T07:05:47.1613640Z         modules : sequence, optional
2025-07-17T07:05:47.1613770Z             Sequence of modules for which to reset warnings registry on entry and
2025-07-17T07:05:47.1613880Z             restore on exit. To work correctly, all 'ignore' filters should
2025-07-17T07:05:47.1613950Z             filter by one of these modules.
2025-07-17T07:05:47.1613990Z     
2025-07-17T07:05:47.1614030Z         Examples
2025-07-17T07:05:47.1614080Z         --------
2025-07-17T07:05:47.1614130Z         >>> import warnings
2025-07-17T07:05:47.1614270Z         >>> with np.testing.clear_and_catch_warnings(  # doctest: +SKIP
2025-07-17T07:05:47.1614370Z         ...     modules=[np.core.fromnumeric]
2025-07-17T07:05:47.1614410Z         ... ):
2025-07-17T07:05:47.1614480Z         ...     warnings.simplefilter("always")
2025-07-17T07:05:47.1614620Z         ...     warnings.filterwarnings("ignore", module="np.core.fromnumeric")
2025-07-17T07:05:47.1614720Z         ...     # do something that raises a warning but ignore those in
2025-07-17T07:05:47.1614780Z         ...     # np.core.fromnumeric
2025-07-17T07:05:47.1614820Z         
2025-07-17T07:05:47.1614970Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1615010Z     
2025-07-17T07:05:47.1615060Z       warnings.warn(msg)
2025-07-17T07:05:47.1615100Z     
2025-07-17T07:05:47.1615200Z --- Parse Warning: 29 / 136 ---
2025-07-17T07:05:47.1615830Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=calculate_gain in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/init.py line=142.
2025-07-17T07:05:47.1615990Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1616120Z     Return the recommended gain value for the given nonlinearity function.
2025-07-17T07:05:47.1616170Z     
2025-07-17T07:05:47.1616220Z         The values are as follows:
2025-07-17T07:05:47.1616260Z     
2025-07-17T07:05:47.1616340Z         ================= ====================================================
2025-07-17T07:05:47.1616390Z         nonlinearity      gain
2025-07-17T07:05:47.1616460Z         ================= ====================================================
2025-07-17T07:05:47.1616520Z         Linear / Identity :math:`1`
2025-07-17T07:05:47.1616570Z         Conv{1,2,3}D      :math:`1`
2025-07-17T07:05:47.1616630Z         Sigmoid           :math:`1`
2025-07-17T07:05:47.1616690Z         Tanh              :math:`\frac{5}{3}`
2025-07-17T07:05:47.1616750Z         ReLU              :math:`\sqrt{2}`
2025-07-17T07:05:47.1616870Z         Leaky Relu        :math:`\sqrt{\frac{2}{1 + \text{negative\_slope}^2}}`
2025-07-17T07:05:47.1616930Z         SELU              :math:`\frac{3}{4}`
2025-07-17T07:05:47.1617010Z         ================= ====================================================
2025-07-17T07:05:47.1617040Z     
2025-07-17T07:05:47.1617090Z         .. warning::
2025-07-17T07:05:47.1617210Z             In order to implement `Self-Normalizing Neural Networks`_ ,
2025-07-17T07:05:47.1617350Z             you should use ``nonlinearity='linear'`` instead of ``nonlinearity='selu'``.
2025-07-17T07:05:47.1617460Z             This gives the initial weights a variance of ``1 / N``,
2025-07-17T07:05:47.1617590Z             which is necessary to induce a stable fixed point in the forward pass.
2025-07-17T07:05:47.1617730Z             In contrast, the default gain for ``SELU`` sacrifices the normalization
2025-07-17T07:05:47.1617840Z             effect for more stable gradient flow in rectangular layers.
2025-07-17T07:05:47.1617900Z     
2025-07-17T07:05:47.1617940Z         Args:
2025-07-17T07:05:47.1618060Z             nonlinearity: the non-linear function (`nn.functional` name)
2025-07-17T07:05:47.1618170Z             param: optional parameter for the non-linear function
2025-07-17T07:05:47.1618230Z     
2025-07-17T07:05:47.1618270Z         Examples:
2025-07-17T07:05:47.1618340Z             >>> gain = nn.init.calculate_gain(
2025-07-17T07:05:47.1618400Z             ...     "leaky_relu", 0.2
2025-07-17T07:05:47.1618470Z             ... )  # leaky_relu with negative_slope=0.2
2025-07-17T07:05:47.1618510Z     
2025-07-17T07:05:47.1618800Z         .. _Self-Normalizing Neural Networks: https://papers.nips.cc/paper/2017/hash/5d44ee6f2c3f71b73125876103c8f6c4-Abstract.html
2025-07-17T07:05:47.1618840Z         
2025-07-17T07:05:47.1618990Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1619050Z     
2025-07-17T07:05:47.1619120Z       warnings.warn(msg)
2025-07-17T07:05:47.1619170Z     
2025-07-17T07:05:47.1619260Z --- Parse Warning: 30 / 136 ---
2025-07-17T07:05:47.1619980Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedDataParallel.join in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py line=1766.
2025-07-17T07:05:47.1620140Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1620180Z     
2025-07-17T07:05:47.1620320Z     Context manager for training with uneven inputs across processes in DDP.
2025-07-17T07:05:47.1620360Z     
2025-07-17T07:05:47.1620490Z     This context manager will keep track of already-joined DDP processes,
2025-07-17T07:05:47.1620610Z     and "shadow" the forward and backward passes by inserting collective
2025-07-17T07:05:47.1620750Z     communication operations to match with the ones created by non-joined
2025-07-17T07:05:47.1620890Z     DDP processes. This will ensure each collective call has a corresponding
2025-07-17T07:05:47.1621020Z     call by already-joined DDP processes, preventing hangs or errors that
2025-07-17T07:05:47.1621140Z     would otherwise happen when training with uneven inputs across
2025-07-17T07:05:47.1621280Z     processes. Alternatively, if the flag ``throw_on_early_termination`` is
2025-07-17T07:05:47.1621400Z     specified to be ``True``, all trainers will throw an error once one rank
2025-07-17T07:05:47.1621520Z     runs out of inputs, allowing these errors to be caught and handled
2025-07-17T07:05:47.1621580Z     according to application logic.
2025-07-17T07:05:47.1621620Z     
2025-07-17T07:05:47.1621750Z     Once all DDP processes have joined, the context manager will broadcast
2025-07-17T07:05:47.1621880Z     the model corresponding to the last joined process to all processes to
2025-07-17T07:05:47.1621970Z     ensure the model is the same across all processes
2025-07-17T07:05:47.1622030Z     (which is guaranteed by DDP).
2025-07-17T07:05:47.1622070Z     
2025-07-17T07:05:47.1622200Z     To use this to enable training with uneven inputs across processes,
2025-07-17T07:05:47.1622330Z     simply wrap this context manager around your training loop. No further
2025-07-17T07:05:47.1622430Z     modifications to the model or data loading is required.
2025-07-17T07:05:47.1622470Z     
2025-07-17T07:05:47.1622520Z     .. warning::
2025-07-17T07:05:47.1622640Z         If the model or training loop this context manager is wrapped around
2025-07-17T07:05:47.1622750Z         has additional distributed collective operations, such as
2025-07-17T07:05:47.1622870Z         ``SyncBatchNorm`` in the model's forward pass, then the flag
2025-07-17T07:05:47.1622990Z         ``throw_on_early_termination`` must be enabled. This is because this
2025-07-17T07:05:47.1623120Z         context manager is not aware of non-DDP collective communication.
2025-07-17T07:05:47.1623250Z         This flag will cause all ranks to throw when any one rank
2025-07-17T07:05:47.1623380Z         exhausts inputs, allowing these errors to be caught and recovered
2025-07-17T07:05:47.1623430Z         from across all ranks.
2025-07-17T07:05:47.1623490Z     
2025-07-17T07:05:47.1623540Z     Args:
2025-07-17T07:05:47.1623650Z         divide_by_initial_world_size (bool): If ``True``, will divide
2025-07-17T07:05:47.1623770Z             gradients by the initial ``world_size`` DDP training was launched
2025-07-17T07:05:47.1623870Z             with. If ``False``, will compute the effective world size
2025-07-17T07:05:47.1623980Z             (number of ranks that have not depleted their inputs yet) and
2025-07-17T07:05:47.1624070Z             divide gradients by that during allreduce. Set
2025-07-17T07:05:47.1624180Z             ``divide_by_initial_world_size=True`` to ensure every input
2025-07-17T07:05:47.1624330Z             sample including the uneven inputs have equal weight in terms of
2025-07-17T07:05:47.1624450Z             how much they contribute to the global gradient. This is
2025-07-17T07:05:47.1624550Z             achieved by always dividing the gradient by the initial
2025-07-17T07:05:47.1624670Z             ``world_size`` even when we encounter uneven inputs. If you set
2025-07-17T07:05:47.1624770Z             this to ``False``, we divide the gradient by the remaining
2025-07-17T07:05:47.1624890Z             number of nodes. This ensures parity with training on a smaller
2025-07-17T07:05:47.1625000Z             ``world_size`` although it also means the uneven inputs would
2025-07-17T07:05:47.1625120Z             contribute more towards the global gradient. Typically, you
2025-07-17T07:05:47.1625230Z             would want to set this to ``True`` for cases where the last few
2025-07-17T07:05:47.1625340Z             inputs of your training job are uneven. In extreme cases, where
2025-07-17T07:05:47.1625460Z             there is a large discrepancy in the number of inputs, setting
2025-07-17T07:05:47.1625550Z             this to ``False`` might provide better results.
2025-07-17T07:05:47.1625670Z         enable (bool): Whether to enable uneven input detection or not. Pass
2025-07-17T07:05:47.1625780Z             in ``enable=False`` to disable in cases where you know that
2025-07-17T07:05:47.1625890Z             inputs are even across participating processes. Default is
2025-07-17T07:05:47.1625940Z             ``True``.
2025-07-17T07:05:47.1626050Z         throw_on_early_termination (bool): Whether to throw an error
2025-07-17T07:05:47.1626150Z             or continue training when at least one rank has exhausted
2025-07-17T07:05:47.1626260Z             inputs. If ``True``, will throw upon the first rank reaching end
2025-07-17T07:05:47.1626370Z             of data. If ``False``, will continue training with a smaller
2025-07-17T07:05:47.1626480Z             effective world size until all ranks are joined. Note that if
2025-07-17T07:05:47.1626560Z             this flag is specified, then the flag
2025-07-17T07:05:47.1626660Z             ``divide_by_initial_world_size`` would be ignored. Default
2025-07-17T07:05:47.1626710Z             is ``False``.
2025-07-17T07:05:47.1626750Z     
2025-07-17T07:05:47.1626790Z     
2025-07-17T07:05:47.1626840Z     Example::
2025-07-17T07:05:47.1626880Z     
2025-07-17T07:05:47.1626950Z         >>> # xdoctest: +SKIP("Distributed")
2025-07-17T07:05:47.1626990Z         >>> import torch
2025-07-17T07:05:47.1627060Z         >>> import torch.distributed as dist
2025-07-17T07:05:47.1627110Z         >>> import os
2025-07-17T07:05:47.1627180Z         >>> import torch.multiprocessing as mp
2025-07-17T07:05:47.1627240Z         >>> import torch.nn as nn
2025-07-17T07:05:47.1627290Z         >>> # On each spawned worker
2025-07-17T07:05:47.1627340Z         >>> def worker(rank):
2025-07-17T07:05:47.1627450Z         >>>     dist.init_process_group("nccl", rank=rank, world_size=2)
2025-07-17T07:05:47.1627510Z         >>>     torch.cuda.set_device(rank)
2025-07-17T07:05:47.1627620Z         >>>     model = nn.Linear(1, 1, bias=False).to(rank)
2025-07-17T07:05:47.1627730Z         >>>     model = torch.nn.parallel.DistributedDataParallel(
2025-07-17T07:05:47.1627810Z         >>>         model, device_ids=[rank], output_device=rank
2025-07-17T07:05:47.1627890Z         >>>     )
2025-07-17T07:05:47.1627970Z         >>>     # Rank 1 gets one more input than rank 0.
2025-07-17T07:05:47.1628080Z         >>>     inputs = [torch.tensor([1]).float() for _ in range(10 + rank)]
2025-07-17T07:05:47.1628130Z         >>>     with model.join():
2025-07-17T07:05:47.1628190Z         >>>         for _ in range(5):
2025-07-17T07:05:47.1628250Z         >>>             for inp in inputs:
2025-07-17T07:05:47.1628320Z         >>>                 loss = model(inp).sum()
2025-07-17T07:05:47.1628380Z         >>>                 loss.backward()
2025-07-17T07:05:47.1628490Z         >>>     # Without the join() API, the below synchronization will hang
2025-07-17T07:05:47.1628600Z         >>>     # blocking for rank 1's allreduce to complete.
2025-07-17T07:05:47.1628690Z         >>>     torch.cuda.synchronize(device=rank)
2025-07-17T07:05:47.1628730Z     
2025-07-17T07:05:47.1628880Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1628920Z     
2025-07-17T07:05:47.1628970Z       warnings.warn(msg)
2025-07-17T07:05:47.1629010Z     
2025-07-17T07:05:47.1629110Z --- Parse Warning: 31 / 136 ---
2025-07-17T07:05:47.1629870Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedDataParallel._register_fused_optim in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/parallel/distributed.py line=2057.
2025-07-17T07:05:47.1630020Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1630060Z     
2025-07-17T07:05:47.1630240Z     Register an optimizer in DDP to optimize parameter immediately after its gradient reduction.
2025-07-17T07:05:47.1630280Z     
2025-07-17T07:05:47.1630400Z     Registers an optimizer with DDP such that the optimization for a
2025-07-17T07:05:47.1630520Z     parameter will run immediately when that parameter's gradient is
2025-07-17T07:05:47.1630640Z     finished with reduction, instead of waiting for all parameters'
2025-07-17T07:05:47.1630760Z     gradients to finish reduction. This can result in a training speedup
2025-07-17T07:05:47.1630890Z     depending on your workload since the optimizer can run while gradient
2025-07-17T07:05:47.1631020Z     reduction for other parameters are still ongoing. In addition, this has
2025-07-17T07:05:47.1631150Z     the potential to reduce peak memory consumption during training, as it
2025-07-17T07:05:47.1631270Z     only needs to load the per-parameter optimizer states of a single
2025-07-17T07:05:47.1631390Z     parameter at a time, instead of loading all per-parameter optimizer
2025-07-17T07:05:47.1631440Z     states at once.
2025-07-17T07:05:47.1631480Z     
2025-07-17T07:05:47.1631520Z     Args:
2025-07-17T07:05:47.1631630Z         optim (Type): a ``torch.optim.Optimizer`` class to be registered
2025-07-17T07:05:47.1631680Z         as a fused optimizer.
2025-07-17T07:05:47.1631780Z         *args (Sequence[Any]): Arguments to forward to `optim`.
2025-07-17T07:05:47.1631910Z         optim_params (Optional[Iterable[torch.Tensor]]): Set of parameters
2025-07-17T07:05:47.1632040Z         to optimize, similar to `params` argument of traditional `torch.optim`
2025-07-17T07:05:47.1632150Z         Optimizers. If this is omitted, all DDP model parameters will be
2025-07-17T07:05:47.1632200Z         optimized.
2025-07-17T07:05:47.1632310Z         **kwargs: (Dict[str, Any]): Keyword arguments to forward to `optim`.
2025-07-17T07:05:47.1632350Z     
2025-07-17T07:05:47.1632390Z     .. warning ::
2025-07-17T07:05:47.1632520Z         _register_fused_optim should only be called once on a DDP instance,
2025-07-17T07:05:47.1632660Z         and registering multiple fused optimizers for the same DDP model
2025-07-17T07:05:47.1632740Z         is not currently supported. Please ping
2025-07-17T07:05:47.1632870Z         https://github.com/pytorch/pytorch/issues/71595 if this is necessary
2025-07-17T07:05:47.1632940Z         for your use case.
2025-07-17T07:05:47.1632980Z     
2025-07-17T07:05:47.1633020Z     .. warning ::
2025-07-17T07:05:47.1633130Z         _register_fused_optim and register_comm_hook currently do not
2025-07-17T07:05:47.1633250Z         compose together, meaning that custom DDP communication hooks are
2025-07-17T07:05:47.1633350Z         not supported with overlapped optimizers. Please ping
2025-07-17T07:05:47.1633480Z         https://github.com/pytorch/pytorch/issues/71595 if this is necessary
2025-07-17T07:05:47.1633530Z         for your use case.
2025-07-17T07:05:47.1633570Z     
2025-07-17T07:05:47.1633620Z     .. warning ::
2025-07-17T07:05:47.1633770Z         Gradient accumulation and DDP `no_sync` are currently not supported
2025-07-17T07:05:47.1633890Z         with overlapped optimizer. Please ping
2025-07-17T07:05:47.1634020Z         https://github.com/pytorch/pytorch/issues/71595 if this is necessary
2025-07-17T07:05:47.1634070Z         for your use case.
2025-07-17T07:05:47.1634110Z     
2025-07-17T07:05:47.1634150Z     Example::
2025-07-17T07:05:47.1634190Z     
2025-07-17T07:05:47.1634260Z         >>> # xdoctest: +SKIP("No rendezvous handler")
2025-07-17T07:05:47.1634430Z         >>> torch.distributed.init_process_group(backend='nccl', world_size=4, init_method='...')
2025-07-17T07:05:47.1634550Z         >>> net = torch.nn.parallel.DistributedDataParallel(model, pg)
2025-07-17T07:05:47.1634600Z         >>> lr = 1e-2
2025-07-17T07:05:47.1634650Z         >>> betas = (0.9, 0.99)
2025-07-17T07:05:47.1634690Z         >>> eps = 1e-6
2025-07-17T07:05:47.1634820Z         >>> net._register_fused_optim(torch.optim.Adam, lr, betas=betas, eps=eps)
2025-07-17T07:05:47.1634890Z         >>> # Example with subset of parameters
2025-07-17T07:05:47.1634970Z         >>> params_to_opt = [list(net.parameters())[0]]
2025-07-17T07:05:47.1635030Z         >>> net._register_fused_optim(
2025-07-17T07:05:47.1635160Z         ...   torch.optim.Adam, lr, optim_params=params_to_opt,  betas=betas, eps=eps
2025-07-17T07:05:47.1635210Z         ... )
2025-07-17T07:05:47.1635240Z     
2025-07-17T07:05:47.1635540Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1635580Z     
2025-07-17T07:05:47.1635630Z       warnings.warn(msg)
2025-07-17T07:05:47.1635670Z     
2025-07-17T07:05:47.1635770Z --- Parse Warning: 32 / 136 ---
2025-07-17T07:05:47.1636460Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_parametrization in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/parametrize.py line=424.
2025-07-17T07:05:47.1636610Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1636710Z     Register a parametrization to a tensor in a module.
2025-07-17T07:05:47.1636750Z     
2025-07-17T07:05:47.1636910Z         Assume that ``tensor_name="weight"`` for simplicity. When accessing ``module.weight``,
2025-07-17T07:05:47.1637080Z         the module will return the parametrized version ``parametrization(module.weight)``.
2025-07-17T07:05:47.1637230Z         If the original tensor requires a gradient, the backward pass will differentiate
2025-07-17T07:05:47.1637390Z         through :attr:`parametrization`, and the optimizer will update the tensor accordingly.
2025-07-17T07:05:47.1637430Z     
2025-07-17T07:05:47.1637610Z         The first time that a module registers a parametrization, this function will add an attribute
2025-07-17T07:05:47.1637750Z         ``parametrizations`` to the module of type :class:`~ParametrizationList`.
2025-07-17T07:05:47.1637790Z     
2025-07-17T07:05:47.1637990Z         The list of parametrizations on the tensor ``weight`` will be accessible under
2025-07-17T07:05:47.1638060Z         ``module.parametrizations.weight``.
2025-07-17T07:05:47.1638100Z     
2025-07-17T07:05:47.1638170Z         The original tensor will be accessible under
2025-07-17T07:05:47.1638310Z         ``module.parametrizations.weight.original``.
2025-07-17T07:05:47.1638350Z     
2025-07-17T07:05:47.1638500Z         Parametrizations may be concatenated by registering several parametrizations
2025-07-17T07:05:47.1638560Z         on the same attribute.
2025-07-17T07:05:47.1638600Z     
2025-07-17T07:05:47.1638730Z         The training mode of a registered parametrization is updated on registration
2025-07-17T07:05:47.1638810Z         to match the training mode of the host module
2025-07-17T07:05:47.1638850Z     
2025-07-17T07:05:47.1639020Z         Parametrized parameters and buffers have an inbuilt caching system that can be activated
2025-07-17T07:05:47.1639120Z         using the context manager :func:`cached`.
2025-07-17T07:05:47.1639170Z     
2025-07-17T07:05:47.1639320Z         A :attr:`parametrization` may optionally implement a method with signature
2025-07-17T07:05:47.1639360Z     
2025-07-17T07:05:47.1639410Z         .. code-block:: python
2025-07-17T07:05:47.1639450Z     
2025-07-17T07:05:47.1639570Z             def right_inverse(self, X: Tensor) -> Union[Tensor, Sequence[Tensor]]
2025-07-17T07:05:47.1639610Z     
2025-07-17T07:05:47.1639760Z         This method is called on the unparametrized tensor when the first parametrization
2025-07-17T07:05:47.1639880Z         is registered to compute the initial value of the original tensor.
2025-07-17T07:05:47.1640060Z         If this method is not implemented, the original tensor will be just the unparametrized tensor.
2025-07-17T07:05:47.1640100Z     
2025-07-17T07:05:47.1640280Z         If all the parametrizations registered on a tensor implement `right_inverse` it is possible
2025-07-17T07:05:47.1640440Z         to initialize a parametrized tensor by assigning to it, as shown in the example below.
2025-07-17T07:05:47.1640480Z     
2025-07-17T07:05:47.1640620Z         It is possible for the first parametrization to depend on several inputs.
2025-07-17T07:05:47.1640750Z         This may be implemented returning a tuple of tensors from ``right_inverse``
2025-07-17T07:05:47.1640890Z         (see the example implementation of a ``RankOne`` parametrization below).
2025-07-17T07:05:47.1640930Z     
2025-07-17T07:05:47.1641130Z         In this case, the unconstrained tensors are also located under ``module.parametrizations.weight``
2025-07-17T07:05:47.1641200Z         with names ``original0``, ``original1``,...
2025-07-17T07:05:47.1641240Z     
2025-07-17T07:05:47.1641280Z         .. note::
2025-07-17T07:05:47.1641320Z     
2025-07-17T07:05:47.1641470Z             If unsafe=False (default) both the forward and right_inverse methods will be called
2025-07-17T07:05:47.1641560Z             once to perform a number of consistency checks.
2025-07-17T07:05:47.1641720Z             If unsafe=True, then right_inverse will be called if the tensor is not parametrized,
2025-07-17T07:05:47.1641790Z             and nothing will be called otherwise.
2025-07-17T07:05:47.1641830Z     
2025-07-17T07:05:47.1641870Z         .. note::
2025-07-17T07:05:47.1641910Z     
2025-07-17T07:05:47.1642020Z             In most situations, ``right_inverse`` will be a function such that
2025-07-17T07:05:47.1642090Z             ``forward(right_inverse(X)) == X`` (see
2025-07-17T07:05:47.1642250Z             `right inverse <https://en.wikipedia.org/wiki/Inverse_function#Right_inverses>`_).
2025-07-17T07:05:47.1642450Z             Sometimes, when the parametrization is not surjective, it may be reasonable
2025-07-17T07:05:47.1642500Z             to relax this.
2025-07-17T07:05:47.1642540Z     
2025-07-17T07:05:47.1642580Z         .. warning::
2025-07-17T07:05:47.1642620Z     
2025-07-17T07:05:47.1642780Z             If a parametrization depends on several inputs, :func:`~register_parametrization`
2025-07-17T07:05:47.1642970Z             will register a number of new parameters. If such parametrization is registered
2025-07-17T07:05:47.1643140Z             after the optimizer is created, these new parameters will need to be added manually
2025-07-17T07:05:47.1643280Z             to the optimizer. See :meth:`torch.Optimizer.add_param_group`.
2025-07-17T07:05:47.1643320Z     
2025-07-17T07:05:47.1643370Z         Args:
2025-07-17T07:05:47.1643490Z             module (nn.Module): module on which to register the parametrization
2025-07-17T07:05:47.1643620Z             tensor_name (str): name of the parameter or buffer on which to register
2025-07-17T07:05:47.1643680Z                 the parametrization
2025-07-17T07:05:47.1643810Z             parametrization (nn.Module): the parametrization to register
2025-07-17T07:05:47.1643850Z         Keyword args:
2025-07-17T07:05:47.1644010Z             unsafe (bool): a boolean flag that denotes whether the parametrization
2025-07-17T07:05:47.1644150Z                 may change the dtype and shape of the tensor. Default: `False`
2025-07-17T07:05:47.1644310Z                 Warning: the parametrization is not checked for consistency upon registration.
2025-07-17T07:05:47.1644380Z                 Enable this flag at your own risk.
2025-07-17T07:05:47.1644420Z     
2025-07-17T07:05:47.1644460Z         Raises:
2025-07-17T07:05:47.1644630Z             ValueError: if the module does not have a parameter or a buffer named :attr:`tensor_name`
2025-07-17T07:05:47.1644670Z     
2025-07-17T07:05:47.1644720Z         Examples:
2025-07-17T07:05:47.1644810Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK)
2025-07-17T07:05:47.1644860Z             >>> import torch
2025-07-17T07:05:47.1644920Z             >>> import torch.nn as nn
2025-07-17T07:05:47.1645000Z             >>> import torch.nn.utils.parametrize as P
2025-07-17T07:05:47.1645040Z             >>>
2025-07-17T07:05:47.1645110Z             >>> class Symmetric(nn.Module):
2025-07-17T07:05:47.1645170Z             >>>     def forward(self, X):
2025-07-17T07:05:47.1645280Z             >>>         return X.triu() + X.triu(1).T  # Return a symmetric matrix
2025-07-17T07:05:47.1645320Z             >>>
2025-07-17T07:05:47.1645380Z             >>>     def right_inverse(self, A):
2025-07-17T07:05:47.1645440Z             >>>         return A.triu()
2025-07-17T07:05:47.1645480Z             >>>
2025-07-17T07:05:47.1645540Z             >>> m = nn.Linear(5, 5)
2025-07-17T07:05:47.1645640Z             >>> P.register_parametrization(m, "weight", Symmetric())
2025-07-17T07:05:47.1645790Z             >>> print(torch.allclose(m.weight, m.weight.T))  # m.weight is now symmetric
2025-07-17T07:05:47.1645830Z             True
2025-07-17T07:05:47.1645880Z             >>> A = torch.rand(5, 5)
2025-07-17T07:05:47.1645950Z             >>> A = A + A.T  # A is now symmetric
2025-07-17T07:05:47.1646070Z             >>> m.weight = A  # Initialize the weight to be the symmetric matrix A
2025-07-17T07:05:47.1646140Z             >>> print(torch.allclose(m.weight, A))
2025-07-17T07:05:47.1646190Z             True
2025-07-17T07:05:47.1646230Z     
2025-07-17T07:05:47.1646290Z             >>> class RankOne(nn.Module):
2025-07-17T07:05:47.1646350Z             >>>     def forward(self, x, y):
2025-07-17T07:05:47.1646440Z             >>> # Form a rank 1 matrix multiplying two vectors
2025-07-17T07:05:47.1646520Z             >>>         return x.unsqueeze(-1) @ y.unsqueeze(-2)
2025-07-17T07:05:47.1646570Z             >>>
2025-07-17T07:05:47.1646630Z             >>>     def right_inverse(self, Z):
2025-07-17T07:05:47.1646700Z             >>> # Project Z onto the rank 1 matrices
2025-07-17T07:05:47.1646800Z             >>>         U, S, Vh = torch.linalg.svd(Z, full_matrices=False)
2025-07-17T07:05:47.1646870Z             >>> # Return rescaled singular vectors
2025-07-17T07:05:47.1646940Z             >>>         s0_sqrt = S[0].sqrt().unsqueeze(-1)
2025-07-17T07:05:47.1647030Z             >>>         return U[..., :, 0] * s0_sqrt, Vh[..., 0, :] * s0_sqrt
2025-07-17T07:05:47.1647100Z             >>>
2025-07-17T07:05:47.1647190Z             >>> linear_rank_one = P.register_parametrization(
2025-07-17T07:05:47.1647270Z             ...     nn.Linear(4, 4), "weight", RankOne()
2025-07-17T07:05:47.1647340Z             ... )
2025-07-17T07:05:47.1647460Z             >>> print(torch.linalg.matrix_rank(linear_rank_one.weight).item())
2025-07-17T07:05:47.1647500Z             1
2025-07-17T07:05:47.1647540Z     
2025-07-17T07:05:47.1647590Z         
2025-07-17T07:05:47.1647740Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1647780Z     
2025-07-17T07:05:47.1647830Z       warnings.warn(msg)
2025-07-17T07:05:47.1647870Z     
2025-07-17T07:05:47.1647970Z --- Parse Warning: 33 / 136 ---
2025-07-17T07:05:47.1648700Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=convert_conv2d_weight_memory_format in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/memory_format.py line=14.
2025-07-17T07:05:47.1648870Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1649010Z     Convert ``memory_format`` of ``nn.Conv2d.weight`` to ``memory_format``.
2025-07-17T07:05:47.1649050Z     
2025-07-17T07:05:47.1649210Z         The conversion recursively applies to nested ``nn.Module``, including ``module``.
2025-07-17T07:05:47.1649370Z         Note that it only changes the memory_format, but not the semantics of each dimensions.
2025-07-17T07:05:47.1649530Z         This function is used to facilitate the computation to adopt NHWC kernels, which
2025-07-17T07:05:47.1649710Z         provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0
2025-07-17T07:05:47.1649750Z     
2025-07-17T07:05:47.1649790Z         .. note::
2025-07-17T07:05:47.1649930Z             Calling ``model.to(memory_format=torch.channels_last)`` is more aggressive
2025-07-17T07:05:47.1650070Z             than the utility function ``convert_conv2d_weight_memory_format``. Any
2025-07-17T07:05:47.1650200Z             layer with 4d weight will be affected by ``model.to``, which does not
2025-07-17T07:05:47.1650330Z             necessarily benefit from conversion to specified ``memory_format``.
2025-07-17T07:05:47.1650470Z             One place we are confident in is that NHWC(channels_last) conversion for
2025-07-17T07:05:47.1650600Z             convolution in cuDNN, as it is beneficial to run convolution in NHWC,
2025-07-17T07:05:47.1650720Z             even in cases where we have to apply permutation to input tensors.
2025-07-17T07:05:47.1650760Z     
2025-07-17T07:05:47.1650890Z             Hence our strategy here is to convert only the weight of convolution to
2025-07-17T07:05:47.1650960Z             channels_last. This ensures that;
2025-07-17T07:05:47.1651090Z             1. Fast convolution kernels will be used, the benefit of which could
2025-07-17T07:05:47.1651230Z             outweigh overhead of permutation (if input is not in the same format).
2025-07-17T07:05:47.1651370Z             2. No unnecessary permutations are applied on layers that do not benefit
2025-07-17T07:05:47.1651440Z             from memory_format conversion.
2025-07-17T07:05:47.1651480Z     
2025-07-17T07:05:47.1651610Z             The optimal case is that, layers between convolution layers are channels
2025-07-17T07:05:47.1651750Z             last compatible. Input tensor would be permuted to channels last when it
2025-07-17T07:05:47.1651890Z             encounters the first convolution layer and stay in that memory format.
2025-07-17T07:05:47.1652020Z             Hence following convolutions will not need to permute its input tensor.
2025-07-17T07:05:47.1652070Z     
2025-07-17T07:05:47.1652200Z             In case where a channels last incompatible layer is between convolution
2025-07-17T07:05:47.1652320Z             layers, we need to permute the input tensor back to contiguous format
2025-07-17T07:05:47.1652480Z             for that layer. The input tensor will go through the remaining layers in
2025-07-17T07:05:47.1652620Z             contiguous format and be permuted to channels last when it encounters
2025-07-17T07:05:47.1652770Z             another convolution layer. There's no point in propagating that
2025-07-17T07:05:47.1652890Z             permutation to an earlier layer, as most layers are quite agnostic to
2025-07-17T07:05:47.1652950Z             ``memory_format``.
2025-07-17T07:05:47.1652990Z     
2025-07-17T07:05:47.1653130Z             This claim might change when PyTorch supports fusion of permutation, as
2025-07-17T07:05:47.1653260Z             there might have been a better spot to fuse the permutation other than
2025-07-17T07:05:47.1653330Z             immediately before a convolution.
2025-07-17T07:05:47.1653370Z     
2025-07-17T07:05:47.1653410Z         Args:
2025-07-17T07:05:47.1653570Z             module (nn.Module): ``nn.Conv2d`` & ``nn.ConvTranspose2d`` or container
2025-07-17T07:05:47.1653660Z                                 ``nn.Module``
2025-07-17T07:05:47.1653750Z             memory_format: user specified ``memory_format``,
2025-07-17T07:05:47.1653860Z                 e.g. ``torch.channels_last`` or ``torch.contiguous_format``
2025-07-17T07:05:47.1653900Z     
2025-07-17T07:05:47.1653940Z         Returns:
2025-07-17T07:05:47.1654030Z             The original module with updated ``nn.Conv2d``
2025-07-17T07:05:47.1654070Z     
2025-07-17T07:05:47.1654110Z         Example:
2025-07-17T07:05:47.1654200Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-07-17T07:05:47.1654290Z             >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG)
2025-07-17T07:05:47.1654350Z             >>> input = torch.randint(
2025-07-17T07:05:47.1654450Z             ...     1, 10, (2, 8, 4, 4), dtype=torch.float16, device="cuda"
2025-07-17T07:05:47.1654490Z             ... )
2025-07-17T07:05:47.1654550Z             >>> model = nn.Sequential(
2025-07-17T07:05:47.1654620Z             >>>     nn.Conv2d(8, 4, 3)).cuda().half()
2025-07-17T07:05:47.1654680Z             >>> # This is identical to:
2025-07-17T07:05:47.1654830Z             >>> # nn.utils.convert_conv2d_weight_memory_format(model, torch.channels_last)
2025-07-17T07:05:47.1654930Z             >>> model = nn.utils.convert_conv2d_weight_memory_format(
2025-07-17T07:05:47.1655000Z             ...     model, torch.channels_last
2025-07-17T07:05:47.1655040Z             ... )
2025-07-17T07:05:47.1655090Z             >>> out = model(input)
2025-07-17T07:05:47.1655130Z         
2025-07-17T07:05:47.1655280Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1655320Z     
2025-07-17T07:05:47.1655370Z       warnings.warn(msg)
2025-07-17T07:05:47.1655410Z     
2025-07-17T07:05:47.1655510Z --- Parse Warning: 34 / 136 ---
2025-07-17T07:05:47.1656220Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=convert_conv3d_weight_memory_format in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/memory_format.py line=93.
2025-07-17T07:05:47.1656380Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1656510Z     Convert ``memory_format`` of ``nn.Conv3d.weight`` to ``memory_format``
2025-07-17T07:05:47.1656670Z         The conversion recursively applies to nested ``nn.Module``, including ``module``.
2025-07-17T07:05:47.1656830Z         Note that it only changes the memory_format, but not the semantics of each dimensions.
2025-07-17T07:05:47.1656990Z         This function is used to facilitate the computation to adopt NHWC kernels, which
2025-07-17T07:05:47.1657170Z         provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0
2025-07-17T07:05:47.1657210Z     
2025-07-17T07:05:47.1657250Z         .. note::
2025-07-17T07:05:47.1657420Z             Calling ``model.to(memory_format=torch.channels_last_3d)`` is more aggressive
2025-07-17T07:05:47.1657560Z             than the utility function ``convert_conv3d_weight_memory_format``. Any
2025-07-17T07:05:47.1657710Z             layer with 4d weight will be affected by ``model.to``, which does not
2025-07-17T07:05:47.1657840Z             necessarily benefit from conversion to specified ``memory_format``.
2025-07-17T07:05:47.1657980Z             One place we are confident in is that NDHWC(channels_last_3d) conversion for
2025-07-17T07:05:47.1658110Z             convolution in cuDNN, as it is beneficial to run convolution in NDHWC,
2025-07-17T07:05:47.1658230Z             even in cases where we have to apply permutation to input tensors.
2025-07-17T07:05:47.1658270Z     
2025-07-17T07:05:47.1658410Z             Hence our strategy here is to convert only the weight of convolution to
2025-07-17T07:05:47.1658500Z             channels_last_3d. This ensures that;
2025-07-17T07:05:47.1661890Z             1. Fast convolution kernels will be used, the benefit of which could
2025-07-17T07:05:47.1662070Z             outweigh overhead of permutation (if input is not in the same format).
2025-07-17T07:05:47.1662210Z             2. No unnecessary permutations are applied on layers that do not benefit
2025-07-17T07:05:47.1662280Z             from memory_format conversion.
2025-07-17T07:05:47.1662320Z     
2025-07-17T07:05:47.1662450Z             The optimal case is that, layers between convolution layers are channels
2025-07-17T07:05:47.1662590Z             last compatible. Input tensor would be permuted to channels last when it
2025-07-17T07:05:47.1662730Z             encounters the first convolution layer and stay in that memory format.
2025-07-17T07:05:47.1662870Z             Hence following convolutions will not need to permute its input tensor.
2025-07-17T07:05:47.1662910Z     
2025-07-17T07:05:47.1663040Z             In case where a channels last incompatible layer is between convolution
2025-07-17T07:05:47.1663170Z             layers, we need to permute the input tensor back to contiguous format
2025-07-17T07:05:47.1663310Z             for that layer. The input tensor will go through the remaining layers in
2025-07-17T07:05:47.1663440Z             contiguous format and be permuted to channels last when it encounters
2025-07-17T07:05:47.1663570Z             another convolution layer. There's no point in propagating that
2025-07-17T07:05:47.1663700Z             permutation to an earlier layer, as most layers are quite agnostic to
2025-07-17T07:05:47.1663750Z             ``memory_format``.
2025-07-17T07:05:47.1663790Z     
2025-07-17T07:05:47.1663930Z             This claim might change when PyTorch supports fusion of permutation, as
2025-07-17T07:05:47.1664060Z             there might have been a better spot to fuse the permutation other than
2025-07-17T07:05:47.1664130Z             immediately before a convolution.
2025-07-17T07:05:47.1664170Z     
2025-07-17T07:05:47.1664210Z         Args:
2025-07-17T07:05:47.1664340Z             module (nn.Module): ``nn.Conv3d`` & ``nn.ConvTranspose3d`` or container
2025-07-17T07:05:47.1664410Z                                 ``nn.Module``
2025-07-17T07:05:47.1664500Z             memory_format: user specified ``memory_format``,
2025-07-17T07:05:47.1664610Z                 e.g. ``torch.channels_last`` or ``torch.contiguous_format``
2025-07-17T07:05:47.1664650Z     
2025-07-17T07:05:47.1664690Z         Returns:
2025-07-17T07:05:47.1664780Z             The original module with updated ``nn.Conv3d``
2025-07-17T07:05:47.1664820Z     
2025-07-17T07:05:47.1664860Z         Example:
2025-07-17T07:05:47.1664940Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-07-17T07:05:47.1665040Z             >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG)
2025-07-17T07:05:47.1665100Z             >>> input = torch.randint(
2025-07-17T07:05:47.1665190Z             ...     1, 10, (2, 8, 4, 4, 4), dtype=torch.float16, device="cuda"
2025-07-17T07:05:47.1665230Z             ... )
2025-07-17T07:05:47.1665370Z             >>> model = nn.Sequential(
2025-07-17T07:05:47.1665450Z             >>>     nn.Conv3d(8, 4, 3)).cuda().half()
2025-07-17T07:05:47.1665510Z             >>> # This is identical to:
2025-07-17T07:05:47.1665680Z             >>> # nn.utils.convert_conv3d_weight_memory_format(model, torch.channels_last_3d)
2025-07-17T07:05:47.1665780Z             >>> model = nn.utils.convert_conv3d_weight_memory_format(
2025-07-17T07:05:47.1665850Z             ...     model, torch.channels_last_3d
2025-07-17T07:05:47.1665890Z             ... )
2025-07-17T07:05:47.1665950Z             >>> out = model(input)
2025-07-17T07:05:47.1665990Z         
2025-07-17T07:05:47.1666140Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1666180Z     
2025-07-17T07:05:47.1666230Z       warnings.warn(msg)
2025-07-17T07:05:47.1666270Z     
2025-07-17T07:05:47.1666410Z --- Parse Warning: 35 / 136 ---
2025-07-17T07:05:47.1667080Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ln_structured in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py line=979.
2025-07-17T07:05:47.1667230Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1667420Z     Prune tensor by removing channels with the lowest L\ ``n``-norm along the specified dimension.
2025-07-17T07:05:47.1667460Z     
2025-07-17T07:05:47.1667590Z         Prunes tensor corresponding to parameter called ``name`` in ``module``
2025-07-17T07:05:47.1667720Z         by removing the specified ``amount`` of (currently unpruned) channels
2025-07-17T07:05:47.1667830Z         along the specified ``dim`` with the lowest L\ ``n``-norm.
2025-07-17T07:05:47.1667950Z         Modifies module in place (and also return the modified module)
2025-07-17T07:05:47.1667990Z         by:
2025-07-17T07:05:47.1668030Z     
2025-07-17T07:05:47.1668160Z         1) adding a named buffer called ``name+'_mask'`` corresponding to the
2025-07-17T07:05:47.1668290Z            binary mask applied to the parameter ``name`` by the pruning method.
2025-07-17T07:05:47.1668420Z         2) replacing the parameter ``name`` by its pruned version, while the
2025-07-17T07:05:47.1668550Z            original (unpruned) parameter is stored in a new parameter named
2025-07-17T07:05:47.1668600Z            ``name+'_orig'``.
2025-07-17T07:05:47.1668640Z     
2025-07-17T07:05:47.1668680Z         Args:
2025-07-17T07:05:47.1668790Z             module (nn.Module): module containing the tensor to prune
2025-07-17T07:05:47.1668900Z             name (str): parameter name within ``module`` on which pruning
2025-07-17T07:05:47.1668950Z                     will act.
2025-07-17T07:05:47.1669050Z             amount (int or float): quantity of parameters to prune.
2025-07-17T07:05:47.1669160Z                 If ``float``, should be between 0.0 and 1.0 and represent the
2025-07-17T07:05:47.1669280Z                 fraction of parameters to prune. If ``int``, it represents the
2025-07-17T07:05:47.1669360Z                 absolute number of parameters to prune.
2025-07-17T07:05:47.1669480Z             n (int, float, inf, -inf, 'fro', 'nuc'): See documentation of valid
2025-07-17T07:05:47.1669580Z                 entries for argument ``p`` in :func:`torch.norm`.
2025-07-17T07:05:47.1669700Z             dim (int): index of the dim along which we define channels to prune.
2025-07-17T07:05:47.1669840Z             importance_scores (torch.Tensor): tensor of importance scores (of same
2025-07-17T07:05:47.1669950Z                 shape as module parameter) used to compute mask for pruning.
2025-07-17T07:05:47.1670080Z                 The values in this tensor indicate the importance of the corresponding
2025-07-17T07:05:47.1670160Z                 elements in the parameter being pruned.
2025-07-17T07:05:47.1670320Z                 If unspecified or None, the module parameter will be used in its place.
2025-07-17T07:05:47.1670360Z     
2025-07-17T07:05:47.1670410Z         Returns:
2025-07-17T07:05:47.1670540Z             module (nn.Module): modified (i.e. pruned) version of the input module
2025-07-17T07:05:47.1670630Z     
2025-07-17T07:05:47.1670680Z         Examples:
2025-07-17T07:05:47.1670750Z             >>> from torch.nn.utils import prune
2025-07-17T07:05:47.1670810Z             >>> m = prune.ln_structured(
2025-07-17T07:05:47.1670920Z             ...     nn.Conv2d(5, 3, 2), "weight", amount=0.3, dim=1, n=float("-inf")
2025-07-17T07:05:47.1670960Z             ... )
2025-07-17T07:05:47.1671000Z         
2025-07-17T07:05:47.1671150Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1671190Z     
2025-07-17T07:05:47.1671250Z       warnings.warn(msg)
2025-07-17T07:05:47.1671280Z     
2025-07-17T07:05:47.1671380Z --- Parse Warning: 36 / 136 ---
2025-07-17T07:05:47.1672060Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=global_unstructured in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py line=1026.
2025-07-17T07:05:47.1672240Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1672280Z     
2025-07-17T07:05:47.1672530Z     Globally prunes tensors corresponding to all parameters in ``parameters`` by applying the specified ``pruning_method``.
2025-07-17T07:05:47.1672570Z     
2025-07-17T07:05:47.1672660Z     Modifies modules in place by:
2025-07-17T07:05:47.1672700Z     
2025-07-17T07:05:47.1672830Z     1) adding a named buffer called ``name+'_mask'`` corresponding to the
2025-07-17T07:05:47.1672960Z        binary mask applied to the parameter ``name`` by the pruning method.
2025-07-17T07:05:47.1673090Z     2) replacing the parameter ``name`` by its pruned version, while the
2025-07-17T07:05:47.1673210Z        original (unpruned) parameter is stored in a new parameter named
2025-07-17T07:05:47.1673260Z        ``name+'_orig'``.
2025-07-17T07:05:47.1673300Z     
2025-07-17T07:05:47.1673340Z     Args:
2025-07-17T07:05:47.1673470Z         parameters (Iterable of (module, name) tuples): parameters of
2025-07-17T07:05:47.1673580Z             the model to prune in a global fashion, i.e. by aggregating all
2025-07-17T07:05:47.1673710Z             weights prior to deciding which ones to prune. module must be of
2025-07-17T07:05:47.1673800Z             type :class:`nn.Module`, and name must be a string.
2025-07-17T07:05:47.1673940Z         pruning_method (function): a valid pruning function from this module,
2025-07-17T07:05:47.1674040Z             or a custom one implemented by the user that satisfies the
2025-07-17T07:05:47.1674180Z             implementation guidelines and has ``PRUNING_TYPE='unstructured'``.
2025-07-17T07:05:47.1674320Z         importance_scores (dict): a dictionary mapping (module, name) tuples to
2025-07-17T07:05:47.1674450Z             the corresponding parameter's importance scores tensor. The tensor
2025-07-17T07:05:47.1674580Z             should be the same shape as the parameter, and is used for computing
2025-07-17T07:05:47.1674640Z             mask for pruning.
2025-07-17T07:05:47.1674760Z             If unspecified or None, the parameter will be used in place of its
2025-07-17T07:05:47.1674810Z             importance scores.
2025-07-17T07:05:47.1674890Z         kwargs: other keyword arguments such as:
2025-07-17T07:05:47.1675010Z             amount (int or float): quantity of parameters to prune across the
2025-07-17T07:05:47.1675060Z             specified parameters.
2025-07-17T07:05:47.1675170Z             If ``float``, should be between 0.0 and 1.0 and represent the
2025-07-17T07:05:47.1675290Z             fraction of parameters to prune. If ``int``, it represents the
2025-07-17T07:05:47.1675360Z             absolute number of parameters to prune.
2025-07-17T07:05:47.1675410Z     
2025-07-17T07:05:47.1675470Z     Raises:
2025-07-17T07:05:47.1675560Z         TypeError: if ``PRUNING_TYPE != 'unstructured'``
2025-07-17T07:05:47.1675600Z     
2025-07-17T07:05:47.1675640Z     Note:
2025-07-17T07:05:47.1675790Z         Since global structured pruning doesn't make much sense unless the
2025-07-17T07:05:47.1675910Z         norm is normalized by the size of the parameter, we now limit the
2025-07-17T07:05:47.1676000Z         scope of global pruning to unstructured methods.
2025-07-17T07:05:47.1676040Z     
2025-07-17T07:05:47.1676080Z     Examples:
2025-07-17T07:05:47.1676150Z         >>> from torch.nn.utils import prune
2025-07-17T07:05:47.1676220Z         >>> from collections import OrderedDict
2025-07-17T07:05:47.1676280Z         >>> net = nn.Sequential(
2025-07-17T07:05:47.1676330Z         ...     OrderedDict(
2025-07-17T07:05:47.1676370Z         ...         [
2025-07-17T07:05:47.1676470Z         ...             ("first", nn.Linear(10, 4)),
2025-07-17T07:05:47.1676570Z         ...             ("second", nn.Linear(4, 1)),
2025-07-17T07:05:47.1676610Z         ...         ]
2025-07-17T07:05:47.1676650Z         ...     )
2025-07-17T07:05:47.1676700Z         ... )
2025-07-17T07:05:47.1676750Z         >>> parameters_to_prune = (
2025-07-17T07:05:47.1676810Z         ...     (net.first, "weight"),
2025-07-17T07:05:47.1676870Z         ...     (net.second, "weight"),
2025-07-17T07:05:47.1676910Z         ... )
2025-07-17T07:05:47.1676970Z         >>> prune.global_unstructured(
2025-07-17T07:05:47.1677030Z         ...     parameters_to_prune,
2025-07-17T07:05:47.1677110Z         ...     pruning_method=prune.L1Unstructured,
2025-07-17T07:05:47.1677160Z         ...     amount=10,
2025-07-17T07:05:47.1677200Z         ... )
2025-07-17T07:05:47.1677330Z         >>> print(sum(torch.nn.utils.parameters_to_vector(net.buffers()) == 0))
2025-07-17T07:05:47.1677380Z         tensor(10)
2025-07-17T07:05:47.1677420Z     
2025-07-17T07:05:47.1677460Z     
2025-07-17T07:05:47.1677610Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1677650Z     
2025-07-17T07:05:47.1677710Z       warnings.warn(msg)
2025-07-17T07:05:47.1677740Z     
2025-07-17T07:05:47.1677840Z --- Parse Warning: 37 / 136 ---
2025-07-17T07:05:47.1678490Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=custom_from_mask in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/prune.py line=1149.
2025-07-17T07:05:47.1678650Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1678880Z     Prune tensor corresponding to parameter called ``name`` in ``module`` by applying the pre-computed mask in ``mask``.
2025-07-17T07:05:47.1678920Z     
2025-07-17T07:05:47.1679050Z         Modifies module in place (and also return the modified module) by:
2025-07-17T07:05:47.1679090Z     
2025-07-17T07:05:47.1679220Z         1) adding a named buffer called ``name+'_mask'`` corresponding to the
2025-07-17T07:05:47.1679350Z            binary mask applied to the parameter ``name`` by the pruning method.
2025-07-17T07:05:47.1679480Z         2) replacing the parameter ``name`` by its pruned version, while the
2025-07-17T07:05:47.1679600Z            original (unpruned) parameter is stored in a new parameter named
2025-07-17T07:05:47.1679650Z            ``name+'_orig'``.
2025-07-17T07:05:47.1679690Z     
2025-07-17T07:05:47.1679730Z         Args:
2025-07-17T07:05:47.1679840Z             module (nn.Module): module containing the tensor to prune
2025-07-17T07:05:47.1679950Z             name (str): parameter name within ``module`` on which pruning
2025-07-17T07:05:47.1680000Z                 will act.
2025-07-17T07:05:47.1680110Z             mask (Tensor): binary mask to be applied to the parameter.
2025-07-17T07:05:47.1680150Z     
2025-07-17T07:05:47.1680190Z         Returns:
2025-07-17T07:05:47.1680340Z             module (nn.Module): modified (i.e. pruned) version of the input module
2025-07-17T07:05:47.1680380Z     
2025-07-17T07:05:47.1680430Z         Examples:
2025-07-17T07:05:47.1680500Z             >>> from torch.nn.utils import prune
2025-07-17T07:05:47.1680590Z             >>> m = prune.custom_from_mask(
2025-07-17T07:05:47.1680690Z             ...     nn.Linear(5, 3), name="bias", mask=torch.tensor([0, 1, 0])
2025-07-17T07:05:47.1680740Z             ... )
2025-07-17T07:05:47.1680790Z             >>> print(m.bias_mask)
2025-07-17T07:05:47.1680840Z             tensor([0., 1., 0.])
2025-07-17T07:05:47.1680880Z     
2025-07-17T07:05:47.1680920Z         
2025-07-17T07:05:47.1681070Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1681110Z     
2025-07-17T07:05:47.1681160Z       warnings.warn(msg)
2025-07-17T07:05:47.1681200Z     
2025-07-17T07:05:47.1681300Z --- Parse Warning: 38 / 136 ---
2025-07-17T07:05:47.1681970Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=pad_packed_sequence in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/rnn.py line=342.
2025-07-17T07:05:47.1682150Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1682240Z     Pad a packed batch of variable length sequences.
2025-07-17T07:05:47.1682270Z     
2025-07-17T07:05:47.1682380Z         It is an inverse operation to :func:`pack_padded_sequence`.
2025-07-17T07:05:47.1682420Z     
2025-07-17T07:05:47.1682590Z         The returned Tensor's data will be of size ``T x B x *`` (if :attr:`batch_first` is ``False``)
2025-07-17T07:05:47.1682740Z         or ``B x T x *`` (if :attr:`batch_first` is ``True``) , where ``T`` is the length of the longest
2025-07-17T07:05:47.1682810Z         sequence and ``B`` is the batch size.
2025-07-17T07:05:47.1682850Z     
2025-07-17T07:05:47.1682900Z         Example:
2025-07-17T07:05:47.1683040Z             >>> from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
2025-07-17T07:05:47.1683140Z             >>> seq = torch.tensor([[1, 2, 0], [3, 0, 0], [4, 5, 6]])
2025-07-17T07:05:47.1683190Z             >>> lens = [2, 1, 3]
2025-07-17T07:05:47.1683260Z             >>> packed = pack_padded_sequence(
2025-07-17T07:05:47.1683350Z             ...     seq, lens, batch_first=True, enforce_sorted=False
2025-07-17T07:05:47.1683390Z             ... )
2025-07-17T07:05:47.1683440Z             >>> packed
2025-07-17T07:05:47.1683580Z             PackedSequence(data=tensor([4, 1, 3, 5, 2, 6]), batch_sizes=tensor([3, 2, 1]),
2025-07-17T07:05:47.1683720Z                            sorted_indices=tensor([2, 0, 1]), unsorted_indices=tensor([1, 2, 0]))
2025-07-17T07:05:47.1683860Z             >>> seq_unpacked, lens_unpacked = pad_packed_sequence(packed, batch_first=True)
2025-07-17T07:05:47.1683920Z             >>> seq_unpacked
2025-07-17T07:05:47.1683970Z             tensor([[1, 2, 0],
2025-07-17T07:05:47.1684020Z                     [3, 0, 0],
2025-07-17T07:05:47.1684070Z                     [4, 5, 6]])
2025-07-17T07:05:47.1684120Z             >>> lens_unpacked
2025-07-17T07:05:47.1684170Z             tensor([2, 1, 3])
2025-07-17T07:05:47.1684210Z     
2025-07-17T07:05:47.1684260Z         .. note::
2025-07-17T07:05:47.1684340Z             :attr:`total_length` is useful to implement the
2025-07-17T07:05:47.1684480Z             ``pack sequence -> recurrent network -> unpack sequence`` pattern in a
2025-07-17T07:05:47.1684610Z             :class:`~torch.nn.Module` wrapped in :class:`~torch.nn.DataParallel`.
2025-07-17T07:05:47.1684750Z             See :ref:`this FAQ section <pack-rnn-unpack-with-data-parallelism>` for
2025-07-17T07:05:47.1684790Z             details.
2025-07-17T07:05:47.1684840Z     
2025-07-17T07:05:47.1684880Z         Args:
2025-07-17T07:05:47.1684960Z             sequence (PackedSequence): batch to pad
2025-07-17T07:05:47.1685130Z             batch_first (bool, optional): if ``True``, the output will be in ``B x T x *``
2025-07-17T07:05:47.1685200Z                 format, ``T x B x *`` otherwise.
2025-07-17T07:05:47.1685320Z             padding_value (float, optional): values for padded elements.
2025-07-17T07:05:47.1685480Z             total_length (int, optional): if not ``None``, the output will be padded to
2025-07-17T07:05:47.1685630Z                 have length :attr:`total_length`. This method will throw :class:`ValueError`
2025-07-17T07:05:47.1685740Z                 if :attr:`total_length` is less than the max sequence length in
2025-07-17T07:05:47.1685790Z                 :attr:`sequence`.
2025-07-17T07:05:47.1685840Z     
2025-07-17T07:05:47.1685880Z         Returns:
2025-07-17T07:05:47.1685990Z             Tuple of Tensor containing the padded sequence, and a Tensor
2025-07-17T07:05:47.1686110Z             containing the list of lengths of each sequence in the batch.
2025-07-17T07:05:47.1686270Z             Batch elements will be re-ordered as they were ordered originally when
2025-07-17T07:05:47.1686420Z             the batch was passed to ``pack_padded_sequence`` or ``pack_sequence``.
2025-07-17T07:05:47.1686460Z         
2025-07-17T07:05:47.1686610Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1686650Z     
2025-07-17T07:05:47.1686700Z       warnings.warn(msg)
2025-07-17T07:05:47.1686740Z     
2025-07-17T07:05:47.1686840Z --- Parse Warning: 39 / 136 ---
2025-07-17T07:05:47.1687480Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Unflatten in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/flatten.py line=60.
2025-07-17T07:05:47.1687640Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1687680Z     
2025-07-17T07:05:47.1687870Z     Unflattens a tensor dim expanding it to a desired shape. For use with :class:`~nn.Sequential`.
2025-07-17T07:05:47.1687910Z     
2025-07-17T07:05:47.1688070Z     * :attr:`dim` specifies the dimension of the input tensor to be unflattened, and it can
2025-07-17T07:05:47.1688210Z       be either `int` or `str` when `Tensor` or `NamedTensor` is used, respectively.
2025-07-17T07:05:47.1688250Z     
2025-07-17T07:05:47.1688440Z     * :attr:`unflattened_size` is the new shape of the unflattened dimension of the tensor and it can be
2025-07-17T07:05:47.1688590Z       a `tuple` of ints or a `list` of ints or `torch.Size` for `Tensor` input;  a `NamedShape`
2025-07-17T07:05:47.1688690Z       (tuple of `(name, size)` tuples) for `NamedTensor` input.
2025-07-17T07:05:47.1688730Z     
2025-07-17T07:05:47.1688780Z     Shape:
2025-07-17T07:05:47.1688910Z         - Input: :math:`(*, S_{\text{dim}}, *)`, where :math:`S_{\text{dim}}` is the size at
2025-07-17T07:05:47.1689060Z           dimension :attr:`dim` and :math:`*` means any number of dimensions including none.
2025-07-17T07:05:47.1689200Z         - Output: :math:`(*, U_1, ..., U_n, *)`, where :math:`U` = :attr:`unflattened_size` and
2025-07-17T07:05:47.1689280Z           :math:`\prod_{i=1}^n U_i = S_{\text{dim}}`.
2025-07-17T07:05:47.1689320Z     
2025-07-17T07:05:47.1689360Z     Args:
2025-07-17T07:05:47.1689450Z         dim (Union[int, str]): Dimension to be unflattened
2025-07-17T07:05:47.1689660Z         unflattened_size (Union[torch.Size, Tuple, List, NamedShape]): New shape of the unflattened dimension
2025-07-17T07:05:47.1689700Z     
2025-07-17T07:05:47.1689750Z     Examples:
2025-07-17T07:05:47.1689810Z         >>> input = torch.randn(2, 50)
2025-07-17T07:05:47.1689860Z         >>> # With tuple of ints
2025-07-17T07:05:47.1689910Z         >>> m = nn.Sequential(
2025-07-17T07:05:47.1689960Z         >>>     nn.Linear(50, 50),
2025-07-17T07:05:47.1690030Z         >>>     nn.Unflatten(1, (2, 5, 5))
2025-07-17T07:05:47.1690070Z         >>> )
2025-07-17T07:05:47.1690120Z         >>> output = m(input)
2025-07-17T07:05:47.1690190Z         >>> output.size()
2025-07-17T07:05:47.1690250Z         torch.Size([2, 2, 5, 5])
2025-07-17T07:05:47.1690300Z         >>> # With torch.Size
2025-07-17T07:05:47.1690350Z         >>> m = nn.Sequential(
2025-07-17T07:05:47.1690430Z         >>>     nn.Linear(50, 50),
2025-07-17T07:05:47.1690510Z         >>>     nn.Unflatten(1, torch.Size([2, 5, 5]))
2025-07-17T07:05:47.1690550Z         >>> )
2025-07-17T07:05:47.1690600Z         >>> output = m(input)
2025-07-17T07:05:47.1690650Z         >>> output.size()
2025-07-17T07:05:47.1690700Z         torch.Size([2, 2, 5, 5])
2025-07-17T07:05:47.1690770Z         >>> # With namedshape (tuple of tuples)
2025-07-17T07:05:47.1690860Z         >>> input = torch.randn(2, 50, names=("N", "features"))
2025-07-17T07:05:47.1690990Z         >>> unflatten = nn.Unflatten("features", (("C", 2), ("H", 5), ("W", 5)))
2025-07-17T07:05:47.1691050Z         >>> output = unflatten(input)
2025-07-17T07:05:47.1691120Z         >>> output.size()
2025-07-17T07:05:47.1691190Z         torch.Size([2, 2, 5, 5])
2025-07-17T07:05:47.1691230Z     
2025-07-17T07:05:47.1691380Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1691420Z     
2025-07-17T07:05:47.1691470Z       warnings.warn(msg)
2025-07-17T07:05:47.1691510Z     
2025-07-17T07:05:47.1691610Z --- Parse Warning: 40 / 136 ---
2025-07-17T07:05:47.1692270Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyncBatchNorm in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py line=601.
2025-07-17T07:05:47.1692420Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1692530Z     Applies Batch Normalization over a N-Dimensional input.
2025-07-17T07:05:47.1692570Z     
2025-07-17T07:05:47.1692780Z         The N-D input is a mini-batch of [N-2]D inputs with additional channel dimension) as described in the paper
2025-07-17T07:05:47.1692920Z         `Batch Normalization: Accelerating Deep Network Training by Reducing
2025-07-17T07:05:47.1693050Z         Internal Covariate Shift <https://arxiv.org/abs/1502.03167>`__ .
2025-07-17T07:05:47.1693090Z     
2025-07-17T07:05:47.1693130Z         .. math::
2025-07-17T07:05:47.1693170Z     
2025-07-17T07:05:47.1693310Z             y = \frac{x - \mathrm{E}[x]}{ \sqrt{\mathrm{Var}[x] + \epsilon}} * \gamma + \beta
2025-07-17T07:05:47.1693350Z     
2025-07-17T07:05:47.1693480Z         The mean and standard-deviation are calculated per-dimension over all
2025-07-17T07:05:47.1693620Z         mini-batches of the same process groups. :math:`\gamma` and :math:`\beta`
2025-07-17T07:05:47.1693760Z         are learnable parameter vectors of size `C` (where `C` is the input size).
2025-07-17T07:05:47.1693940Z         By default, the elements of :math:`\gamma` are sampled from
2025-07-17T07:05:47.1694070Z         :math:`\mathcal{U}(0, 1)` and the elements of :math:`\beta` are set to 0.
2025-07-17T07:05:47.1694220Z         The standard-deviation is calculated via the biased estimator, equivalent to
2025-07-17T07:05:47.1694290Z         `torch.var(input, unbiased=False)`.
2025-07-17T07:05:47.1694330Z     
2025-07-17T07:05:47.1694470Z         Also by default, during training this layer keeps running estimates of its
2025-07-17T07:05:47.1694610Z         computed mean and variance, which are then used for normalization during
2025-07-17T07:05:47.1694750Z         evaluation. The running estimates are kept with a default :attr:`momentum`
2025-07-17T07:05:47.1694790Z         of 0.1.
2025-07-17T07:05:47.1694830Z     
2025-07-17T07:05:47.1694970Z         If :attr:`track_running_stats` is set to ``False``, this layer then does not
2025-07-17T07:05:47.1695100Z         keep running estimates, and batch statistics are instead used during
2025-07-17T07:05:47.1695160Z         evaluation time as well.
2025-07-17T07:05:47.1695200Z     
2025-07-17T07:05:47.1695270Z         .. note::
2025-07-17T07:05:47.1695410Z             This :attr:`momentum` argument is different from one used in optimizer
2025-07-17T07:05:47.1695540Z             classes and the conventional notion of momentum. Mathematically, the
2025-07-17T07:05:47.1695650Z             update rule for running statistics here is
2025-07-17T07:05:47.1695810Z             :math:`\hat{x}_\text{new} = (1 - \text{momentum}) \times \hat{x} + \text{momentum} \times x_t`,
2025-07-17T07:05:47.1695940Z             where :math:`\hat{x}` is the estimated statistic and :math:`x_t` is the
2025-07-17T07:05:47.1695990Z             new observed value.
2025-07-17T07:05:47.1696030Z     
2025-07-17T07:05:47.1696210Z         Because the Batch Normalization is done for each channel in the ``C`` dimension, computing
2025-07-17T07:05:47.1696360Z         statistics on ``(N, +)`` slices, it's common terminology to call this Volumetric Batch
2025-07-17T07:05:47.1696520Z         Normalization or Spatio-temporal Batch Normalization.
2025-07-17T07:05:47.1696590Z     
2025-07-17T07:05:47.1696680Z         Currently :class:`SyncBatchNorm` only supports
2025-07-17T07:05:47.1696850Z         :class:`~torch.nn.DistributedDataParallel` (DDP) with single GPU per process. Use
2025-07-17T07:05:47.1696980Z         :meth:`torch.nn.SyncBatchNorm.convert_sync_batchnorm()` to convert
2025-07-17T07:05:47.1697100Z         :attr:`BatchNorm*D` layer to :class:`SyncBatchNorm` before wrapping
2025-07-17T07:05:47.1697160Z         Network with DDP.
2025-07-17T07:05:47.1697200Z     
2025-07-17T07:05:47.1697240Z         Args:
2025-07-17T07:05:47.1697340Z             num_features: :math:`C` from an expected input of size
2025-07-17T07:05:47.1697390Z                 :math:`(N, C, +)`
2025-07-17T07:05:47.1697510Z             eps: a value added to the denominator for numerical stability.
2025-07-17T07:05:47.1697560Z                 Default: ``1e-5``
2025-07-17T07:05:47.1697680Z             momentum: the value used for the running_mean and running_var
2025-07-17T07:05:47.1697800Z                 computation. Can be set to ``None`` for cumulative moving average
2025-07-17T07:05:47.1697880Z                 (i.e. simple average). Default: 0.1
2025-07-17T07:05:47.1698000Z             affine: a boolean value that when set to ``True``, this module has
2025-07-17T07:05:47.1698090Z                 learnable affine parameters. Default: ``True``
2025-07-17T07:05:47.1698220Z             track_running_stats: a boolean value that when set to ``True``, this
2025-07-17T07:05:47.1698360Z                 module tracks the running mean and variance, and when set to ``False``,
2025-07-17T07:05:47.1698500Z                 this module does not track such statistics, and initializes statistics
2025-07-17T07:05:47.1698620Z                 buffers :attr:`running_mean` and :attr:`running_var` as ``None``.
2025-07-17T07:05:47.1698750Z                 When these buffers are ``None``, this module always uses batch statistics.
2025-07-17T07:05:47.1698850Z                 in both training and eval modes. Default: ``True``
2025-07-17T07:05:47.1699000Z             process_group: synchronization of stats happen within each process group
2025-07-17T07:05:47.1699140Z                 individually. Default behavior is synchronization across the whole
2025-07-17T07:05:47.1699180Z                 world
2025-07-17T07:05:47.1699220Z     
2025-07-17T07:05:47.1699260Z         Shape:
2025-07-17T07:05:47.1699320Z             - Input: :math:`(N, C, +)`
2025-07-17T07:05:47.1699410Z             - Output: :math:`(N, C, +)` (same shape as input)
2025-07-17T07:05:47.1699450Z     
2025-07-17T07:05:47.1699490Z         .. note::
2025-07-17T07:05:47.1699640Z             Synchronization of batchnorm statistics occurs only while training, i.e.
2025-07-17T07:05:47.1699760Z             synchronization is disabled when ``model.eval()`` is set or if
2025-07-17T07:05:47.1699830Z             ``self.training`` is otherwise ``False``.
2025-07-17T07:05:47.1699880Z     
2025-07-17T07:05:47.1699920Z         Examples::
2025-07-17T07:05:47.1699960Z     
2025-07-17T07:05:47.1700030Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1700100Z             >>> # With Learnable Parameters
2025-07-17T07:05:47.1700160Z             >>> m = nn.SyncBatchNorm(100)
2025-07-17T07:05:47.1700260Z             >>> # creating process group (optional)
2025-07-17T07:05:47.1700340Z             >>> # ranks is a list of int identifying rank ids.
2025-07-17T07:05:47.1700400Z             >>> ranks = list(range(8))
2025-07-17T07:05:47.1700460Z             >>> r1, r2 = ranks[:4], ranks[4:]
2025-07-17T07:05:47.1700550Z             >>> # Note: every rank calls into new_group for every
2025-07-17T07:05:47.1700640Z             >>> # process group created, even if that rank is not
2025-07-17T07:05:47.1700700Z             >>> # part of the group.
2025-07-17T07:05:47.1700850Z             >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]]
2025-07-17T07:05:47.1700990Z             >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1]
2025-07-17T07:05:47.1701080Z             >>> # Without Learnable Parameters
2025-07-17T07:05:47.1701200Z             >>> m = nn.BatchNorm3d(100, affine=False, process_group=process_group)
2025-07-17T07:05:47.1701280Z             >>> input = torch.randn(20, 100, 35, 45, 10)
2025-07-17T07:05:47.1701330Z             >>> output = m(input)
2025-07-17T07:05:47.1701370Z     
2025-07-17T07:05:47.1701440Z             >>> # network is nn.BatchNorm layer
2025-07-17T07:05:47.1701610Z             >>> sync_bn_network = nn.SyncBatchNorm.convert_sync_batchnorm(network, process_group)
2025-07-17T07:05:47.1701710Z             >>> # only single gpu per process is currently supported
2025-07-17T07:05:47.1701840Z             >>> ddp_sync_bn_network = torch.nn.parallel.DistributedDataParallel(
2025-07-17T07:05:47.1701910Z             >>>                         sync_bn_network,
2025-07-17T07:05:47.1701990Z             >>>                         device_ids=[args.local_rank],
2025-07-17T07:05:47.1702080Z             >>>                         output_device=args.local_rank)
2025-07-17T07:05:47.1702120Z         
2025-07-17T07:05:47.1702270Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1702310Z     
2025-07-17T07:05:47.1702360Z       warnings.warn(msg)
2025-07-17T07:05:47.1702400Z     
2025-07-17T07:05:47.1702500Z --- Parse Warning: 41 / 136 ---
2025-07-17T07:05:47.1703220Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyncBatchNorm.convert_sync_batchnorm in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/batchnorm.py line=825.
2025-07-17T07:05:47.1703380Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1703560Z     Converts all :attr:`BatchNorm*D` layers in the model to :class:`torch.nn.SyncBatchNorm` layers.
2025-07-17T07:05:47.1703610Z     
2025-07-17T07:05:47.1703650Z             Args:
2025-07-17T07:05:47.1703800Z                 module (nn.Module): module containing one or more :attr:`BatchNorm*D` layers
2025-07-17T07:05:47.1703930Z                 process_group (optional): process group to scope synchronization,
2025-07-17T07:05:47.1704000Z                     default is the whole world
2025-07-17T07:05:47.1704040Z     
2025-07-17T07:05:47.1704080Z             Returns:
2025-07-17T07:05:47.1704230Z                 The original :attr:`module` with the converted :class:`torch.nn.SyncBatchNorm`
2025-07-17T07:05:47.1704360Z                 layers. If the original :attr:`module` is a :attr:`BatchNorm*D` layer,
2025-07-17T07:05:47.1704490Z                 a new :class:`torch.nn.SyncBatchNorm` layer object will be returned
2025-07-17T07:05:47.1704540Z                 instead.
2025-07-17T07:05:47.1704580Z     
2025-07-17T07:05:47.1704620Z             Example::
2025-07-17T07:05:47.1704670Z     
2025-07-17T07:05:47.1704740Z                 >>> # Network with nn.BatchNorm layer
2025-07-17T07:05:47.1704860Z                 >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-07-17T07:05:47.1704940Z                 >>> module = torch.nn.Sequential(
2025-07-17T07:05:47.1705010Z                 >>>            torch.nn.Linear(20, 100),
2025-07-17T07:05:47.1705100Z                 >>>            torch.nn.BatchNorm1d(100),
2025-07-17T07:05:47.1705150Z                 >>>          ).cuda()
2025-07-17T07:05:47.1705230Z                 >>> # creating process group (optional)
2025-07-17T07:05:47.1705320Z                 >>> # ranks is a list of int identifying rank ids.
2025-07-17T07:05:47.1705380Z                 >>> ranks = list(range(8))
2025-07-17T07:05:47.1705440Z                 >>> r1, r2 = ranks[:4], ranks[4:]
2025-07-17T07:05:47.1705530Z                 >>> # Note: every rank calls into new_group for every
2025-07-17T07:05:47.1705650Z                 >>> # process group created, even if that rank is not
2025-07-17T07:05:47.1705730Z                 >>> # part of the group.
2025-07-17T07:05:47.1705800Z                 >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:47.1705950Z                 >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]]
2025-07-17T07:05:47.1706080Z                 >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1]
2025-07-17T07:05:47.1706260Z                 >>> sync_bn_module = torch.nn.SyncBatchNorm.convert_sync_batchnorm(module, process_group)
2025-07-17T07:05:47.1706300Z     
2025-07-17T07:05:47.1706340Z             
2025-07-17T07:05:47.1706490Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1706530Z     
2025-07-17T07:05:47.1706580Z       warnings.warn(msg)
2025-07-17T07:05:47.1706620Z     
2025-07-17T07:05:47.1706720Z --- Parse Warning: 42 / 136 ---
2025-07-17T07:05:47.1707380Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MaxUnpool2d in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/pooling.py line=406.
2025-07-17T07:05:47.1707530Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1707630Z     Computes a partial inverse of :class:`MaxPool2d`.
2025-07-17T07:05:47.1707670Z     
2025-07-17T07:05:47.1707820Z         :class:`MaxPool2d` is not fully invertible, since the non-maximal values are lost.
2025-07-17T07:05:47.1707860Z     
2025-07-17T07:05:47.1707990Z         :class:`MaxUnpool2d` takes in as input the output of :class:`MaxPool2d`
2025-07-17T07:05:47.1708140Z         including the indices of the maximal values and computes a partial inverse
2025-07-17T07:05:47.1708230Z         in which all non-maximal values are set to zero.
2025-07-17T07:05:47.1708270Z     
2025-07-17T07:05:47.1708310Z         Note:
2025-07-17T07:05:47.1708500Z             This operation may behave nondeterministically when the input indices has repeat values.
2025-07-17T07:05:47.1708720Z             See https://github.com/pytorch/pytorch/issues/80827 and :doc:`/notes/randomness` for more information.
2025-07-17T07:05:47.1708770Z     
2025-07-17T07:05:47.1708900Z         .. note:: :class:`MaxPool2d` can map several input sizes to the same output
2025-07-17T07:05:47.1709010Z                   sizes. Hence, the inversion process can get ambiguous.
2025-07-17T07:05:47.1709120Z                   To accommodate this, you can provide the needed output size
2025-07-17T07:05:47.1709250Z                   as an additional argument :attr:`output_size` in the forward call.
2025-07-17T07:05:47.1709320Z                   See the Inputs and Example below.
2025-07-17T07:05:47.1709360Z     
2025-07-17T07:05:47.1709400Z         Args:
2025-07-17T07:05:47.1709510Z             kernel_size (int or tuple): Size of the max pooling window.
2025-07-17T07:05:47.1709620Z             stride (int or tuple): Stride of the max pooling window.
2025-07-17T07:05:47.1709750Z                 It is set to :attr:`kernel_size` by default.
2025-07-17T07:05:47.1709870Z             padding (int or tuple): Padding that was added to the input
2025-07-17T07:05:47.1709910Z     
2025-07-17T07:05:47.1709950Z         Inputs:
2025-07-17T07:05:47.1710050Z             - `input`: the input Tensor to invert
2025-07-17T07:05:47.1710180Z             - `indices`: the indices given out by :class:`~torch.nn.MaxPool2d`
2025-07-17T07:05:47.1710270Z             - `output_size` (optional): the targeted output size
2025-07-17T07:05:47.1710310Z     
2025-07-17T07:05:47.1710350Z         Shape:
2025-07-17T07:05:47.1710470Z             - Input: :math:`(N, C, H_{in}, W_{in})` or :math:`(C, H_{in}, W_{in})`.
2025-07-17T07:05:47.1710600Z             - Output: :math:`(N, C, H_{out}, W_{out})` or :math:`(C, H_{out}, W_{out})`, where
2025-07-17T07:05:47.1710640Z     
2025-07-17T07:05:47.1710690Z               .. math::
2025-07-17T07:05:47.1710870Z                 H_{out} = (H_{in} - 1) \times \text{stride[0]} - 2 \times \text{padding[0]} + \text{kernel\_size[0]}
2025-07-17T07:05:47.1710930Z     
2025-07-17T07:05:47.1710970Z               .. math::
2025-07-17T07:05:47.1711130Z                 W_{out} = (W_{in} - 1) \times \text{stride[1]} - 2 \times \text{padding[1]} + \text{kernel\_size[1]}
2025-07-17T07:05:47.1711170Z     
2025-07-17T07:05:47.1711270Z               or as given by :attr:`output_size` in the call operator
2025-07-17T07:05:47.1711310Z     
2025-07-17T07:05:47.1711360Z         Example::
2025-07-17T07:05:47.1711390Z     
2025-07-17T07:05:47.1711490Z             >>> pool = nn.MaxPool2d(2, stride=2, return_indices=True)
2025-07-17T07:05:47.1711570Z             >>> unpool = nn.MaxUnpool2d(2, stride=2)
2025-07-17T07:05:47.1711650Z             >>> input = torch.tensor([[[[ 1.,  2.,  3.,  4.],
2025-07-17T07:05:47.1711720Z                                         [ 5.,  6.,  7.,  8.],
2025-07-17T07:05:47.1711790Z                                         [ 9., 10., 11., 12.],
2025-07-17T07:05:47.1711860Z                                         [13., 14., 15., 16.]]]])
2025-07-17T07:05:47.1711930Z             >>> output, indices = pool(input)
2025-07-17T07:05:47.1711980Z             >>> unpool(output, indices)
2025-07-17T07:05:47.1712040Z             tensor([[[[  0.,   0.,   0.,   0.],
2025-07-17T07:05:47.1712100Z                       [  0.,   6.,   0.,   8.],
2025-07-17T07:05:47.1712160Z                       [  0.,   0.,   0.,   0.],
2025-07-17T07:05:47.1712220Z                       [  0.,  14.,   0.,  16.]]]])
2025-07-17T07:05:47.1712350Z             >>> # Now using output_size to resolve an ambiguous size for the inverse
2025-07-17T07:05:47.1712430Z             >>> input = torch.tensor([[[[ 1.,  2.,  3.,  4.,  5.],
2025-07-17T07:05:47.1712500Z                                         [ 6.,  7.,  8.,  9., 10.],
2025-07-17T07:05:47.1715930Z                                         [11., 12., 13., 14., 15.],
2025-07-17T07:05:47.1716020Z                                         [16., 17., 18., 19., 20.]]]])
2025-07-17T07:05:47.1716100Z             >>> output, indices = pool(input)
2025-07-17T07:05:47.1716200Z             >>> # This call will not work without specifying output_size
2025-07-17T07:05:47.1716300Z             >>> unpool(output, indices, output_size=input.size())
2025-07-17T07:05:47.1716360Z             tensor([[[[ 0.,  0.,  0.,  0.,  0.],
2025-07-17T07:05:47.1716420Z                       [ 0.,  7.,  0.,  9.,  0.],
2025-07-17T07:05:47.1716470Z                       [ 0.,  0.,  0.,  0.,  0.],
2025-07-17T07:05:47.1716530Z                       [ 0., 17.,  0., 19.,  0.]]]])
2025-07-17T07:05:47.1716570Z     
2025-07-17T07:05:47.1716610Z     
2025-07-17T07:05:47.1716650Z         
2025-07-17T07:05:47.1716810Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1716850Z     
2025-07-17T07:05:47.1716900Z       warnings.warn(msg)
2025-07-17T07:05:47.1716940Z     
2025-07-17T07:05:47.1717050Z --- Parse Warning: 43 / 136 ---
2025-07-17T07:05:47.1717870Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=TripletMarginWithDistanceLoss in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py line=1718.
2025-07-17T07:05:47.1718040Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1718160Z     Creates a criterion that measures the triplet loss given input
2025-07-17T07:05:47.1718280Z         tensors :math:`a`, :math:`p`, and :math:`n` (representing anchor,
2025-07-17T07:05:47.1718410Z         positive, and negative examples, respectively), and a nonnegative,
2025-07-17T07:05:47.1718550Z         real-valued function ("distance function") used to compute the relationship
2025-07-17T07:05:47.1718690Z         between the anchor and positive example ("positive distance") and the
2025-07-17T07:05:47.1718810Z         anchor and negative example ("negative distance").
2025-07-17T07:05:47.1718880Z     
2025-07-17T07:05:47.1719010Z         The unreduced loss (i.e., with :attr:`reduction` set to ``'none'``)
2025-07-17T07:05:47.1719070Z         can be described as:
2025-07-17T07:05:47.1719110Z     
2025-07-17T07:05:47.1719150Z         .. math::
2025-07-17T07:05:47.1719240Z             \ell(a, p, n) = L = \{l_1,\dots,l_N\}^\top, \quad
2025-07-17T07:05:47.1719330Z             l_i = \max \{d(a_i, p_i) - d(a_i, n_i) + {\rm margin}, 0\}
2025-07-17T07:05:47.1719370Z     
2025-07-17T07:05:47.1719520Z         where :math:`N` is the batch size; :math:`d` is a nonnegative, real-valued function
2025-07-17T07:05:47.1719700Z         quantifying the closeness of two tensors, referred to as the :attr:`distance_function`;
2025-07-17T07:05:47.1719840Z         and :math:`margin` is a nonnegative margin representing the minimum difference
2025-07-17T07:05:47.1719990Z         between the positive and negative distances that is required for the loss to
2025-07-17T07:05:47.1720130Z         be 0.  The input tensors have :math:`N` elements each and can be of any shape
2025-07-17T07:05:47.1720200Z         that the distance function can handle.
2025-07-17T07:05:47.1720240Z     
2025-07-17T07:05:47.1720310Z         If :attr:`reduction` is not ``'none'``
2025-07-17T07:05:47.1720360Z         (default ``'mean'``), then:
2025-07-17T07:05:47.1720400Z     
2025-07-17T07:05:47.1720450Z         .. math::
2025-07-17T07:05:47.1720490Z             \ell(x, y) =
2025-07-17T07:05:47.1720540Z             \begin{cases}
2025-07-17T07:05:47.1720660Z                 \operatorname{mean}(L), &  \text{if reduction} = \text{`mean';}\\
2025-07-17T07:05:47.1720780Z                 \operatorname{sum}(L),  &  \text{if reduction} = \text{`sum'.}
2025-07-17T07:05:47.1720820Z             \end{cases}
2025-07-17T07:05:47.1720870Z     
2025-07-17T07:05:47.1721000Z         See also :class:`~torch.nn.TripletMarginLoss`, which computes the triplet
2025-07-17T07:05:47.1721160Z         loss for input tensors using the :math:`l_p` distance as the distance function.
2025-07-17T07:05:47.1721200Z     
2025-07-17T07:05:47.1721240Z         Args:
2025-07-17T07:05:47.1721400Z             distance_function (Callable, optional): A nonnegative, real-valued function that
2025-07-17T07:05:47.1721520Z                 quantifies the closeness of two tensors. If not specified,
2025-07-17T07:05:47.1721630Z                 `nn.PairwiseDistance` will be used.  Default: ``None``
2025-07-17T07:05:47.1721790Z             margin (float, optional): A nonnegative margin representing the minimum difference
2025-07-17T07:05:47.1721950Z                 between the positive and negative distances required for the loss to be 0. Larger
2025-07-17T07:05:47.1722120Z                 margins penalize cases where the negative examples are not distant enough from the
2025-07-17T07:05:47.1722220Z                 anchors, relative to the positives. Default: :math:`1`.
2025-07-17T07:05:47.1722370Z             swap (bool, optional): Whether to use the distance swap described in the paper
2025-07-17T07:05:47.1722550Z                 `Learning shallow convolutional feature descriptors with triplet losses` by
2025-07-17T07:05:47.1722700Z                 V. Balntas, E. Riba et al. If True, and if the positive example is closer to the
2025-07-17T07:05:47.1722880Z                 negative example than the anchor is, swaps the positive example and the anchor in
2025-07-17T07:05:47.1722960Z                 the loss computation. Default: ``False``.
2025-07-17T07:05:47.1723130Z             reduction (str, optional): Specifies the (optional) reduction to apply to the output:
2025-07-17T07:05:47.1723240Z                 ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied,
2025-07-17T07:05:47.1723360Z                 ``'mean'``: the sum of the output will be divided by the number of
2025-07-17T07:05:47.1723500Z                 elements in the output, ``'sum'``: the output will be summed. Default: ``'mean'``
2025-07-17T07:05:47.1723560Z     
2025-07-17T07:05:47.1723620Z     
2025-07-17T07:05:47.1723670Z         Shape:
2025-07-17T07:05:47.1723810Z             - Input: :math:`(N, *)` where :math:`*` represents any number of additional dimensions
2025-07-17T07:05:47.1723890Z               as supported by the distance function.
2025-07-17T07:05:47.1724050Z             - Output: A Tensor of shape :math:`(N)` if :attr:`reduction` is ``'none'``, or a scalar
2025-07-17T07:05:47.1724100Z               otherwise.
2025-07-17T07:05:47.1724140Z     
2025-07-17T07:05:47.1724180Z         Examples:
2025-07-17T07:05:47.1724220Z     
2025-07-17T07:05:47.1724280Z         >>> # Initialize embeddings
2025-07-17T07:05:47.1724350Z         >>> embedding = nn.Embedding(1000, 128)
2025-07-17T07:05:47.1724420Z         >>> anchor_ids = torch.randint(0, 1000, (1,))
2025-07-17T07:05:47.1724500Z         >>> positive_ids = torch.randint(0, 1000, (1,))
2025-07-17T07:05:47.1724580Z         >>> negative_ids = torch.randint(0, 1000, (1,))
2025-07-17T07:05:47.1724640Z         >>> anchor = embedding(anchor_ids)
2025-07-17T07:05:47.1724710Z         >>> positive = embedding(positive_ids)
2025-07-17T07:05:47.1724780Z         >>> negative = embedding(negative_ids)
2025-07-17T07:05:47.1724820Z         >>>
2025-07-17T07:05:47.1724880Z         >>> # Built-in Distance Function
2025-07-17T07:05:47.1724930Z         >>> triplet_loss = \
2025-07-17T07:05:47.1725100Z         >>>     nn.TripletMarginWithDistanceLoss(distance_function=nn.PairwiseDistance())
2025-07-17T07:05:47.1725190Z         >>> output = triplet_loss(anchor, positive, negative)
2025-07-17T07:05:47.1725250Z         >>> output.backward()
2025-07-17T07:05:47.1725290Z         >>>
2025-07-17T07:05:47.1725350Z         >>> # Custom Distance Function
2025-07-17T07:05:47.1725400Z         >>> def l_infinity(x1, x2):
2025-07-17T07:05:47.1725500Z         >>>     return torch.max(torch.abs(x1 - x2), dim=1).values
2025-07-17T07:05:47.1725550Z         >>>
2025-07-17T07:05:47.1725660Z         >>> # xdoctest: +SKIP("FIXME: Would call backwards a second time")
2025-07-17T07:05:47.1725720Z         >>> triplet_loss = (
2025-07-17T07:05:47.1725880Z         >>>     nn.TripletMarginWithDistanceLoss(distance_function=l_infinity, margin=1.5))
2025-07-17T07:05:47.1725980Z         >>> output = triplet_loss(anchor, positive, negative)
2025-07-17T07:05:47.1726030Z         >>> output.backward()
2025-07-17T07:05:47.1726070Z         >>>
2025-07-17T07:05:47.1726140Z         >>> # Custom Distance Function (Lambda)
2025-07-17T07:05:47.1726190Z         >>> triplet_loss = (
2025-07-17T07:05:47.1726270Z         >>>     nn.TripletMarginWithDistanceLoss(
2025-07-17T07:05:47.1726400Z         >>>         distance_function=lambda x, y: 1.0 - F.cosine_similarity(x, y)))
2025-07-17T07:05:47.1726490Z         >>> output = triplet_loss(anchor, positive, negative)
2025-07-17T07:05:47.1726550Z         >>> output.backward()
2025-07-17T07:05:47.1726590Z     
2025-07-17T07:05:47.1726630Z         Reference:
2025-07-17T07:05:47.1726820Z             V. Balntas, et al.: Learning shallow convolutional feature descriptors with triplet losses:
2025-07-17T07:05:47.1726980Z             https://bmva-archive.org.uk/bmvc/2016/papers/paper119/index.html
2025-07-17T07:05:47.1727030Z         
2025-07-17T07:05:47.1727180Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 17))
2025-07-17T07:05:47.1727240Z     
2025-07-17T07:05:47.1727290Z       warnings.warn(msg)
2025-07-17T07:05:47.1727330Z     
2025-07-17T07:05:47.1727430Z --- Parse Warning: 44 / 136 ---
2025-07-17T07:05:47.1728070Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CTCLoss in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/loss.py line=1852.
2025-07-17T07:05:47.1728220Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1728330Z     The Connectionist Temporal Classification loss.
2025-07-17T07:05:47.1728390Z     
2025-07-17T07:05:47.1728620Z         Calculates loss between a continuous (unsegmented) time series and a target sequence. CTCLoss sums over the
2025-07-17T07:05:47.1728830Z         probability of possible alignments of input to target, producing a loss value which is differentiable
2025-07-17T07:05:47.1729030Z         with respect to each input node. The alignment of input to target is assumed to be "many-to-one", which
2025-07-17T07:05:47.1729210Z         limits the length of the target sequence such that it must be :math:`\leq` the input length.
2025-07-17T07:05:47.1729250Z     
2025-07-17T07:05:47.1729290Z         Args:
2025-07-17T07:05:47.1729390Z             blank (int, optional): blank label. Default :math:`0`.
2025-07-17T07:05:47.1729540Z             reduction (str, optional): Specifies the reduction to apply to the output:
2025-07-17T07:05:47.1729650Z                 ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied,
2025-07-17T07:05:47.1729780Z                 ``'mean'``: the output losses will be divided by the target lengths and
2025-07-17T07:05:47.1729940Z                 then the mean over the batch is taken, ``'sum'``: the output losses will be summed.
2025-07-17T07:05:47.1729990Z                 Default: ``'mean'``
2025-07-17T07:05:47.1730060Z             zero_infinity (bool, optional):
2025-07-17T07:05:47.1730180Z                 Whether to zero infinite losses and the associated gradients.
2025-07-17T07:05:47.1730230Z                 Default: ``False``
2025-07-17T07:05:47.1730350Z                 Infinite losses mainly occur when the inputs are too short
2025-07-17T07:05:47.1730410Z                 to be aligned to the targets.
2025-07-17T07:05:47.1730450Z     
2025-07-17T07:05:47.1730500Z         Shape:
2025-07-17T07:05:47.1730610Z             - Log_probs: Tensor of size :math:`(T, N, C)` or :math:`(T, C)`,
2025-07-17T07:05:47.1730690Z               where :math:`T = \text{input length}`,
2025-07-17T07:05:47.1730760Z               :math:`N = \text{batch size}`, and
2025-07-17T07:05:47.1730860Z               :math:`C = \text{number of classes (including blank)}`.
2025-07-17T07:05:47.1730990Z               The logarithmized probabilities of the outputs (e.g. obtained with
2025-07-17T07:05:47.1731070Z               :func:`torch.nn.functional.log_softmax`).
2025-07-17T07:05:47.1731150Z             - Targets: Tensor of size :math:`(N, S)` or
2025-07-17T07:05:47.1731250Z               :math:`(\operatorname{sum}(\text{target\_lengths}))`,
2025-07-17T07:05:47.1731330Z               where :math:`N = \text{batch size}` and
2025-07-17T07:05:47.1731430Z               :math:`S = \text{max target length, if shape is } (N, S)`.
2025-07-17T07:05:47.1731550Z               It represents the target sequences. Each element in the target
2025-07-17T07:05:47.1731690Z               sequence is a class index. And the target index cannot be blank (default=0).
2025-07-17T07:05:47.1731790Z               In the :math:`(N, S)` form, targets are padded to the
2025-07-17T07:05:47.1731900Z               length of the longest sequence, and stacked.
2025-07-17T07:05:47.1732020Z               In the :math:`(\operatorname{sum}(\text{target\_lengths}))` form,
2025-07-17T07:05:47.1732100Z               the targets are assumed to be un-padded and
2025-07-17T07:05:47.1732200Z               concatenated within 1 dimension.
2025-07-17T07:05:47.1732330Z             - Input_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`,
2025-07-17T07:05:47.1732450Z               where :math:`N = \text{batch size}`. It represents the lengths of the
2025-07-17T07:05:47.1732570Z               inputs (must each be :math:`\leq T`). And the lengths are specified
2025-07-17T07:05:47.1732710Z               for each sequence to achieve masking under the assumption that sequences
2025-07-17T07:05:47.1732770Z               are padded to equal lengths.
2025-07-17T07:05:47.1732900Z             - Target_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`,
2025-07-17T07:05:47.1733040Z               where :math:`N = \text{batch size}`. It represents lengths of the targets.
2025-07-17T07:05:47.1733200Z               Lengths are specified for each sequence to achieve masking under the
2025-07-17T07:05:47.1733340Z               assumption that sequences are padded to equal lengths. If target shape is
2025-07-17T07:05:47.1733450Z               :math:`(N,S)`, target_lengths are effectively the stop index
2025-07-17T07:05:47.1733600Z               :math:`s_n` for each target sequence, such that ``target_n = targets[n,0:s_n]`` for
2025-07-17T07:05:47.1733710Z               each target in a batch. Lengths must each be :math:`\leq S`
2025-07-17T07:05:47.1733860Z               If the targets are given as a 1d tensor that is the concatenation of individual
2025-07-17T07:05:47.1734000Z               targets, the target_lengths must add up to the total length of the tensor.
2025-07-17T07:05:47.1734120Z             - Output: scalar if :attr:`reduction` is ``'mean'`` (default) or
2025-07-17T07:05:47.1734260Z               ``'sum'``. If :attr:`reduction` is ``'none'``, then :math:`(N)` if input is batched or
2025-07-17T07:05:47.1734380Z               :math:`()` if input is unbatched, where :math:`N = \text{batch size}`.
2025-07-17T07:05:47.1734430Z     
2025-07-17T07:05:47.1734470Z         Examples:
2025-07-17T07:05:47.1734510Z     
2025-07-17T07:05:47.1734570Z             >>> # Target are to be padded
2025-07-17T07:05:47.1734640Z             >>> T = 50  # Input sequence length
2025-07-17T07:05:47.1734720Z             >>> C = 20  # Number of classes (including blank)
2025-07-17T07:05:47.1734770Z             >>> N = 16  # Batch size
2025-07-17T07:05:47.1734910Z             >>> S = 30  # Target sequence length of longest target in batch (padding length)
2025-07-17T07:05:47.1735020Z             >>> S_min = 10  # Minimum target length, for demonstration purposes
2025-07-17T07:05:47.1735060Z             >>>
2025-07-17T07:05:47.1735180Z             >>> # Initialize random batch of input vectors, for *size = (T,N,C)
2025-07-17T07:05:47.1735310Z             >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_()
2025-07-17T07:05:47.1735360Z             >>>
2025-07-17T07:05:47.1735480Z             >>> # Initialize random batch of targets (0 = blank, 1:C = classes)
2025-07-17T07:05:47.1735610Z             >>> target = torch.randint(low=1, high=C, size=(N, S), dtype=torch.long)
2025-07-17T07:05:47.1735650Z             >>>
2025-07-17T07:05:47.1735780Z             >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long)
2025-07-17T07:05:47.1735850Z             >>> target_lengths = torch.randint(
2025-07-17T07:05:47.1735900Z             ...     low=S_min,
2025-07-17T07:05:47.1735950Z             ...     high=S,
2025-07-17T07:05:47.1736000Z             ...     size=(N,),
2025-07-17T07:05:47.1736060Z             ...     dtype=torch.long,
2025-07-17T07:05:47.1736100Z             ... )
2025-07-17T07:05:47.1736150Z             >>> ctc_loss = nn.CTCLoss()
2025-07-17T07:05:47.1736270Z             >>> loss = ctc_loss(input, target, input_lengths, target_lengths)
2025-07-17T07:05:47.1736340Z             >>> loss.backward()
2025-07-17T07:05:47.1736390Z             >>>
2025-07-17T07:05:47.1736430Z             >>>
2025-07-17T07:05:47.1736490Z             >>> # Target are to be un-padded
2025-07-17T07:05:47.1736580Z             >>> T = 50  # Input sequence length
2025-07-17T07:05:47.1736660Z             >>> C = 20  # Number of classes (including blank)
2025-07-17T07:05:47.1736710Z             >>> N = 16  # Batch size
2025-07-17T07:05:47.1736750Z             >>>
2025-07-17T07:05:47.1736870Z             >>> # Initialize random batch of input vectors, for *size = (T,N,C)
2025-07-17T07:05:47.1737000Z             >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_()
2025-07-17T07:05:47.1737130Z             >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long)
2025-07-17T07:05:47.1737180Z             >>>
2025-07-17T07:05:47.1737320Z             >>> # Initialize random batch of targets (0 = blank, 1:C = classes)
2025-07-17T07:05:47.1737490Z             >>> target_lengths = torch.randint(low=1, high=T, size=(N,), dtype=torch.long)
2025-07-17T07:05:47.1737570Z             >>> target = torch.randint(
2025-07-17T07:05:47.1737620Z             ...     low=1,
2025-07-17T07:05:47.1737670Z             ...     high=C,
2025-07-17T07:05:47.1737740Z             ...     size=(sum(target_lengths),),
2025-07-17T07:05:47.1737800Z             ...     dtype=torch.long,
2025-07-17T07:05:47.1737840Z             ... )
2025-07-17T07:05:47.1737890Z             >>> ctc_loss = nn.CTCLoss()
2025-07-17T07:05:47.1738000Z             >>> loss = ctc_loss(input, target, input_lengths, target_lengths)
2025-07-17T07:05:47.1738060Z             >>> loss.backward()
2025-07-17T07:05:47.1738100Z             >>>
2025-07-17T07:05:47.1738140Z             >>>
2025-07-17T07:05:47.1738250Z             >>> # Target are to be un-padded and unbatched (effectively N=1)
2025-07-17T07:05:47.1738320Z             >>> T = 50  # Input sequence length
2025-07-17T07:05:47.1738400Z             >>> C = 20  # Number of classes (including blank)
2025-07-17T07:05:47.1738440Z             >>>
2025-07-17T07:05:47.1738560Z             >>> # Initialize random batch of input vectors, for *size = (T,C)
2025-07-17T07:05:47.1738640Z             >>> # xdoctest: +SKIP("FIXME: error in doctest")
2025-07-17T07:05:47.1738760Z             >>> input = torch.randn(T, C).log_softmax(1).detach().requires_grad_()
2025-07-17T07:05:47.1738850Z             >>> input_lengths = torch.tensor(T, dtype=torch.long)
2025-07-17T07:05:47.1738890Z             >>>
2025-07-17T07:05:47.1739010Z             >>> # Initialize random batch of targets (0 = blank, 1:C = classes)
2025-07-17T07:05:47.1739150Z             >>> target_lengths = torch.randint(low=1, high=T, size=(), dtype=torch.long)
2025-07-17T07:05:47.1739210Z             >>> target = torch.randint(
2025-07-17T07:05:47.1739250Z             ...     low=1,
2025-07-17T07:05:47.1739300Z             ...     high=C,
2025-07-17T07:05:47.1739360Z             ...     size=(target_lengths,),
2025-07-17T07:05:47.1739420Z             ...     dtype=torch.long,
2025-07-17T07:05:47.1739470Z             ... )
2025-07-17T07:05:47.1739520Z             >>> ctc_loss = nn.CTCLoss()
2025-07-17T07:05:47.1739630Z             >>> loss = ctc_loss(input, target, input_lengths, target_lengths)
2025-07-17T07:05:47.1739690Z             >>> loss.backward()
2025-07-17T07:05:47.1739720Z     
2025-07-17T07:05:47.1739770Z         Reference:
2025-07-17T07:05:47.1739880Z             A. Graves et al.: Connectionist Temporal Classification:
2025-07-17T07:05:47.1740010Z             Labelling Unsegmented Sequence Data with Recurrent Neural Networks:
2025-07-17T07:05:47.1740110Z             https://www.cs.toronto.edu/~graves/icml_2006.pdf
2025-07-17T07:05:47.1740150Z     
2025-07-17T07:05:47.1740190Z         Note:
2025-07-17T07:05:47.1740340Z             In order to use CuDNN, the following must be satisfied: :attr:`targets` must be
2025-07-17T07:05:47.1740490Z             in concatenated format, all :attr:`input_lengths` must be `T`.  :math:`blank=0`,
2025-07-17T07:05:47.1740640Z             :attr:`target_lengths` :math:`\leq 256`, the integer arguments must be of
2025-07-17T07:05:47.1740700Z             dtype :attr:`torch.int32`.
2025-07-17T07:05:47.1740770Z     
2025-07-17T07:05:47.1740930Z             The regular implementation uses the (more common in PyTorch) `torch.long` dtype.
2025-07-17T07:05:47.1740970Z     
2025-07-17T07:05:47.1741010Z     
2025-07-17T07:05:47.1741050Z         Note:
2025-07-17T07:05:47.1741200Z             In some circumstances when using the CUDA backend with CuDNN, this operator
2025-07-17T07:05:47.1741350Z             may select a nondeterministic algorithm to increase performance. If this is
2025-07-17T07:05:47.1741490Z             undesirable, you can try to make the operation deterministic (potentially at
2025-07-17T07:05:47.1741630Z             a performance cost) by setting ``torch.backends.cudnn.deterministic =
2025-07-17T07:05:47.1741700Z             True``.
2025-07-17T07:05:47.1741840Z             Please see the notes on :doc:`/notes/randomness` for background.
2025-07-17T07:05:47.1741880Z         
2025-07-17T07:05:47.1742030Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1742070Z     
2025-07-17T07:05:47.1742130Z       warnings.warn(msg)
2025-07-17T07:05:47.1742170Z     
2025-07-17T07:05:47.1742270Z --- Parse Warning: 45 / 136 ---
2025-07-17T07:05:47.1742960Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Transformer.forward in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py line=186.
2025-07-17T07:05:47.1743110Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1743200Z     Take in and process masked source/target sequences.
2025-07-17T07:05:47.1743240Z     
2025-07-17T07:05:47.1743290Z             .. note::
2025-07-17T07:05:47.1743330Z     
2025-07-17T07:05:47.1743560Z                 If a boolean tensor is provided for any of the [src/tgt/memory]_mask arguments, positions with a ``True`` value are
2025-07-17T07:05:47.1743650Z                 not allowed to participate in the attention,
2025-07-17T07:05:47.1743770Z                 which is the opposite of the definition for :attr:`attn_mask`
2025-07-17T07:05:47.1743890Z                 in :func:`torch.nn.functional.scaled_dot_product_attention`.
2025-07-17T07:05:47.1743930Z     
2025-07-17T07:05:47.1743970Z             Args:
2025-07-17T07:05:47.1744050Z                 src: the sequence to the encoder (required).
2025-07-17T07:05:47.1744130Z                 tgt: the sequence to the decoder (required).
2025-07-17T07:05:47.1744240Z                 src_mask: the additive mask for the src sequence (optional).
2025-07-17T07:05:47.1744360Z                 tgt_mask: the additive mask for the tgt sequence (optional).
2025-07-17T07:05:47.1744480Z                 memory_mask: the additive mask for the encoder output (optional).
2025-07-17T07:05:47.1744620Z                 src_key_padding_mask: the Tensor mask for src keys per batch (optional).
2025-07-17T07:05:47.1744760Z                 tgt_key_padding_mask: the Tensor mask for tgt keys per batch (optional).
2025-07-17T07:05:47.1744910Z                 memory_key_padding_mask: the Tensor mask for memory keys per batch (optional).
2025-07-17T07:05:47.1745030Z                 src_is_causal: If specified, applies a causal mask as ``src_mask``.
2025-07-17T07:05:47.1745130Z                     Default: ``None``; try to detect a causal mask.
2025-07-17T07:05:47.1745180Z                     Warning:
2025-07-17T07:05:47.1745270Z                     ``src_is_causal`` provides a hint that ``src_mask`` is
2025-07-17T07:05:47.1745390Z                     the causal mask. Providing incorrect hints can result in
2025-07-17T07:05:47.1745490Z                     incorrect execution, including forward and backward
2025-07-17T07:05:47.1745610Z                     compatibility.
2025-07-17T07:05:47.1745730Z                 tgt_is_causal: If specified, applies a causal mask as ``tgt_mask``.
2025-07-17T07:05:47.1745830Z                     Default: ``None``; try to detect a causal mask.
2025-07-17T07:05:47.1745890Z                     Warning:
2025-07-17T07:05:47.1745990Z                     ``tgt_is_causal`` provides a hint that ``tgt_mask`` is
2025-07-17T07:05:47.1746100Z                     the causal mask. Providing incorrect hints can result in
2025-07-17T07:05:47.1746200Z                     incorrect execution, including forward and backward
2025-07-17T07:05:47.1746250Z                     compatibility.
2025-07-17T07:05:47.1746360Z                 memory_is_causal: If specified, applies a causal mask as
2025-07-17T07:05:47.1746410Z                     ``memory_mask``.
2025-07-17T07:05:47.1746470Z                     Default: ``False``.
2025-07-17T07:05:47.1746540Z                     Warning:
2025-07-17T07:05:47.1746650Z                     ``memory_is_causal`` provides a hint that
2025-07-17T07:05:47.1746750Z                     ``memory_mask`` is the causal mask. Providing incorrect
2025-07-17T07:05:47.1746850Z                     hints can result in incorrect execution, including
2025-07-17T07:05:47.1746920Z                     forward and backward compatibility.
2025-07-17T07:05:47.1746960Z     
2025-07-17T07:05:47.1747010Z             Shape:
2025-07-17T07:05:47.1747160Z                 - src: :math:`(S, E)` for unbatched input, :math:`(S, N, E)` if `batch_first=False` or
2025-07-17T07:05:47.1747230Z                   `(N, S, E)` if `batch_first=True`.
2025-07-17T07:05:47.1747370Z                 - tgt: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or
2025-07-17T07:05:47.1747450Z                   `(N, T, E)` if `batch_first=True`.
2025-07-17T07:05:47.1747560Z                 - src_mask: :math:`(S, S)` or :math:`(N\cdot\text{num\_heads}, S, S)`.
2025-07-17T07:05:47.1747680Z                 - tgt_mask: :math:`(T, T)` or :math:`(N\cdot\text{num\_heads}, T, T)`.
2025-07-17T07:05:47.1747740Z                 - memory_mask: :math:`(T, S)`.
2025-07-17T07:05:47.1747890Z                 - src_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`.
2025-07-17T07:05:47.1748030Z                 - tgt_key_padding_mask: :math:`(T)` for unbatched input otherwise :math:`(N, T)`.
2025-07-17T07:05:47.1748190Z                 - memory_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`.
2025-07-17T07:05:47.1748230Z     
2025-07-17T07:05:47.1748420Z                 Note: [src/tgt/memory]_mask ensures that position :math:`i` is allowed to attend the unmasked
2025-07-17T07:05:47.1748540Z                 positions. If a BoolTensor is provided, positions with ``True``
2025-07-17T07:05:47.1748700Z                 are not allowed to attend while ``False`` values will be unchanged. If a FloatTensor
2025-07-17T07:05:47.1748800Z                 is provided, it will be added to the attention weight.
2025-07-17T07:05:47.1748990Z                 [src/tgt/memory]_key_padding_mask provides specified elements in the key to be ignored by
2025-07-17T07:05:47.1749120Z                 the attention. If a BoolTensor is provided, the positions with the
2025-07-17T07:05:47.1749310Z                 value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged.
2025-07-17T07:05:47.1749350Z     
2025-07-17T07:05:47.1749500Z                 - output: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or
2025-07-17T07:05:47.1749570Z                   `(N, T, E)` if `batch_first=True`.
2025-07-17T07:05:47.1749610Z     
2025-07-17T07:05:47.1749760Z                 Note: Due to the multi-head attention architecture in the transformer model,
2025-07-17T07:05:47.1749900Z                 the output sequence length of a transformer is same as the input sequence
2025-07-17T07:05:47.1749980Z                 (i.e. target) length of the decoder.
2025-07-17T07:05:47.1750020Z     
2025-07-17T07:05:47.1750230Z                 where :math:`S` is the source sequence length, :math:`T` is the target sequence length, :math:`N` is the
2025-07-17T07:05:47.1750320Z                 batch size, :math:`E` is the feature number
2025-07-17T07:05:47.1750390Z     
2025-07-17T07:05:47.1750430Z             Examples:
2025-07-17T07:05:47.1750490Z                 >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1750560Z                 >>> output = transformer_model(
2025-07-17T07:05:47.1750650Z                 ...     src, tgt, src_mask=src_mask, tgt_mask=tgt_mask
2025-07-17T07:05:47.1750690Z                 ... )
2025-07-17T07:05:47.1750730Z             
2025-07-17T07:05:47.1750880Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1750920Z     
2025-07-17T07:05:47.1750980Z       warnings.warn(msg)
2025-07-17T07:05:47.1751010Z     
2025-07-17T07:05:47.1751130Z --- Parse Warning: 46 / 136 ---
2025-07-17T07:05:47.1751800Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=EmbeddingBag in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/sparse.py line=272.
2025-07-17T07:05:47.1751960Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1752150Z     Compute sums or means of 'bags' of embeddings, without instantiating the intermediate embeddings.
2025-07-17T07:05:47.1752190Z     
2025-07-17T07:05:47.1752380Z         For bags of constant length, no :attr:`per_sample_weights`, no indices equal to :attr:`padding_idx`,
2025-07-17T07:05:47.1752450Z         and with 2D inputs, this class
2025-07-17T07:05:47.1752480Z     
2025-07-17T07:05:47.1752670Z             * with ``mode="sum"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.sum(dim=1)``,
2025-07-17T07:05:47.1752860Z             * with ``mode="mean"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.mean(dim=1)``,
2025-07-17T07:05:47.1753040Z             * with ``mode="max"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.max(dim=1)``.
2025-07-17T07:05:47.1753080Z     
2025-07-17T07:05:47.1753290Z         However, :class:`~torch.nn.EmbeddingBag` is much more time and memory efficient than using a chain of these
2025-07-17T07:05:47.1753330Z         operations.
2025-07-17T07:05:47.1753370Z     
2025-07-17T07:05:47.1753530Z         EmbeddingBag also supports per-sample weights as an argument to the forward
2025-07-17T07:05:47.1753670Z         pass. This scales the output of the Embedding before performing a weighted
2025-07-17T07:05:47.1753820Z         reduction as specified by ``mode``. If :attr:`per_sample_weights` is passed, the
2025-07-17T07:05:47.1753960Z         only supported ``mode`` is ``"sum"``, which computes a weighted sum according to
2025-07-17T07:05:47.1754020Z         :attr:`per_sample_weights`.
2025-07-17T07:05:47.1754060Z     
2025-07-17T07:05:47.1754100Z         Args:
2025-07-17T07:05:47.1754210Z             num_embeddings (int): size of the dictionary of embeddings
2025-07-17T07:05:47.1754310Z             embedding_dim (int): the size of each embedding vector
2025-07-17T07:05:47.1754500Z             max_norm (float, optional): If given, each embedding vector with norm larger than :attr:`max_norm`
2025-07-17T07:05:47.1754610Z                                         is renormalized to have norm :attr:`max_norm`.
2025-07-17T07:05:47.1754810Z             norm_type (float, optional): The p of the p-norm to compute for the :attr:`max_norm` option. Default ``2``.
2025-07-17T07:05:47.1755000Z             scale_grad_by_freq (bool, optional): if given, this will scale gradients by the inverse of frequency of
2025-07-17T07:05:47.1755100Z                                                     the words in the mini-batch. Default ``False``.
2025-07-17T07:05:47.1755250Z                                                     Note: this option is not supported when ``mode="max"``.
2025-07-17T07:05:47.1755410Z             mode (str, optional): ``"sum"``, ``"mean"`` or ``"max"``. Specifies the way to reduce the bag.
2025-07-17T07:05:47.1755540Z                                      ``"sum"`` computes the weighted sum, taking :attr:`per_sample_weights`
2025-07-17T07:05:47.1755700Z                                      into consideration. ``"mean"`` computes the average of the values
2025-07-17T07:05:47.1755810Z                                      in the bag, ``"max"`` computes the max value over each bag.
2025-07-17T07:05:47.1755880Z                                      Default: ``"mean"``
2025-07-17T07:05:47.1756070Z             sparse (bool, optional): if ``True``, gradient w.r.t. :attr:`weight` matrix will be a sparse tensor. See
2025-07-17T07:05:47.1756230Z                                      Notes for more details regarding sparse gradients. Note: this option is not
2025-07-17T07:05:47.1756370Z                                      supported when ``mode="max"``.
2025-07-17T07:05:47.1756620Z             include_last_offset (bool, optional): if ``True``, :attr:`offsets` has one additional element, where the last element
2025-07-17T07:05:47.1756750Z                                           is equivalent to the size of `indices`. This matches the CSR format.
2025-07-17T07:05:47.1756950Z             padding_idx (int, optional): If specified, the entries at :attr:`padding_idx` do not contribute to the
2025-07-17T07:05:47.1757120Z                                          gradient; therefore, the embedding vector at :attr:`padding_idx` is not updated
2025-07-17T07:05:47.1757260Z                                          during training, i.e. it remains as a fixed "pad". For a newly constructed
2025-07-17T07:05:47.1757430Z                                          EmbeddingBag, the embedding vector at :attr:`padding_idx` will default to all
2025-07-17T07:05:47.1757580Z                                          zeros, but can be updated to another value to be used as the padding vector.
2025-07-17T07:05:47.1757730Z                                          Note that the embedding vector at :attr:`padding_idx` is excluded from the
2025-07-17T07:05:47.1757790Z                                          reduction.
2025-07-17T07:05:47.1757840Z     
2025-07-17T07:05:47.1757880Z         Attributes:
2025-07-17T07:05:47.1758070Z             weight (Tensor): the learnable weights of the module of shape `(num_embeddings, embedding_dim)`
2025-07-17T07:05:47.1758160Z                              initialized from :math:`\mathcal{N}(0, 1)`.
2025-07-17T07:05:47.1758200Z     
2025-07-17T07:05:47.1758250Z         Examples::
2025-07-17T07:05:47.1758280Z     
2025-07-17T07:05:47.1758390Z             >>> # an EmbeddingBag module containing 10 tensors of size 3
2025-07-17T07:05:47.1758480Z             >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum')
2025-07-17T07:05:47.1758560Z             >>> # a batch of 2 samples of 4 indices each
2025-07-17T07:05:47.1758680Z             >>> input = torch.tensor([1, 2, 4, 5, 4, 3, 2, 9], dtype=torch.long)
2025-07-17T07:05:47.1758770Z             >>> offsets = torch.tensor([0, 4], dtype=torch.long)
2025-07-17T07:05:47.1758860Z             >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-07-17T07:05:47.1758930Z             >>> embedding_sum(input, offsets)
2025-07-17T07:05:47.1758990Z             tensor([[-0.8861, -5.4350, -0.0523],
2025-07-17T07:05:47.1759050Z                     [ 1.1306, -2.5798, -1.0044]])
2025-07-17T07:05:47.1759090Z     
2025-07-17T07:05:47.1759160Z             >>> # Example with padding_idx
2025-07-17T07:05:47.1759280Z             >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum', padding_idx=2)
2025-07-17T07:05:47.1759390Z             >>> input = torch.tensor([2, 2, 2, 2, 4, 3, 2, 9], dtype=torch.long)
2025-07-17T07:05:47.1759480Z             >>> offsets = torch.tensor([0, 4], dtype=torch.long)
2025-07-17T07:05:47.1759550Z             >>> embedding_sum(input, offsets)
2025-07-17T07:05:47.1759610Z             tensor([[ 0.0000,  0.0000,  0.0000],
2025-07-17T07:05:47.1759690Z                     [-0.7082,  3.2145, -2.6251]])
2025-07-17T07:05:47.1759730Z     
2025-07-17T07:05:47.1759830Z             >>> # An EmbeddingBag can be loaded from an Embedding like so
2025-07-17T07:05:47.1759950Z             >>> embedding = nn.Embedding(10, 3, padding_idx=2)
2025-07-17T07:05:47.1760040Z             >>> embedding_sum = nn.EmbeddingBag.from_pretrained(
2025-07-17T07:05:47.1760100Z                     embedding.weight,
2025-07-17T07:05:47.1760180Z                     padding_idx=embedding.padding_idx,
2025-07-17T07:05:47.1760230Z                     mode='sum')
2025-07-17T07:05:47.1760270Z         
2025-07-17T07:05:47.1760420Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1760460Z     
2025-07-17T07:05:47.1760510Z       warnings.warn(msg)
2025-07-17T07:05:47.1760550Z     
2025-07-17T07:05:47.1760670Z --- Parse Warning: 47 / 136 ---
2025-07-17T07:05:47.1761380Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=batch_isend_irecv in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=2706.
2025-07-17T07:05:47.1761540Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1761580Z     
2025-07-17T07:05:47.1761730Z     Send or Receive a batch of tensors asynchronously and return a list of requests.
2025-07-17T07:05:47.1761770Z     
2025-07-17T07:05:47.1761910Z     Process each of the operations in ``p2p_op_list`` and return the corresponding
2025-07-17T07:05:47.1762040Z     requests. NCCL, Gloo, and UCC backend are currently supported.
2025-07-17T07:05:47.1762070Z     
2025-07-17T07:05:47.1762120Z     Args:
2025-07-17T07:05:47.1762250Z         p2p_op_list: A list of point-to-point operations(type of each operator is
2025-07-17T07:05:47.1762400Z             ``torch.distributed.P2POp``). The order of the isend/irecv in the list
2025-07-17T07:05:47.1762520Z             matters and it needs to match with corresponding isend/irecv on the
2025-07-17T07:05:47.1762570Z             remote end.
2025-07-17T07:05:47.1762610Z     
2025-07-17T07:05:47.1762650Z     Returns:
2025-07-17T07:05:47.1762800Z         A list of distributed request objects returned by calling the corresponding
2025-07-17T07:05:47.1762850Z         op in the op_list.
2025-07-17T07:05:47.1762890Z     
2025-07-17T07:05:47.1762930Z     Examples:
2025-07-17T07:05:47.1763000Z         >>> # xdoctest: +SKIP("no rank")
2025-07-17T07:05:47.1763110Z         >>> send_tensor = torch.arange(2, dtype=torch.float32) + 2 * rank
2025-07-17T07:05:47.1763210Z         >>> recv_tensor = torch.randn(2, dtype=torch.float32)
2025-07-17T07:05:47.1763330Z         >>> send_op = dist.P2POp(dist.isend, send_tensor, (rank + 1) % world_size)
2025-07-17T07:05:47.1763390Z         >>> recv_op = dist.P2POp(
2025-07-17T07:05:47.1763500Z         ...     dist.irecv, recv_tensor, (rank - 1 + world_size) % world_size
2025-07-17T07:05:47.1763550Z         ... )
2025-07-17T07:05:47.1763630Z         >>> reqs = batch_isend_irecv([send_op, recv_op])
2025-07-17T07:05:47.1763680Z         >>> for req in reqs:
2025-07-17T07:05:47.1763730Z         >>>     req.wait()
2025-07-17T07:05:47.1763770Z         >>> recv_tensor
2025-07-17T07:05:47.1763830Z         tensor([2, 3])     # Rank 0
2025-07-17T07:05:47.1763880Z         tensor([0, 1])     # Rank 1
2025-07-17T07:05:47.1763920Z     
2025-07-17T07:05:47.1764070Z     .. note:: Note that when this API is used with the NCCL PG backend, users must set
2025-07-17T07:05:47.1764200Z         the current GPU device with `torch.cuda.set_device`, otherwise it will
2025-07-17T07:05:47.1764260Z         lead to unexpected hang issues.
2025-07-17T07:05:47.1764300Z     
2025-07-17T07:05:47.1764420Z         In addition, if this API is the first collective call in the ``group``
2025-07-17T07:05:47.1764590Z         passed to ``dist.P2POp``, all ranks of the ``group`` must participate in
2025-07-17T07:05:47.1764720Z         this API call; otherwise, the behavior is undefined. If this API call is
2025-07-17T07:05:47.1764860Z         not the first collective call in the ``group``, batched P2P operations
2025-07-17T07:05:47.1764990Z         involving only a subset of ranks of the ``group`` are allowed.
2025-07-17T07:05:47.1765030Z     
2025-07-17T07:05:47.1765180Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1765220Z     
2025-07-17T07:05:47.1765270Z       warnings.warn(msg)
2025-07-17T07:05:47.1765310Z     
2025-07-17T07:05:47.1765410Z --- Parse Warning: 48 / 136 ---
2025-07-17T07:05:47.1766120Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_reduce in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=2838.
2025-07-17T07:05:47.1766290Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1766330Z     
2025-07-17T07:05:47.1766500Z     Reduces the tensor data across all machines in a way that all get the final result.
2025-07-17T07:05:47.1766540Z     
2025-07-17T07:05:47.1766680Z     After the call ``tensor`` is going to be bitwise identical in all processes.
2025-07-17T07:05:47.1766710Z     
2025-07-17T07:05:47.1766780Z     Complex tensors are supported.
2025-07-17T07:05:47.1766820Z     
2025-07-17T07:05:47.1766860Z     Args:
2025-07-17T07:05:47.1766980Z         tensor (Tensor): Input and output of the collective. The function
2025-07-17T07:05:47.1767040Z             operates in-place.
2025-07-17T07:05:47.1767100Z         op (optional): One of the values from
2025-07-17T07:05:47.1767170Z             ``torch.distributed.ReduceOp``
2025-07-17T07:05:47.1767290Z             enum.  Specifies an operation used for element-wise reductions.
2025-07-17T07:05:47.1767430Z         group (ProcessGroup, optional): The process group to work on. If None,
2025-07-17T07:05:47.1767510Z             the default process group will be used.
2025-07-17T07:05:47.1767630Z         async_op (bool, optional): Whether this op should be an async op
2025-07-17T07:05:47.1767670Z     
2025-07-17T07:05:47.1767710Z     Returns:
2025-07-17T07:05:47.1767790Z         Async work handle, if async_op is set to True.
2025-07-17T07:05:47.1767880Z         None, if not async_op or if not part of the group
2025-07-17T07:05:47.1767920Z     
2025-07-17T07:05:47.1767960Z     Examples:
2025-07-17T07:05:47.1768020Z         >>> # xdoctest: +SKIP("no rank")
2025-07-17T07:05:47.1768100Z         >>> # All tensors below are of torch.int64 type.
2025-07-17T07:05:47.1768170Z         >>> # We have 2 process groups, 2 ranks.
2025-07-17T07:05:47.1768240Z         >>> device = torch.device(f"cuda:{rank}")
2025-07-17T07:05:47.1768380Z         >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank
2025-07-17T07:05:47.1771770Z         >>> tensor
2025-07-17T07:05:47.1771840Z         tensor([1, 2], device='cuda:0') # Rank 0
2025-07-17T07:05:47.1771910Z         tensor([3, 4], device='cuda:1') # Rank 1
2025-07-17T07:05:47.1771990Z         >>> dist.all_reduce(tensor, op=ReduceOp.SUM)
2025-07-17T07:05:47.1772030Z         >>> tensor
2025-07-17T07:05:47.1772100Z         tensor([4, 6], device='cuda:0') # Rank 0
2025-07-17T07:05:47.1772160Z         tensor([4, 6], device='cuda:1') # Rank 1
2025-07-17T07:05:47.1772200Z     
2025-07-17T07:05:47.1772290Z         >>> # All tensors below are of torch.cfloat type.
2025-07-17T07:05:47.1772350Z         >>> # We have 2 process groups, 2 ranks.
2025-07-17T07:05:47.1772410Z         >>> tensor = torch.tensor(
2025-07-17T07:05:47.1772500Z         ...     [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device
2025-07-17T07:05:47.1772560Z         ... ) + 2 * rank * (1 + 1j)
2025-07-17T07:05:47.1772600Z         >>> tensor
2025-07-17T07:05:47.1772780Z         tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0
2025-07-17T07:05:47.1772860Z         tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1
2025-07-17T07:05:47.1772940Z         >>> dist.all_reduce(tensor, op=ReduceOp.SUM)
2025-07-17T07:05:47.1773020Z         >>> tensor
2025-07-17T07:05:47.1773100Z         tensor([4.+4.j, 6.+6.j], device='cuda:0') # Rank 0
2025-07-17T07:05:47.1773180Z         tensor([4.+4.j, 6.+6.j], device='cuda:1') # Rank 1
2025-07-17T07:05:47.1773210Z     
2025-07-17T07:05:47.1773260Z     
2025-07-17T07:05:47.1773410Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1773450Z     
2025-07-17T07:05:47.1773500Z       warnings.warn(msg)
2025-07-17T07:05:47.1773540Z     
2025-07-17T07:05:47.1773650Z --- Parse Warning: 49 / 136 ---
2025-07-17T07:05:47.1774350Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=gather_object in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=3198.
2025-07-17T07:05:47.1774530Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1774570Z     
2025-07-17T07:05:47.1774700Z     Gathers picklable objects from the whole group in a single process.
2025-07-17T07:05:47.1774740Z     
2025-07-17T07:05:47.1774880Z     Similar to :func:`gather`, but Python objects can be passed in. Note that the
2025-07-17T07:05:47.1774970Z     object must be picklable in order to be gathered.
2025-07-17T07:05:47.1775010Z     
2025-07-17T07:05:47.1775050Z     Args:
2025-07-17T07:05:47.1775130Z         obj (Any): Input object. Must be picklable.
2025-07-17T07:05:47.1775260Z         object_gather_list (list[Any]): Output list. On the ``dst`` rank, it
2025-07-17T07:05:47.1775370Z             should be correctly sized as the size of the group for this
2025-07-17T07:05:47.1775500Z             collective and will contain the output. Must be ``None`` on non-dst
2025-07-17T07:05:47.1775560Z             ranks. (default is ``None``)
2025-07-17T07:05:47.1775760Z         dst (int, optional): Destination rank on global process group (regardless of ``group`` argument).
2025-07-17T07:05:47.1775880Z             (If both ``dst`` and ``group_dst`` are None, default is global rank 0)
2025-07-17T07:05:47.1776010Z         group: (ProcessGroup, optional): The process group to work on. If None,
2025-07-17T07:05:47.1776130Z             the default process group will be used. Default is ``None``.
2025-07-17T07:05:47.1776340Z         group_dst (int, optional): Destination rank on ``group``.  Invalid to specify both ``dst`` and ``group_dst``
2025-07-17T07:05:47.1776380Z     
2025-07-17T07:05:47.1776420Z     Returns:
2025-07-17T07:05:47.1776530Z         None. On the ``dst`` rank, ``object_gather_list`` will contain the
2025-07-17T07:05:47.1776590Z         output of the collective.
2025-07-17T07:05:47.1776630Z     
2025-07-17T07:05:47.1776760Z     .. note:: Note that this API differs slightly from the gather collective
2025-07-17T07:05:47.1776890Z         since it does not provide an async_op handle and thus will be a blocking
2025-07-17T07:05:47.1776930Z         call.
2025-07-17T07:05:47.1776970Z     
2025-07-17T07:05:47.1777110Z     .. note:: For NCCL-based processed groups, internal tensor representations
2025-07-17T07:05:47.1777240Z         of objects must be moved to the GPU device before communication takes
2025-07-17T07:05:47.1777320Z         place. In this case, the device used is given by
2025-07-17T07:05:47.1777450Z         ``torch.cuda.current_device()`` and it is the user's responsibility to
2025-07-17T07:05:47.1777570Z         ensure that this is set so that each rank has an individual GPU, via
2025-07-17T07:05:47.1777630Z         ``torch.cuda.set_device()``.
2025-07-17T07:05:47.1777670Z     
2025-07-17T07:05:47.1777720Z     .. warning::
2025-07-17T07:05:47.1777860Z         Object collectives have a number of serious performance and scalability
2025-07-17T07:05:47.1777990Z         limitations.  See :ref:`object_collectives` for details.
2025-07-17T07:05:47.1778030Z     
2025-07-17T07:05:47.1778080Z     .. warning::
2025-07-17T07:05:47.1778200Z         :func:`gather_object` uses ``pickle`` module implicitly, which is
2025-07-17T07:05:47.1778350Z         known to be insecure. It is possible to construct malicious pickle data
2025-07-17T07:05:47.1778480Z         which will execute arbitrary code during unpickling. Only call this
2025-07-17T07:05:47.1778540Z         function with data you trust.
2025-07-17T07:05:47.1778580Z     
2025-07-17T07:05:47.1778630Z     .. warning::
2025-07-17T07:05:47.1778760Z         Calling :func:`gather_object` with GPU tensors is not well supported
2025-07-17T07:05:47.1778890Z         and inefficient as it incurs GPU -> CPU transfer since tensors would be
2025-07-17T07:05:47.1778990Z         pickled. Please consider using :func:`gather` instead.
2025-07-17T07:05:47.1779060Z     
2025-07-17T07:05:47.1779140Z     Example::
2025-07-17T07:05:47.1779220Z         >>> # xdoctest: +SKIP("need process group init")
2025-07-17T07:05:47.1779330Z         >>> # Note: Process group initialization omitted on each rank.
2025-07-17T07:05:47.1779400Z         >>> import torch.distributed as dist
2025-07-17T07:05:47.1779460Z         >>> # Assumes world_size of 3.
2025-07-17T07:05:47.1779570Z         >>> gather_objects = ["foo", 12, {1: 2}] # any picklable object
2025-07-17T07:05:47.1779640Z         >>> output = [None for _ in gather_objects]
2025-07-17T07:05:47.1779690Z         >>> dist.gather_object(
2025-07-17T07:05:47.1779760Z         ...     gather_objects[dist.get_rank()],
2025-07-17T07:05:47.1779840Z         ...     output if dist.get_rank() == 0 else None,
2025-07-17T07:05:47.1779880Z         ...     dst=0
2025-07-17T07:05:47.1779930Z         ... )
2025-07-17T07:05:47.1779970Z         >>> # On rank 0
2025-07-17T07:05:47.1780010Z         >>> output
2025-07-17T07:05:47.1780060Z         ['foo', 12, {1: 2}]
2025-07-17T07:05:47.1780110Z     
2025-07-17T07:05:47.1780250Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1780300Z     
2025-07-17T07:05:47.1780350Z       warnings.warn(msg)
2025-07-17T07:05:47.1780390Z     
2025-07-17T07:05:47.1780490Z --- Parse Warning: 50 / 136 ---
2025-07-17T07:05:47.1781160Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_gather in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=3794.
2025-07-17T07:05:47.1781310Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1781360Z     
2025-07-17T07:05:47.1781430Z     Gathers tensors from the whole group in a list.
2025-07-17T07:05:47.1781470Z     
2025-07-17T07:05:47.1781560Z     Complex and uneven sized tensors are supported.
2025-07-17T07:05:47.1781600Z     
2025-07-17T07:05:47.1781640Z     Args:
2025-07-17T07:05:47.1781750Z         tensor_list (list[Tensor]): Output list. It should contain
2025-07-17T07:05:47.1781880Z             correctly-sized tensors to be used for output of the collective.
2025-07-17T07:05:47.1781950Z             Uneven sized tensors are supported.
2025-07-17T07:05:47.1782060Z         tensor (Tensor): Tensor to be broadcast from current process.
2025-07-17T07:05:47.1782200Z         group (ProcessGroup, optional): The process group to work on. If None,
2025-07-17T07:05:47.1782270Z             the default process group will be used.
2025-07-17T07:05:47.1782390Z         async_op (bool, optional): Whether this op should be an async op
2025-07-17T07:05:47.1782430Z     
2025-07-17T07:05:47.1782470Z     Returns:
2025-07-17T07:05:47.1782550Z         Async work handle, if async_op is set to True.
2025-07-17T07:05:47.1782640Z         None, if not async_op or if not part of the group
2025-07-17T07:05:47.1782680Z     
2025-07-17T07:05:47.1782720Z     Examples:
2025-07-17T07:05:47.1782820Z         >>> # xdoctest: +SKIP("need process group init")
2025-07-17T07:05:47.1782910Z         >>> # All tensors below are of torch.int64 dtype.
2025-07-17T07:05:47.1782980Z         >>> # We have 2 process groups, 2 ranks.
2025-07-17T07:05:47.1783070Z         >>> device = torch.device(f"cuda:{rank}")
2025-07-17T07:05:47.1783120Z         >>> tensor_list = [
2025-07-17T07:05:47.1783250Z         ...     torch.zeros(2, dtype=torch.int64, device=device) for _ in range(2)
2025-07-17T07:05:47.1783290Z         ... ]
2025-07-17T07:05:47.1783340Z         >>> tensor_list
2025-07-17T07:05:47.1783460Z         [tensor([0, 0], device='cuda:0'), tensor([0, 0], device='cuda:0')] # Rank 0
2025-07-17T07:05:47.1783580Z         [tensor([0, 0], device='cuda:1'), tensor([0, 0], device='cuda:1')] # Rank 1
2025-07-17T07:05:47.1783720Z         >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank
2025-07-17T07:05:47.1783780Z         >>> tensor
2025-07-17T07:05:47.1783870Z         tensor([1, 2], device='cuda:0') # Rank 0
2025-07-17T07:05:47.1783940Z         tensor([3, 4], device='cuda:1') # Rank 1
2025-07-17T07:05:47.1784010Z         >>> dist.all_gather(tensor_list, tensor)
2025-07-17T07:05:47.1784050Z         >>> tensor_list
2025-07-17T07:05:47.1784170Z         [tensor([1, 2], device='cuda:0'), tensor([3, 4], device='cuda:0')] # Rank 0
2025-07-17T07:05:47.1784290Z         [tensor([1, 2], device='cuda:1'), tensor([3, 4], device='cuda:1')] # Rank 1
2025-07-17T07:05:47.1784330Z     
2025-07-17T07:05:47.1784410Z         >>> # All tensors below are of torch.cfloat dtype.
2025-07-17T07:05:47.1784480Z         >>> # We have 2 process groups, 2 ranks.
2025-07-17T07:05:47.1784530Z         >>> tensor_list = [
2025-07-17T07:05:47.1784660Z         ...     torch.zeros(2, dtype=torch.cfloat, device=device) for _ in range(2)
2025-07-17T07:05:47.1784700Z         ... ]
2025-07-17T07:05:47.1784750Z         >>> tensor_list
2025-07-17T07:05:47.1784900Z         [tensor([0.+0.j, 0.+0.j], device='cuda:0'), tensor([0.+0.j, 0.+0.j], device='cuda:0')] # Rank 0
2025-07-17T07:05:47.1785050Z         [tensor([0.+0.j, 0.+0.j], device='cuda:1'), tensor([0.+0.j, 0.+0.j], device='cuda:1')] # Rank 1
2025-07-17T07:05:47.1785100Z         >>> tensor = torch.tensor(
2025-07-17T07:05:47.1785200Z         ...     [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device
2025-07-17T07:05:47.1785250Z         ... ) + 2 * rank * (1 + 1j)
2025-07-17T07:05:47.1785290Z         >>> tensor
2025-07-17T07:05:47.1785380Z         tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0
2025-07-17T07:05:47.1785450Z         tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1
2025-07-17T07:05:47.1785520Z         >>> dist.all_gather(tensor_list, tensor)
2025-07-17T07:05:47.1785570Z         >>> tensor_list
2025-07-17T07:05:47.1785710Z         [tensor([1.+1.j, 2.+2.j], device='cuda:0'), tensor([3.+3.j, 4.+4.j], device='cuda:0')] # Rank 0
2025-07-17T07:05:47.1785850Z         [tensor([1.+1.j, 2.+2.j], device='cuda:1'), tensor([3.+3.j, 4.+4.j], device='cuda:1')] # Rank 1
2025-07-17T07:05:47.1785900Z     
2025-07-17T07:05:47.1785940Z     
2025-07-17T07:05:47.1786090Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1786130Z     
2025-07-17T07:05:47.1786180Z       warnings.warn(msg)
2025-07-17T07:05:47.1786220Z     
2025-07-17T07:05:47.1786320Z --- Parse Warning: 51 / 136 ---
2025-07-17T07:05:47.1787010Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_to_all_single in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=4500.
2025-07-17T07:05:47.1787170Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1787210Z     
2025-07-17T07:05:47.1787360Z     Split input tensor and then scatter the split list to all processes in a group.
2025-07-17T07:05:47.1787400Z     
2025-07-17T07:05:47.1787600Z     Later the received tensors are concatenated from all the processes in the group
2025-07-17T07:05:47.1787680Z     and returned as a single output tensor.
2025-07-17T07:05:47.1787720Z     
2025-07-17T07:05:47.1787790Z     Complex tensors are supported.
2025-07-17T07:05:47.1787830Z     
2025-07-17T07:05:47.1787880Z     Args:
2025-07-17T07:05:47.1787980Z         output (Tensor): Gathered concatenated output tensor.
2025-07-17T07:05:47.1788050Z         input (Tensor): Input tensor to scatter.
2025-07-17T07:05:47.1788180Z         output_split_sizes: (list[Int], optional): Output split sizes for dim 0
2025-07-17T07:05:47.1788310Z             if specified None or empty, dim 0 of ``output`` tensor must divide
2025-07-17T07:05:47.1788370Z             equally by ``world_size``.
2025-07-17T07:05:47.1788500Z         input_split_sizes: (list[Int], optional): Input split sizes for dim 0
2025-07-17T07:05:47.1788640Z             if specified None or empty, dim 0 of ``input`` tensor must divide
2025-07-17T07:05:47.1788710Z             equally by ``world_size``.
2025-07-17T07:05:47.1788850Z         group (ProcessGroup, optional): The process group to work on. If None,
2025-07-17T07:05:47.1788920Z             the default process group will be used.
2025-07-17T07:05:47.1789050Z         async_op (bool, optional): Whether this op should be an async op.
2025-07-17T07:05:47.1789090Z     
2025-07-17T07:05:47.1789130Z     Returns:
2025-07-17T07:05:47.1789210Z         Async work handle, if async_op is set to True.
2025-07-17T07:05:47.1789300Z         None, if not async_op or if not part of the group.
2025-07-17T07:05:47.1789340Z     
2025-07-17T07:05:47.1789380Z     .. warning::
2025-07-17T07:05:47.1789480Z         `all_to_all_single` is experimental and subject to change.
2025-07-17T07:05:47.1789520Z     
2025-07-17T07:05:47.1789560Z     Examples:
2025-07-17T07:05:47.1789640Z         >>> # xdoctest: +SKIP("Undefined rank")
2025-07-17T07:05:47.1789700Z         >>> input = torch.arange(4) + rank * 4
2025-07-17T07:05:47.1789750Z         >>> input
2025-07-17T07:05:47.1789800Z         tensor([0, 1, 2, 3])     # Rank 0
2025-07-17T07:05:47.1789860Z         tensor([4, 5, 6, 7])     # Rank 1
2025-07-17T07:05:47.1789910Z         tensor([8, 9, 10, 11])   # Rank 2
2025-07-17T07:05:47.1789970Z         tensor([12, 13, 14, 15]) # Rank 3
2025-07-17T07:05:47.1790050Z         >>> output = torch.empty([4], dtype=torch.int64)
2025-07-17T07:05:47.1790120Z         >>> dist.all_to_all_single(output, input)
2025-07-17T07:05:47.1790170Z         >>> output
2025-07-17T07:05:47.1790220Z         tensor([0, 4, 8, 12])    # Rank 0
2025-07-17T07:05:47.1790270Z         tensor([1, 5, 9, 13])    # Rank 1
2025-07-17T07:05:47.1790330Z         tensor([2, 6, 10, 14])   # Rank 2
2025-07-17T07:05:47.1790380Z         tensor([3, 7, 11, 15])   # Rank 3
2025-07-17T07:05:47.1790420Z     
2025-07-17T07:05:47.1790520Z         >>> # Essentially, it is similar to following operation:
2025-07-17T07:05:47.1790600Z         >>> scatter_list = list(input.chunk(world_size))
2025-07-17T07:05:47.1790680Z         >>> gather_list = list(output.chunk(world_size))
2025-07-17T07:05:47.1790740Z         >>> for i in range(world_size):
2025-07-17T07:05:47.1790880Z         >>>     dist.scatter(gather_list[i], scatter_list if i == rank else [], src = i)
2025-07-17T07:05:47.1790920Z     
2025-07-17T07:05:47.1790990Z         >>> # Another example with uneven split
2025-07-17T07:05:47.1791030Z         >>> input
2025-07-17T07:05:47.1791130Z         tensor([0, 1, 2, 3, 4, 5])                                       # Rank 0
2025-07-17T07:05:47.1791230Z         tensor([10, 11, 12, 13, 14, 15, 16, 17, 18])                     # Rank 1
2025-07-17T07:05:47.1791320Z         tensor([20, 21, 22, 23, 24])                                     # Rank 2
2025-07-17T07:05:47.1791420Z         tensor([30, 31, 32, 33, 34, 35, 36])                             # Rank 3
2025-07-17T07:05:47.1791470Z         >>> input_splits
2025-07-17T07:05:47.1791550Z         [2, 2, 1, 1]                                                     # Rank 0
2025-07-17T07:05:47.1791650Z         [3, 2, 2, 2]                                                     # Rank 1
2025-07-17T07:05:47.1791730Z         [2, 1, 1, 1]                                                     # Rank 2
2025-07-17T07:05:47.1791830Z         [2, 2, 2, 1]                                                     # Rank 3
2025-07-17T07:05:47.1791880Z         >>> output_splits
2025-07-17T07:05:47.1791960Z         [2, 3, 2, 2]                                                     # Rank 0
2025-07-17T07:05:47.1792030Z         [2, 2, 1, 2]                                                     # Rank 1
2025-07-17T07:05:47.1792110Z         [1, 2, 1, 2]                                                     # Rank 2
2025-07-17T07:05:47.1792180Z         [1, 2, 1, 1]                                                     # Rank 3
2025-07-17T07:05:47.1792230Z         >>> output = ...
2025-07-17T07:05:47.1792370Z         >>> dist.all_to_all_single(output, input, output_splits, input_splits)
2025-07-17T07:05:47.1792430Z         >>> output
2025-07-17T07:05:47.1792530Z         tensor([ 0,  1, 10, 11, 12, 20, 21, 30, 31])                     # Rank 0
2025-07-17T07:05:47.1792620Z         tensor([ 2,  3, 13, 14, 22, 32, 33])                             # Rank 1
2025-07-17T07:05:47.1792720Z         tensor([ 4, 15, 16, 23, 34, 35])                                 # Rank 2
2025-07-17T07:05:47.1792810Z         tensor([ 5, 17, 18, 24, 36])                                     # Rank 3
2025-07-17T07:05:47.1792850Z     
2025-07-17T07:05:47.1792890Z     
2025-07-17T07:05:47.1792990Z         >>> # Another example with tensors of torch.cfloat type.
2025-07-17T07:05:47.1793040Z         >>> input = torch.tensor(
2025-07-17T07:05:47.1793130Z         ...     [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat
2025-07-17T07:05:47.1793180Z         ... ) + 4 * rank * (1 + 1j)
2025-07-17T07:05:47.1793220Z         >>> input
2025-07-17T07:05:47.1793330Z         tensor([1+1j, 2+2j, 3+3j, 4+4j])                                # Rank 0
2025-07-17T07:05:47.1793440Z         tensor([5+5j, 6+6j, 7+7j, 8+8j])                                # Rank 1
2025-07-17T07:05:47.1793550Z         tensor([9+9j, 10+10j, 11+11j, 12+12j])                          # Rank 2
2025-07-17T07:05:47.1793660Z         tensor([13+13j, 14+14j, 15+15j, 16+16j])                        # Rank 3
2025-07-17T07:05:47.1793740Z         >>> output = torch.empty([4], dtype=torch.int64)
2025-07-17T07:05:47.1793810Z         >>> dist.all_to_all_single(output, input)
2025-07-17T07:05:47.1793910Z         >>> output
2025-07-17T07:05:47.1794020Z         tensor([1+1j, 5+5j, 9+9j, 13+13j])                              # Rank 0
2025-07-17T07:05:47.1794120Z         tensor([2+2j, 6+6j, 10+10j, 14+14j])                            # Rank 1
2025-07-17T07:05:47.1794220Z         tensor([3+3j, 7+7j, 11+11j, 15+15j])                            # Rank 2
2025-07-17T07:05:47.1794320Z         tensor([4+4j, 8+8j, 12+12j, 16+16j])                            # Rank 3
2025-07-17T07:05:47.1794370Z     
2025-07-17T07:05:47.1794520Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1794560Z     
2025-07-17T07:05:47.1794610Z       warnings.warn(msg)
2025-07-17T07:05:47.1794650Z     
2025-07-17T07:05:47.1794750Z --- Parse Warning: 52 / 136 ---
2025-07-17T07:05:47.1795430Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_to_all in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/distributed_c10d.py line=4642.
2025-07-17T07:05:47.1795580Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1795620Z     
2025-07-17T07:05:47.1795840Z     Scatters list of input tensors to all processes in a group and return gathered list of tensors in output list.
2025-07-17T07:05:47.1795880Z     
2025-07-17T07:05:47.1795940Z     Complex tensors are supported.
2025-07-17T07:05:47.1796010Z     
2025-07-17T07:05:47.1796050Z     Args:
2025-07-17T07:05:47.1796180Z         output_tensor_list (list[Tensor]): List of tensors to be gathered one
2025-07-17T07:05:47.1796230Z             per rank.
2025-07-17T07:05:47.1796390Z         input_tensor_list (list[Tensor]): List of tensors to scatter one per rank.
2025-07-17T07:05:47.1796520Z         group (ProcessGroup, optional): The process group to work on. If None,
2025-07-17T07:05:47.1796590Z             the default process group will be used.
2025-07-17T07:05:47.1796710Z         async_op (bool, optional): Whether this op should be an async op.
2025-07-17T07:05:47.1796750Z     
2025-07-17T07:05:47.1796800Z     Returns:
2025-07-17T07:05:47.1796880Z         Async work handle, if async_op is set to True.
2025-07-17T07:05:47.1796970Z         None, if not async_op or if not part of the group.
2025-07-17T07:05:47.1797010Z     
2025-07-17T07:05:47.1797050Z     .. warning::
2025-07-17T07:05:47.1797170Z         `all_to_all` is experimental and subject to change.
2025-07-17T07:05:47.1797240Z     
2025-07-17T07:05:47.1797280Z     Examples:
2025-07-17T07:05:47.1797350Z         >>> # xdoctest: +SKIP("Undefined rank")
2025-07-17T07:05:47.1797420Z         >>> input = torch.arange(4) + rank * 4
2025-07-17T07:05:47.1797480Z         >>> input = list(input.chunk(4))
2025-07-17T07:05:47.1797520Z         >>> input
2025-07-17T07:05:47.1797620Z         [tensor([0]), tensor([1]), tensor([2]), tensor([3])]     # Rank 0
2025-07-17T07:05:47.1797720Z         [tensor([4]), tensor([5]), tensor([6]), tensor([7])]     # Rank 1
2025-07-17T07:05:47.1797820Z         [tensor([8]), tensor([9]), tensor([10]), tensor([11])]   # Rank 2
2025-07-17T07:05:47.1797930Z         [tensor([12]), tensor([13]), tensor([14]), tensor([15])] # Rank 3
2025-07-17T07:05:47.1798040Z         >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4))
2025-07-17T07:05:47.1798100Z         >>> dist.all_to_all(output, input)
2025-07-17T07:05:47.1798150Z         >>> output
2025-07-17T07:05:47.1798250Z         [tensor([0]), tensor([4]), tensor([8]), tensor([12])]    # Rank 0
2025-07-17T07:05:47.1798350Z         [tensor([1]), tensor([5]), tensor([9]), tensor([13])]    # Rank 1
2025-07-17T07:05:47.1798440Z         [tensor([2]), tensor([6]), tensor([10]), tensor([14])]   # Rank 2
2025-07-17T07:05:47.1798550Z         [tensor([3]), tensor([7]), tensor([11]), tensor([15])]   # Rank 3
2025-07-17T07:05:47.1798590Z     
2025-07-17T07:05:47.1798690Z         >>> # Essentially, it is similar to following operation:
2025-07-17T07:05:47.1798740Z         >>> scatter_list = input
2025-07-17T07:05:47.1798800Z         >>> gather_list = output
2025-07-17T07:05:47.1798850Z         >>> for i in range(world_size):
2025-07-17T07:05:47.1798990Z         >>>     dist.scatter(gather_list[i], scatter_list if i == rank else [], src=i)
2025-07-17T07:05:47.1799030Z     
2025-07-17T07:05:47.1799070Z         >>> input
2025-07-17T07:05:47.1799170Z         tensor([0, 1, 2, 3, 4, 5])                                       # Rank 0
2025-07-17T07:05:47.1799270Z         tensor([10, 11, 12, 13, 14, 15, 16, 17, 18])                     # Rank 1
2025-07-17T07:05:47.1799360Z         tensor([20, 21, 22, 23, 24])                                     # Rank 2
2025-07-17T07:05:47.1799460Z         tensor([30, 31, 32, 33, 34, 35, 36])                             # Rank 3
2025-07-17T07:05:47.1799510Z         >>> input_splits
2025-07-17T07:05:47.1799580Z         [2, 2, 1, 1]                                                     # Rank 0
2025-07-17T07:05:47.1799660Z         [3, 2, 2, 2]                                                     # Rank 1
2025-07-17T07:05:47.1799730Z         [2, 1, 1, 1]                                                     # Rank 2
2025-07-17T07:05:47.1799810Z         [2, 2, 2, 1]                                                     # Rank 3
2025-07-17T07:05:47.1799860Z         >>> output_splits
2025-07-17T07:05:47.1799930Z         [2, 3, 2, 2]                                                     # Rank 0
2025-07-17T07:05:47.1800030Z         [2, 2, 1, 2]                                                     # Rank 1
2025-07-17T07:05:47.1800110Z         [1, 2, 1, 2]                                                     # Rank 2
2025-07-17T07:05:47.1800180Z         [1, 2, 1, 1]                                                     # Rank 3
2025-07-17T07:05:47.1800280Z         >>> input = list(input.split(input_splits))
2025-07-17T07:05:47.1800320Z         >>> input
2025-07-17T07:05:47.1800450Z         [tensor([0, 1]), tensor([2, 3]), tensor([4]), tensor([5])]                   # Rank 0
2025-07-17T07:05:47.1800570Z         [tensor([10, 11, 12]), tensor([13, 14]), tensor([15, 16]), tensor([17, 18])] # Rank 1
2025-07-17T07:05:47.1800690Z         [tensor([20, 21]), tensor([22]), tensor([23]), tensor([24])]                 # Rank 2
2025-07-17T07:05:47.1800810Z         [tensor([30, 31]), tensor([32, 33]), tensor([34, 35]), tensor([36])]         # Rank 3
2025-07-17T07:05:47.1800880Z         >>> output = ...
2025-07-17T07:05:47.1800970Z         >>> dist.all_to_all(output, input)
2025-07-17T07:05:47.1801010Z         >>> output
2025-07-17T07:05:47.1801130Z         [tensor([0, 1]), tensor([10, 11, 12]), tensor([20, 21]), tensor([30, 31])]   # Rank 0
2025-07-17T07:05:47.1801250Z         [tensor([2, 3]), tensor([13, 14]), tensor([22]), tensor([32, 33])]           # Rank 1
2025-07-17T07:05:47.1801380Z         [tensor([4]), tensor([15, 16]), tensor([23]), tensor([34, 35])]              # Rank 2
2025-07-17T07:05:47.1801500Z         [tensor([5]), tensor([17, 18]), tensor([24]), tensor([36])]                  # Rank 3
2025-07-17T07:05:47.1801540Z     
2025-07-17T07:05:47.1801630Z         >>> # Another example with tensors of torch.cfloat type.
2025-07-17T07:05:47.1801690Z         >>> input = torch.tensor(
2025-07-17T07:05:47.1801780Z         ...     [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat
2025-07-17T07:05:47.1801830Z         ... ) + 4 * rank * (1 + 1j)
2025-07-17T07:05:47.1801890Z         >>> input = list(input.chunk(4))
2025-07-17T07:05:47.1801940Z         >>> input
2025-07-17T07:05:47.1802070Z         [tensor([1+1j]), tensor([2+2j]), tensor([3+3j]), tensor([4+4j])]            # Rank 0
2025-07-17T07:05:47.1802200Z         [tensor([5+5j]), tensor([6+6j]), tensor([7+7j]), tensor([8+8j])]            # Rank 1
2025-07-17T07:05:47.1802320Z         [tensor([9+9j]), tensor([10+10j]), tensor([11+11j]), tensor([12+12j])]      # Rank 2
2025-07-17T07:05:47.1802460Z         [tensor([13+13j]), tensor([14+14j]), tensor([15+15j]), tensor([16+16j])]    # Rank 3
2025-07-17T07:05:47.1802570Z         >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4))
2025-07-17T07:05:47.1802640Z         >>> dist.all_to_all(output, input)
2025-07-17T07:05:47.1802680Z         >>> output
2025-07-17T07:05:47.1802800Z         [tensor([1+1j]), tensor([5+5j]), tensor([9+9j]), tensor([13+13j])]          # Rank 0
2025-07-17T07:05:47.1802930Z         [tensor([2+2j]), tensor([6+6j]), tensor([10+10j]), tensor([14+14j])]        # Rank 1
2025-07-17T07:05:47.1803060Z         [tensor([3+3j]), tensor([7+7j]), tensor([11+11j]), tensor([15+15j])]        # Rank 2
2025-07-17T07:05:47.1803180Z         [tensor([4+4j]), tensor([8+8j]), tensor([12+12j]), tensor([16+16j])]        # Rank 3
2025-07-17T07:05:47.1803220Z     
2025-07-17T07:05:47.1803260Z     
2025-07-17T07:05:47.1803410Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1803460Z     
2025-07-17T07:05:47.1803510Z       warnings.warn(msg)
2025-07-17T07:05:47.1803550Z     
2025-07-17T07:05:47.1803640Z --- Parse Warning: 53 / 136 ---
2025-07-17T07:05:47.1804270Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=__doc__ in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/launch.py line=2.
2025-07-17T07:05:47.1804430Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1804470Z     
2025-07-17T07:05:47.1804590Z     Module ``torch.distributed.launch``.
2025-07-17T07:05:47.1804630Z     
2025-07-17T07:05:47.1804780Z     ``torch.distributed.launch`` is a module that spawns up multiple distributed
2025-07-17T07:05:47.1804890Z     training processes on each of the training nodes.
2025-07-17T07:05:47.1804930Z     
2025-07-17T07:05:47.1804980Z     .. warning::
2025-07-17T07:05:47.1805020Z     
2025-07-17T07:05:47.1805170Z         This module is going to be deprecated in favor of :ref:`torchrun <launcher-api>`.
2025-07-17T07:05:47.1805210Z     
2025-07-17T07:05:47.1805350Z     The utility can be used for single-node distributed training, in which one or
2025-07-17T07:05:47.1805490Z     more processes per node will be spawned. The utility can be used for either
2025-07-17T07:05:47.1805620Z     CPU training or GPU training. If the utility is used for GPU training,
2025-07-17T07:05:47.1805810Z     each distributed process will be operating on a single GPU. This can achieve
2025-07-17T07:05:47.1805970Z     well-improved single-node training performance. It can also be used in
2025-07-17T07:05:47.1806130Z     multi-node distributed training, by spawning up multiple processes on each node
2025-07-17T07:05:47.1806270Z     for well-improved multi-node distributed training performance as well.
2025-07-17T07:05:47.1806410Z     This will especially be beneficial for systems with multiple Infiniband
2025-07-17T07:05:47.1806560Z     interfaces that have direct-GPU support, since all of them can be utilized for
2025-07-17T07:05:47.1806620Z     aggregated communication bandwidth.
2025-07-17T07:05:47.1806660Z     
2025-07-17T07:05:47.1806800Z     In both cases of single-node distributed training or multi-node distributed
2025-07-17T07:05:47.1806940Z     training, this utility will launch the given number of processes per node
2025-07-17T07:05:47.1807080Z     (``--nproc-per-node``). If used for GPU training, this number needs to be less
2025-07-17T07:05:47.1807210Z     or equal to the number of GPUs on the current system (``nproc_per_node``),
2025-07-17T07:05:47.1807340Z     and each process will be operating on a single GPU from *GPU 0 to
2025-07-17T07:05:47.1807400Z     GPU (nproc_per_node - 1)*.
2025-07-17T07:05:47.1807440Z     
2025-07-17T07:05:47.1807490Z     **How to use this module:**
2025-07-17T07:05:47.1807530Z     
2025-07-17T07:05:47.1807620Z     1. Single-Node multi-process distributed training
2025-07-17T07:05:47.1807660Z     
2025-07-17T07:05:47.1807710Z     ::
2025-07-17T07:05:47.1807740Z     
2025-07-17T07:05:47.1807890Z         python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE
2025-07-17T07:05:47.1808000Z                    YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 and all other
2025-07-17T07:05:47.1808080Z                    arguments of your training script)
2025-07-17T07:05:47.1808120Z     
2025-07-17T07:05:47.1808250Z     2. Multi-Node multi-process distributed training: (e.g. two nodes)
2025-07-17T07:05:47.1808290Z     
2025-07-17T07:05:47.1808330Z     
2025-07-17T07:05:47.1808420Z     Node 1: *(IP: 192.168.1.1, and has a free port: 1234)*
2025-07-17T07:05:47.1808450Z     
2025-07-17T07:05:47.1808500Z     ::
2025-07-17T07:05:47.1808540Z     
2025-07-17T07:05:47.1808680Z         python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE
2025-07-17T07:05:47.1808780Z                    --nnodes=2 --node-rank=0 --master-addr="192.168.1.1"
2025-07-17T07:05:47.1808910Z                    --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3
2025-07-17T07:05:47.1809000Z                    and all other arguments of your training script)
2025-07-17T07:05:47.1809040Z     
2025-07-17T07:05:47.1809080Z     Node 2:
2025-07-17T07:05:47.1809120Z     
2025-07-17T07:05:47.1809160Z     ::
2025-07-17T07:05:47.1809200Z     
2025-07-17T07:05:47.1809340Z         python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE
2025-07-17T07:05:47.1809440Z                    --nnodes=2 --node-rank=1 --master-addr="192.168.1.1"
2025-07-17T07:05:47.1809590Z                    --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3
2025-07-17T07:05:47.1809680Z                    and all other arguments of your training script)
2025-07-17T07:05:47.1809730Z     
2025-07-17T07:05:47.1809820Z     3. To look up what optional arguments this module offers:
2025-07-17T07:05:47.1809900Z     
2025-07-17T07:05:47.1809940Z     ::
2025-07-17T07:05:47.1809980Z     
2025-07-17T07:05:47.1810060Z         python -m torch.distributed.launch --help
2025-07-17T07:05:47.1810100Z     
2025-07-17T07:05:47.1810140Z     
2025-07-17T07:05:47.1810190Z     **Important Notices:**
2025-07-17T07:05:47.1810230Z     
2025-07-17T07:05:47.1810340Z     1. This utility and multi-process distributed (single-node or
2025-07-17T07:05:47.1810490Z     multi-node) GPU training currently only achieves the best performance using
2025-07-17T07:05:47.1810640Z     the NCCL distributed backend. Thus NCCL backend is the recommended backend to
2025-07-17T07:05:47.1810710Z     use for GPU training.
2025-07-17T07:05:47.1810760Z     
2025-07-17T07:05:47.1810890Z     2. In your training program, you must parse the command-line argument:
2025-07-17T07:05:47.1811030Z     ``--local-rank=LOCAL_PROCESS_RANK``, which will be provided by this module.
2025-07-17T07:05:47.1811170Z     If your training program uses GPUs, you should ensure that your code only
2025-07-17T07:05:47.1811290Z     runs on the GPU device of LOCAL_PROCESS_RANK. This can be done by:
2025-07-17T07:05:47.1811330Z     
2025-07-17T07:05:47.1811390Z     Parsing the local_rank argument
2025-07-17T07:05:47.1811430Z     
2025-07-17T07:05:47.1811470Z     ::
2025-07-17T07:05:47.1811510Z     
2025-07-17T07:05:47.1811560Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1811610Z         >>> import argparse
2025-07-17T07:05:47.1811690Z         >>> parser = argparse.ArgumentParser()
2025-07-17T07:05:47.1811800Z         >>> parser.add_argument("--local-rank", "--local_rank", type=int)
2025-07-17T07:05:47.1811870Z         >>> args = parser.parse_args()
2025-07-17T07:05:47.1811910Z     
2025-07-17T07:05:47.1811980Z     Set your device to local rank using either
2025-07-17T07:05:47.1812020Z     
2025-07-17T07:05:47.1812060Z     ::
2025-07-17T07:05:47.1812100Z     
2025-07-17T07:05:47.1812220Z         >>> torch.cuda.set_device(args.local_rank)  # before your code runs
2025-07-17T07:05:47.1812260Z     
2025-07-17T07:05:47.1812300Z     or
2025-07-17T07:05:47.1812340Z     
2025-07-17T07:05:47.1812380Z     ::
2025-07-17T07:05:47.1812420Z     
2025-07-17T07:05:47.1812500Z         >>> with torch.cuda.device(args.local_rank):
2025-07-17T07:05:47.1812550Z         >>>    # your code to run
2025-07-17T07:05:47.1812590Z         >>>    ...
2025-07-17T07:05:47.1812630Z     
2025-07-17T07:05:47.1812690Z     .. versionchanged:: 2.0.0
2025-07-17T07:05:47.1812730Z     
2025-07-17T07:05:47.1812870Z         The launcher will passes the ``--local-rank=<rank>`` argument to your script.
2025-07-17T07:05:47.1813020Z         From PyTorch 2.0.0 onwards, the dashed ``--local-rank`` is preferred over the
2025-07-17T07:05:47.1813110Z         previously used underscored ``--local_rank``.
2025-07-17T07:05:47.1813150Z     
2025-07-17T07:05:47.1813290Z         For backward compatibility, it may be necessary for users to handle both
2025-07-17T07:05:47.1813450Z         cases in their argument parsing code. This means including both ``"--local-rank"``
2025-07-17T07:05:47.1813580Z         and ``"--local_rank"`` in the argument parser. If only ``"--local_rank"`` is
2025-07-17T07:05:47.1813730Z         provided, the launcher will trigger an error: "error: unrecognized arguments:
2025-07-17T07:05:47.1813870Z         --local-rank=<rank>". For training code that only supports PyTorch 2.0.0+,
2025-07-17T07:05:47.1813960Z         including ``"--local-rank"`` should be sufficient.
2025-07-17T07:05:47.1814000Z     
2025-07-17T07:05:47.1814140Z     3. In your training program, you are supposed to call the following function
2025-07-17T07:05:47.1814280Z     at the beginning to start the distributed backend. It is strongly recommended
2025-07-17T07:05:47.1814430Z     that ``init_method=env://``. Other init methods (e.g. ``tcp://``) may work,
2025-07-17T07:05:47.1814550Z     but ``env://`` is the one that is officially supported by this module.
2025-07-17T07:05:47.1814620Z     
2025-07-17T07:05:47.1814660Z     ::
2025-07-17T07:05:47.1814700Z     
2025-07-17T07:05:47.1814820Z         >>> torch.distributed.init_process_group(backend='YOUR BACKEND',
2025-07-17T07:05:47.1814910Z         >>>                                      init_method='env://')
2025-07-17T07:05:47.1814940Z     
2025-07-17T07:05:47.1815090Z     4. In your training program, you can either use regular distributed functions
2025-07-17T07:05:47.1815230Z     or use :func:`torch.nn.parallel.DistributedDataParallel` module. If your
2025-07-17T07:05:47.1815360Z     training program uses GPUs for training and you would like to use
2025-07-17T07:05:47.1815470Z     :func:`torch.nn.parallel.DistributedDataParallel` module,
2025-07-17T07:05:47.1815590Z     here is how to configure it.
2025-07-17T07:05:47.1815650Z     
2025-07-17T07:05:47.1815700Z     ::
2025-07-17T07:05:47.1815740Z     
2025-07-17T07:05:47.1815850Z         >>> model = torch.nn.parallel.DistributedDataParallel(model,
2025-07-17T07:05:47.1815950Z         >>>                                                   device_ids=[args.local_rank],
2025-07-17T07:05:47.1816040Z         >>>                                                   output_device=args.local_rank)
2025-07-17T07:05:47.1816080Z     
2025-07-17T07:05:47.1816220Z     Please ensure that ``device_ids`` argument is set to be the only GPU device id
2025-07-17T07:05:47.1816360Z     that your code will be operating on. This is generally the local rank of the
2025-07-17T07:05:47.1816500Z     process. In other words, the ``device_ids`` needs to be ``[args.local_rank]``,
2025-07-17T07:05:47.1816630Z     and ``output_device`` needs to be ``args.local_rank`` in order to use this
2025-07-17T07:05:47.1816670Z     utility
2025-07-17T07:05:47.1816720Z     
2025-07-17T07:05:47.1816870Z     5. Another way to pass ``local_rank`` to the subprocesses via environment variable
2025-07-17T07:05:47.1817000Z     ``LOCAL_RANK``. This behavior is enabled when you launch the script with
2025-07-17T07:05:47.1817130Z     ``--use-env=True``. You must adjust the subprocess example above to replace
2025-07-17T07:05:47.1817250Z     ``args.local_rank`` with ``os.environ['LOCAL_RANK']``; the launcher
2025-07-17T07:05:47.1817350Z     will not pass ``--local-rank`` when you specify this flag.
2025-07-17T07:05:47.1817390Z     
2025-07-17T07:05:47.1817440Z     .. warning::
2025-07-17T07:05:47.1817470Z     
2025-07-17T07:05:47.1817600Z         ``local_rank`` is NOT globally unique: it is only unique per process
2025-07-17T07:05:47.1817710Z         on a machine.  Thus, don't use it to decide if you should, e.g.,
2025-07-17T07:05:47.1817780Z         write to a networked filesystem.  See
2025-07-17T07:05:47.1817910Z         https://github.com/pytorch/pytorch/issues/12042 for an example of
2025-07-17T07:05:47.1818010Z         how things can go wrong if you don't do this correctly.
2025-07-17T07:05:47.1818050Z     
2025-07-17T07:05:47.1818100Z     
2025-07-17T07:05:47.1818130Z     
2025-07-17T07:05:47.1821670Z     
2025-07-17T07:05:47.1821870Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1821910Z     
2025-07-17T07:05:47.1821960Z       warnings.warn(msg)
2025-07-17T07:05:47.1822000Z     
2025-07-17T07:05:47.1822120Z --- Parse Warning: 54 / 136 ---
2025-07-17T07:05:47.1822810Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DeviceMesh.__getitem__ in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/device_mesh.py line=685.
2025-07-17T07:05:47.1822960Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:47.1823000Z     
2025-07-17T07:05:47.1823240Z     Slice the current DeviceMesh based on the mesh_dim_names given to create a submesh.
2025-07-17T07:05:47.1823400Z     The submesh created consists of the dimensions and the communicators indicated by
2025-07-17T07:05:47.1823450Z     ``mesh_dim_names``
2025-07-17T07:05:47.1823540Z     
2025-07-17T07:05:47.1823580Z     Args:
2025-07-17T07:05:47.1823720Z         mesh_dim_names (Union[str, Tuple[str]]): the name or the tuple of names of the
2025-07-17T07:05:47.1823830Z         mesh dimension of the DeviceMesh to create the submesh for.
2025-07-17T07:05:47.1823870Z     Returns:
2025-07-17T07:05:47.1823930Z         A :class:`DeviceMesh` object
2025-07-17T07:05:47.1823970Z     
2025-07-17T07:05:47.1824140Z     The following program runs on each process/rank in an SPMD manner in a world size of 8.
2025-07-17T07:05:47.1824190Z     In the first example:
2025-07-17T07:05:47.1824370Z         Calling mesh_2d["tp"] on rank 0, 1, 2, 3 returns a 1D submesh of DeviceMesh:([0, 1, 2, 3]).
2025-07-17T07:05:47.1824540Z         Calling mesh_2d["tp"] on rank 4, 5, 6, 7 returns a 1D submesh of  DeviceMesh:([4, 5, 6, 7]).
2025-07-17T07:05:47.1824680Z         Calling mesh_2d["dp"] on rank 0, 4 returns a 1D submesh of  DeviceMesh:([0, 4]).
2025-07-17T07:05:47.1824810Z         Calling mesh_2d["dp"] on rank 1, 5 returns a 1D submesh of  DeviceMesh:([1, 5]).
2025-07-17T07:05:47.1824940Z         Calling mesh_2d["dp"] on rank 2, 6 returns a 1D submesh of  DeviceMesh:([2, 6]).
2025-07-17T07:05:47.1825070Z         Calling mesh_2d["dp"] on rank 3, 7 returns a 1D submesh of  DeviceMesh:([3, 7]).
2025-07-17T07:05:47.1825110Z     
2025-07-17T07:05:47.1825170Z     In the second example:
2025-07-17T07:05:47.1825330Z         Calling mesh_3d["dp", "cp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 1], [4, 5]]).
2025-07-17T07:05:47.1825490Z         Calling mesh_3d["dp", "cp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 3], [6, 7]]).
2025-07-17T07:05:47.1825640Z         Calling mesh_3d["cp", "dp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 4], [1, 5]]).
2025-07-17T07:05:47.1825800Z         Calling mesh_3d["cp", "dp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 6], [3, 7]]).
2025-07-17T07:05:47.1825840Z     
2025-07-17T07:05:47.1825890Z     Example::
2025-07-17T07:05:47.1825930Z     
2025-07-17T07:05:47.1825990Z         >>> # xdoctest: +SKIP("no rank")
2025-07-17T07:05:47.1826090Z         >>> from torch.distributed.device_mesh import DeviceMesh
2025-07-17T07:05:47.1826140Z         >>>
2025-07-17T07:05:47.1826260Z         >>> # Initialize a 2D device mesh as (2, 4) to represent the topology
2025-07-17T07:05:47.1826340Z         >>> # of cross-host(dim 0), and within-host (dim 1).
2025-07-17T07:05:47.1826500Z         >>> mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))
2025-07-17T07:05:47.1826550Z         >>> tp_mesh = mesh_2d["tp"]
2025-07-17T07:05:47.1826610Z         >>> dp_mesh = mesh_2d["dp"]
2025-07-17T07:05:47.1826650Z         >>>
2025-07-17T07:05:47.1826710Z         >>> # Initialize a 3D mesh.
2025-07-17T07:05:47.1826870Z         >>> mesh_3d = init_device_mesh(device_type="cuda", (2,2,2), mesh_dim_names=("dp", "pp", "cp"))
2025-07-17T07:05:47.1827050Z         >>> # The order of the mesh_dim_names provided deteremines the order of dimensions in the submesh.
2025-07-17T07:05:47.1827120Z         >>> dp_cp_mesh = mesh_3d["dp", "cp"]
2025-07-17T07:05:47.1827190Z         >>> cp_dp_mesh = mesh_3d["cp", "dp"]
2025-07-17T07:05:47.1827220Z     
2025-07-17T07:05:47.1827610Z     Original Error: SyntaxError('positional argument follows keyword argument', ('<source_block>', 6, 82, 'mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))\n', 6, 83))
2025-07-17T07:05:47.1827650Z     
2025-07-17T07:05:47.1827800Z     mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))
2025-07-17T07:05:47.1827880Z                                                                                      ^
2025-07-17T07:05:47.1827930Z       warnings.warn(msg)
2025-07-17T07:05:47.1828000Z     
2025-07-17T07:05:47.1828110Z --- Parse Warning: 55 / 136 ---
2025-07-17T07:05:47.1828860Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BroadcastingTorchSaveReader in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/format_utils.py line=40.
2025-07-17T07:05:47.1829030Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1829070Z     
2025-07-17T07:05:47.1829250Z     StorageReader for reading a Torch Save file. This reader will read the entire checkpoint
2025-07-17T07:05:47.1829390Z     on the coordinator rank, and then broadcast and shard each tensor to all ranks.
2025-07-17T07:05:47.1829430Z     
2025-07-17T07:05:47.1829550Z     . N.B. Intended to be used with DynamicMetaLoadPlanner
2025-07-17T07:05:47.1829610Z     
2025-07-17T07:05:47.1829660Z     .. warning::
2025-07-17T07:05:47.1829760Z         Current implementation only supports loading Tensors.
2025-07-17T07:05:47.1829800Z     
2025-07-17T07:05:47.1829870Z     >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:47.1829920Z     >>> sd = {"mode": model}
2025-07-17T07:05:47.1829960Z     >>> dcp.load(
2025-07-17T07:05:47.1830000Z     >>>    sd,
2025-07-17T07:05:47.1830100Z     >>>    storage_reader=BroadcastingTorchSaveReader(),
2025-07-17T07:05:47.1830170Z     >>>    planner=DynamicMetaLoadPlanner(),
2025-07-17T07:05:47.1830230Z     >>>    checkpoint_id="path_to_model.pt"
2025-07-17T07:05:47.1830270Z     >>> )
2025-07-17T07:05:47.1830310Z     
2025-07-17T07:05:47.1830460Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1830500Z     
2025-07-17T07:05:47.1830550Z       warnings.warn(msg)
2025-07-17T07:05:47.1830590Z     
2025-07-17T07:05:47.1830690Z --- Parse Warning: 56 / 136 ---
2025-07-17T07:05:47.1831420Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DynamicMetaLoadPlanner in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/format_utils.py line=151.
2025-07-17T07:05:47.1831580Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1831620Z     
2025-07-17T07:05:47.1831840Z     Extension of DefaultLoadPlanner, which creates a new Metadata object based on the passed in state dict,
2025-07-17T07:05:47.1832030Z     avoiding the need to read metadata from disk. This is useful when reading formats which don't have a
2025-07-17T07:05:47.1832090Z     metadata file, like Torch Save files.
2025-07-17T07:05:47.1832130Z     
2025-07-17T07:05:47.1832240Z     . N.B. Intended to be used with BroadcastingTorchSaveReader
2025-07-17T07:05:47.1832280Z     
2025-07-17T07:05:47.1832330Z     .. warning::
2025-07-17T07:05:47.1832430Z         Current implementation only supports loading Tensors.
2025-07-17T07:05:47.1832470Z     
2025-07-17T07:05:47.1832530Z     >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:47.1832590Z     >>> sd = {"mode": model}
2025-07-17T07:05:47.1832630Z     >>> dcp.load(
2025-07-17T07:05:47.1832670Z     >>>    sd,
2025-07-17T07:05:47.1832760Z     >>>    storage_reader=BroadcastingTorchSaveReader(),
2025-07-17T07:05:47.1832830Z     >>>    planner=DynamicMetaLoadPlanner(),
2025-07-17T07:05:47.1832900Z     >>>    checkpoint_id="path_to_model.pt"
2025-07-17T07:05:47.1832940Z     >>> )
2025-07-17T07:05:47.1832980Z     
2025-07-17T07:05:47.1833120Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1833160Z     
2025-07-17T07:05:47.1833210Z       warnings.warn(msg)
2025-07-17T07:05:47.1833250Z     
2025-07-17T07:05:47.1833350Z --- Parse Warning: 57 / 136 ---
2025-07-17T07:05:47.1834060Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SavePlanner in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/planner.py line=122.
2025-07-17T07:05:47.1834250Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1834290Z     
2025-07-17T07:05:47.1834450Z     Abstract class defining the protocol used by save_state_dict to plan the save process.
2025-07-17T07:05:47.1834500Z     
2025-07-17T07:05:47.1834670Z     SavePlanners are stateful objects that can be used to customize the whole save process.
2025-07-17T07:05:47.1834710Z     
2025-07-17T07:05:47.1834880Z     SavePlanner acts as an access proxy to the state_dict, so any transformation done to it
2025-07-17T07:05:47.1834940Z     will be visible to the whole process.
2025-07-17T07:05:47.1834980Z     
2025-07-17T07:05:47.1835170Z     A planner subclass can expect the following sequence of calls during save_state_dict:
2025-07-17T07:05:47.1835220Z     
2025-07-17T07:05:47.1835290Z     1) set_up_planner - called on all ranks.
2025-07-17T07:05:47.1835370Z         Signals the start of a checkpoint save.
2025-07-17T07:05:47.1835410Z     
2025-07-17T07:05:47.1835480Z     2) create_local_plan - called on all ranks.
2025-07-17T07:05:47.1835650Z         Process the state_dict and produces a `SavePlan` that will be sent for global planning.
2025-07-17T07:05:47.1835690Z     
2025-07-17T07:05:47.1835800Z     3) create_global_plan - called on the coordinator rank only.
2025-07-17T07:05:47.1835920Z         Takes the SavePlan from all ranks and make any global decision.
2025-07-17T07:05:47.1835960Z     
2025-07-17T07:05:47.1836020Z     4) finish_plan - called on all ranks.
2025-07-17T07:05:47.1836150Z         This gives each rank a chance to adjust to global planning decisions.
2025-07-17T07:05:47.1836190Z     
2025-07-17T07:05:47.1836280Z     5) resolve_data - called multiple times on each rank
2025-07-17T07:05:47.1836410Z         Lookups a value on the `state_dict` for the storage layer to write.
2025-07-17T07:05:47.1836450Z     
2025-07-17T07:05:47.1836630Z     Users are recommended to extend DefaultSavePlanner instead of this interface directly as
2025-07-17T07:05:47.1836740Z     most changes can be expressed by changes in a single method.
2025-07-17T07:05:47.1836780Z     
2025-07-17T07:05:47.1836850Z     There are 3 usual patterns of extension:
2025-07-17T07:05:47.1836890Z     
2025-07-17T07:05:47.1837050Z     Rewriting state_dict. This is the simplest way to extend the save process as it
2025-07-17T07:05:47.1837180Z     doesn't requite understanding the intrincacies of how SavePlan works:
2025-07-17T07:05:47.1837220Z     
2025-07-17T07:05:47.1837290Z     >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:47.1837360Z     >>> class RenamePlanner(DefaultSavePlanner):
2025-07-17T07:05:47.1837420Z     >>>     def set_up_planner(
2025-07-17T07:05:47.1837460Z     >>>         self,
2025-07-17T07:05:47.1837530Z     >>>         state_dict: STATE_DICT_TYPE,
2025-07-17T07:05:47.1837600Z     >>>         storage_meta: Optional[StorageMeta],
2025-07-17T07:05:47.1837670Z     >>>         is_coordinator: bool,
2025-07-17T07:05:47.1837710Z     >>>     ) -> None:
2025-07-17T07:05:47.1837770Z     >>> # prefix all keys with `foo_``
2025-07-17T07:05:47.1837950Z     >>>         super().set_up_planner({"foo_" + k: v for k, v in state_dict.items()}, storage_meta, is_coordinator)
2025-07-17T07:05:47.1838000Z     
2025-07-17T07:05:47.1838190Z     Modifying local plan and lookup in tandem. This is useful when fine control of how data is persisted
2025-07-17T07:05:47.1838230Z     
2025-07-17T07:05:47.1838290Z     >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:47.1838370Z     >>> class FP16Planner(DefaultSavePlanner):
2025-07-17T07:05:47.1838430Z     >>>     def create_local_plan(self):
2025-07-17T07:05:47.1838500Z     >>>         plan = super().create_local_plan()
2025-07-17T07:05:47.1838560Z     >>>         for p in plan:
2025-07-17T07:05:47.1838640Z     >>>             if p.tensor_data is not None:
2025-07-17T07:05:47.1838750Z     >>>                 p.tensor_data.properties.dtype = torch.float16
2025-07-17T07:05:47.1838800Z     >>>         return plan
2025-07-17T07:05:47.1838870Z     >>>
2025-07-17T07:05:47.1838930Z     >>>     def resolve_data(self, write_item):
2025-07-17T07:05:47.1839010Z     >>>         item = super().resolve_data(write_item)
2025-07-17T07:05:47.1839170Z     >>>         return item if write_item.type == WriteItemType.BYTE_IO else item.to(torch.float16)
2025-07-17T07:05:47.1839210Z     
2025-07-17T07:05:47.1839410Z     Using the global planning step to make central decisions that can't be made individually by each rank
2025-07-17T07:05:47.1839450Z     
2025-07-17T07:05:47.1839520Z     >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:47.1839580Z     >>> from itertools import zip_longest
2025-07-17T07:05:47.1839670Z     >>> from dataclasses import replace
2025-07-17T07:05:47.1839800Z     >>> class DDPLoadBalancingPlanner(DefaultSavePlanner):
2025-07-17T07:05:47.1839970Z     >>> # This uses the default local plan behavior of having all non-sharded writes in rank 0
2025-07-17T07:05:47.1840040Z     >>> # This sample doesn't handle ShardedTensors
2025-07-17T07:05:47.1840120Z     >>>     def create_global_plan(self, all_plans):
2025-07-17T07:05:47.1840210Z     >>>         iters = [iter(all_plans[0].items)] * len(all_plans)
2025-07-17T07:05:47.1840270Z     >>>         items_per_rank = [
2025-07-17T07:05:47.1840350Z     >>>             [item for item in items if item is not None]
2025-07-17T07:05:47.1840450Z     >>>             for items in zip(*zip_longest(*iters), strict=True)
2025-07-17T07:05:47.1840490Z     >>>         ]
2025-07-17T07:05:47.1840550Z     >>>         all_plans = [
2025-07-17T07:05:47.1840610Z     >>>             replace(plan, items=items)
2025-07-17T07:05:47.1840730Z     >>>             for plan, items in zip(all_plans, items_per_rank, strict=True)
2025-07-17T07:05:47.1840770Z     >>>         ]
2025-07-17T07:05:47.1840860Z     >>>         return super().create_global_plan(all_plans)
2025-07-17T07:05:47.1840900Z     
2025-07-17T07:05:47.1841060Z     Finally, some planners need to save additional metadata in the checkpoint, this is
2025-07-17T07:05:47.1841220Z     accomplished by having each rank contribute their data items in the local plan and
2025-07-17T07:05:47.1841280Z     the global planner aggregate them:
2025-07-17T07:05:47.1841320Z     
2025-07-17T07:05:47.1841390Z     >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:47.1841480Z     >>> class SaveExtraDataPlanner(DefaultSavePlanner):
2025-07-17T07:05:47.1841560Z     >>>     def create_local_plan(self) -> SavePlan:
2025-07-17T07:05:47.1841630Z     >>>         plan = super().create_local_plan()
2025-07-17T07:05:47.1841720Z     >>>         return replace(plan, planner_data="per-rank-data")
2025-07-17T07:05:47.1841760Z     >>>
2025-07-17T07:05:47.1841950Z     >>>     def create_global_plan(self, all_plans: List[SavePlan]) -> Tuple[List[SavePlan], Metadata]:
2025-07-17T07:05:47.1842070Z     >>>         global_plan, metadata = super().create_global_plan(all_plans)
2025-07-17T07:05:47.1842170Z     >>>         merged_data = [p.planner_data for p in global_plan]
2025-07-17T07:05:47.1842270Z     >>>         metadata = replace(metadata, planner_data=merged_data)
2025-07-17T07:05:47.1842330Z     >>>         return global_plan, metadata
2025-07-17T07:05:47.1842380Z     
2025-07-17T07:05:47.1842530Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1842570Z     
2025-07-17T07:05:47.1842620Z       warnings.warn(msg)
2025-07-17T07:05:47.1842660Z     
2025-07-17T07:05:47.1842750Z --- Parse Warning: 58 / 136 ---
2025-07-17T07:05:47.1843460Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LoadPlanner in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/planner.py line=305.
2025-07-17T07:05:47.1843620Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1843660Z     
2025-07-17T07:05:47.1843850Z     Abstract class defining the protocol used by load_state_dict to plan the load process.
2025-07-17T07:05:47.1843890Z     
2025-07-17T07:05:47.1844060Z     LoadPlanner are stateful objects that can be used to customize the whole load process.
2025-07-17T07:05:47.1844100Z     
2025-07-17T07:05:47.1844270Z     LoadPlanner acts as an access proxy to the state_dict, so any transformation done to it
2025-07-17T07:05:47.1844330Z     will be visible to the whole process.
2025-07-17T07:05:47.1844370Z     
2025-07-17T07:05:47.1844540Z     A planner subclass can expect the following sequence of calls during load_state_dict:
2025-07-17T07:05:47.1844580Z     
2025-07-17T07:05:47.1844670Z     1) set_up_planner - called on all ranks.
2025-07-17T07:05:47.1844770Z         Signals the start of loading a checkpoint.
2025-07-17T07:05:47.1844810Z     
2025-07-17T07:05:47.1844880Z     2) create_local_plan - called on all ranks.
2025-07-17T07:05:47.1845050Z         Process the state_dict and produces a `LoadPlan` that will be sent for global planning.
2025-07-17T07:05:47.1845090Z     
2025-07-17T07:05:47.1845210Z     3) create_global_plan - called on the coordinator rank only.
2025-07-17T07:05:47.1845320Z         Takes the LoadPlan from all ranks and make any global decision.
2025-07-17T07:05:47.1845370Z     
2025-07-17T07:05:47.1845450Z     4) load_bytes - called multiple times on each rank
2025-07-17T07:05:47.1845550Z         This is called once per non-tensor value in state_dict.
2025-07-17T07:05:47.1845590Z     
2025-07-17T07:05:47.1845720Z     5) resolve_tensor and commit_tensor - called multiple times on each rank
2025-07-17T07:05:47.1845830Z         They are called in pair for each Tensor value in state_dict.
2025-07-17T07:05:47.1845870Z     
2025-07-17T07:05:47.1846060Z     Users are recommended to extend DefaultLoadPlanner instead of this interface directly as
2025-07-17T07:05:47.1846160Z     most changes can be expressed by changes in a single method.
2025-07-17T07:05:47.1846200Z     
2025-07-17T07:05:47.1846280Z     There are two usual patterns of extension:
2025-07-17T07:05:47.1846320Z     
2025-07-17T07:05:47.1846470Z     Rewriting state_dict. This is the simplest way to extend the load process as it
2025-07-17T07:05:47.1846650Z     doesn't requite understanding the intrincacies of how LoadPlan works. We need
2025-07-17T07:05:47.1846780Z     to keep a reference to the original state_dict as load happens in place so
2025-07-17T07:05:47.1846860Z     we need to be able to perform it in place
2025-07-17T07:05:47.1846890Z     
2025-07-17T07:05:47.1846960Z     >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:47.1847030Z     >>> class RenamePlanner(DefaultLoadPlanner):
2025-07-17T07:05:47.1847090Z     >>>     def set_up_planner(
2025-07-17T07:05:47.1847140Z     >>>         self,
2025-07-17T07:05:47.1847200Z     >>>         state_dict: STATE_DICT_TYPE,
2025-07-17T07:05:47.1847260Z     >>>         metadata: Metadata,
2025-07-17T07:05:47.1847310Z     >>>         is_coordinator: bool,
2025-07-17T07:05:47.1847360Z     >>>     ) -> None:
2025-07-17T07:05:47.1847440Z     >>>         self.original_state_dict = state_dict
2025-07-17T07:05:47.1847550Z     >>>         state_dict = {"foo_" + k: v for k, v in state_dict.items()}
2025-07-17T07:05:47.1847590Z     >>>
2025-07-17T07:05:47.1847660Z     >>>         if self.flatten_sharded_tensors:
2025-07-17T07:05:47.1847750Z     >>>             state_dict = _flatten_sharded_tensors(state_dict)
2025-07-17T07:05:47.1847790Z     >>>
2025-07-17T07:05:47.1847850Z     >>>         if self.flatten_state_dict:
2025-07-17T07:05:47.1847970Z     >>>             state_dict, self.mappings = flatten_state_dict(state_dict)
2025-07-17T07:05:47.1848000Z     >>>
2025-07-17T07:05:47.1848070Z     >>>         self.state_dict = state_dict
2025-07-17T07:05:47.1848160Z     >>>         self.metadata = metadata
2025-07-17T07:05:47.1848230Z     >>>         self.is_coordinator = is_coordinator
2025-07-17T07:05:47.1848280Z     >>>
2025-07-17T07:05:47.1848350Z     >>>     def load_bytes(self, read_item, value):
2025-07-17T07:05:47.1848420Z     >>> # Remove the "foo_" prefix
2025-07-17T07:05:47.1848610Z     >>>         self.original_state_dict[read_item.dest_index.fqn[4:]] = torch.load(value, weights_only=False)
2025-07-17T07:05:47.1848660Z     
2025-07-17T07:05:47.1848700Z     
2025-07-17T07:05:47.1848850Z     Modifying resolve_tensor and commit_tensor to handle load time transformation.
2025-07-17T07:05:47.1848890Z     
2025-07-17T07:05:47.1848950Z     >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:47.1849040Z     >>> class MetaModelMaterialize(DefaultSavePlanner):
2025-07-17T07:05:47.1849120Z     >>>     def resolve_tensor(self, read_item):
2025-07-17T07:05:47.1849210Z     >>>         tensor = super().resolve_tensor(read_item)
2025-07-17T07:05:47.1849330Z     >>>         return torch.empty_like(tensor, device="cpu")
2025-07-17T07:05:47.1849370Z     >>>
2025-07-17T07:05:47.1849440Z     >>>     def commit_tensor(self, read_item, tensor):
2025-07-17T07:05:47.1849540Z     >>>         self.state_dict[read_item.dest_index.fqn] = tensor
2025-07-17T07:05:47.1849580Z     
2025-07-17T07:05:47.1849730Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1849770Z     
2025-07-17T07:05:47.1849820Z       warnings.warn(msg)
2025-07-17T07:05:47.1849860Z     
2025-07-17T07:05:47.1849960Z --- Parse Warning: 59 / 136 ---
2025-07-17T07:05:47.1850650Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=get_state_dict in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict.py line=1118.
2025-07-17T07:05:47.1850810Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1850850Z     
2025-07-17T07:05:47.1850950Z     Return the model state_dict and optimizers state_dict.
2025-07-17T07:05:47.1850990Z     
2025-07-17T07:05:47.1851120Z     ``get_state_dict`` can process any module that is parallelized by PyTorch
2025-07-17T07:05:47.1851270Z     FSDP/fully_shard, DDP/replicate, tensor_parallel/parallelize_module, and any
2025-07-17T07:05:47.1851420Z     combination of these parallelisms. The main functions of ``get_state_dict``
2025-07-17T07:05:47.1851550Z     are: 1.) returning a model and optimizer state_dict that can be resharded
2025-07-17T07:05:47.1851670Z     with a different number of trainers and/or different parallelisms.
2025-07-17T07:05:47.1851820Z     2.) hiding the parallelism-specific state_dict APIs. Users don't have to call
2025-07-17T07:05:47.1851870Z     these APIs.
2025-07-17T07:05:47.1851940Z     3.) sanity checking the result state_dict.
2025-07-17T07:05:47.1851980Z     
2025-07-17T07:05:47.1852110Z     The keys of the result state dictionary are the canonical FQNs (Fully
2025-07-17T07:05:47.1852250Z     Qualified Names).  A canonical FQN refers to the FQN based on a parameter's
2025-07-17T07:05:47.1852390Z     position in an nn.Module hierarchy. More specifically, a canonical FQN to a
2025-07-17T07:05:47.1852520Z     parameter is the FQN returned by ``module.named_parameters()`` or
2025-07-17T07:05:47.1852650Z     ``module.named_buffers()`` when the module is not distributed by any
2025-07-17T07:05:47.1852800Z     parallelisms. Since the optimizer internally uses parameter IDs to represent
2025-07-17T07:05:47.1852930Z     a parameter, there will be a conversion from the parameter IDs to the
2025-07-17T07:05:47.1852990Z     canonical FQNs when calling this API.
2025-07-17T07:05:47.1853030Z     
2025-07-17T07:05:47.1853160Z     ``get_state_dict`` can also process a module that is not parallelized. In
2025-07-17T07:05:47.1853300Z     such a case, ``get_state_dict`` only performs one function -- converting the
2025-07-17T07:05:47.1853400Z     optimizer parameter IDs to the canonical FQNs.
2025-07-17T07:05:47.1853440Z     
2025-07-17T07:05:47.1853490Z     Example:
2025-07-17T07:05:47.1853540Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1853640Z         >>> import torch
2025-07-17T07:05:47.1853790Z         >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-07-17T07:05:47.1853910Z         >>> from torch.nn.parallel import DistributedDataParallel as DDP
2025-07-17T07:05:47.1854050Z         >>> from torch.distributed.checkpoint.state_dict import get_state_dict
2025-07-17T07:05:47.1854090Z     
2025-07-17T07:05:47.1854160Z         >>> fsdp_model = FSDP(copy.deepcopy(model))
2025-07-17T07:05:47.1854280Z         >>> fsdp_optim = torch.optim.Adam(model.parameters(), lr=1e-3)
2025-07-17T07:05:47.1854350Z         >>> ddp_model = DDP(copy.deepcopy(model))
2025-07-17T07:05:47.1854470Z         >>> ddp_optim = torch.optim.Adam(model.parameters(), lr=1e-3)
2025-07-17T07:05:47.1854530Z     
2025-07-17T07:05:47.1854570Z     
2025-07-17T07:05:47.1854710Z         >>> ddp_state_dict, ddp_optim_state_dict = get_state_dict(ddp_model, ddp_optim)
2025-07-17T07:05:47.1854820Z         >>> fsdp_state_dict, fsdp_optim_state_dict = get_state_dict(
2025-07-17T07:05:47.1854880Z         ...     fsdp_model, fsdp_optim
2025-07-17T07:05:47.1854920Z         ... )
2025-07-17T07:05:47.1854960Z     
2025-07-17T07:05:47.1855090Z         >>> # if we simply call ddp_model.state_dict() and fsdp_model.state_dict(),
2025-07-17T07:05:47.1855140Z         >>> # the asserts will fail.
2025-07-17T07:05:47.1855220Z         >>> assert ddp_state_dict == fsdp_state_dict
2025-07-17T07:05:47.1855310Z         >>> assert ddp_optim_state == fsdp_optim_state_dict
2025-07-17T07:05:47.1855350Z     
2025-07-17T07:05:47.1855390Z     
2025-07-17T07:05:47.1855430Z     Args:
2025-07-17T07:05:47.1855520Z         model (nn.Module): the nn.Module to the model.
2025-07-17T07:05:47.1855630Z         optimizers (Union[None, Optimizer, Iterable[Optimizer]]):
2025-07-17T07:05:47.1855720Z             The optimizers that are used to optimize ``model``.
2025-07-17T07:05:47.1855890Z         submodules (deprecated): Optional[set[nn.Module]]: only return the model parameters
2025-07-17T07:05:47.1855950Z             that belong to the submodules.
2025-07-17T07:05:47.1856060Z         options (StateDictOptions): the options to control how
2025-07-17T07:05:47.1856180Z             model state_dict and optimizer state_dict should be returned. See
2025-07-17T07:05:47.1856250Z             `StateDictOptions` for the details.
2025-07-17T07:05:47.1856290Z     
2025-07-17T07:05:47.1856340Z     Returns:
2025-07-17T07:05:47.1856450Z         ``Tuple`` that contain model state_dict and optimizer state_dict.
2025-07-17T07:05:47.1856490Z     
2025-07-17T07:05:47.1856630Z     :rtype: typing.Tuple[typing.Dict[str, ValueType], OptimizerStateType]
2025-07-17T07:05:47.1856670Z     
2025-07-17T07:05:47.1856820Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1856860Z     
2025-07-17T07:05:47.1856910Z       warnings.warn(msg)
2025-07-17T07:05:47.1856950Z     
2025-07-17T07:05:47.1857050Z --- Parse Warning: 60 / 136 ---
2025-07-17T07:05:47.1857740Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=save in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=96.
2025-07-17T07:05:47.1857890Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1857930Z     
2025-07-17T07:05:47.1858000Z     Save a distributed model in SPMD style.
2025-07-17T07:05:47.1858040Z     
2025-07-17T07:05:47.1858160Z     This function is different from ``torch.save()`` as it handles
2025-07-17T07:05:47.1858310Z     ``ShardedTensor`` , and ``DTensor`` by having each rank only save their local shards.
2025-07-17T07:05:47.1858350Z     
2025-07-17T07:05:47.1858530Z     For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``),
2025-07-17T07:05:47.1858620Z     save will call ``state_dict`` before serialization.
2025-07-17T07:05:47.1858660Z     
2025-07-17T07:05:47.1858740Z     .. warning::
2025-07-17T07:05:47.1858880Z         There is no guarantees of Backwards Compatibility across PyTorch versions
2025-07-17T07:05:47.1858940Z         for saved state_dicts.
2025-07-17T07:05:47.1858980Z     
2025-07-17T07:05:47.1859020Z     .. warning::
2025-07-17T07:05:47.1859150Z         If using the `process_group` argument, make sure that only its ranks
2025-07-17T07:05:47.1859270Z         call `save_state_dict` and that all data in state_dict belong to it.
2025-07-17T07:05:47.1859310Z     
2025-07-17T07:05:47.1859350Z     .. note::
2025-07-17T07:05:47.1859510Z         When saving checkpoint for FSDP's `ShardingStrategy.HYBRID_SHARD`, only one of
2025-07-17T07:05:47.1859690Z         the shard_group should be calling `save_state_dict` and the corresponding process
2025-07-17T07:05:47.1859790Z         group needs to be passed in.
2025-07-17T07:05:47.1859820Z     
2025-07-17T07:05:47.1859870Z     .. note::
2025-07-17T07:05:47.1860030Z         If no process group is available, this function assumes the intention is to save the
2025-07-17T07:05:47.1860090Z          state_dict in the local process.
2025-07-17T07:05:47.1860130Z     
2025-07-17T07:05:47.1860170Z     .. note:
2025-07-17T07:05:47.1860260Z         Rank 0 is assumed to be the coordinator rank.
2025-07-17T07:05:47.1860290Z     
2025-07-17T07:05:47.1860330Z     
2025-07-17T07:05:47.1860380Z     Args:
2025-07-17T07:05:47.1860470Z         state_dict (Dict[str, Any]): The state_dict to save.
2025-07-17T07:05:47.1860550Z         checkpoint_id (Union[str, os.PathLike, None]):
2025-07-17T07:05:47.1860680Z             The ID of this checkpoint instance. The meaning of the checkpoint_id
2025-07-17T07:05:47.1860800Z             depends on the storage. It can be a path to a folder or to a file.
2025-07-17T07:05:47.1860910Z             It can also be a key if the storage is a key-value store.
2025-07-17T07:05:47.1860960Z             (Default: ``None``)
2025-07-17T07:05:47.1861040Z         storage_writer (Optional[StorageWriter]):
2025-07-17T07:05:47.1861160Z             Instance of StorageWriter used to perform writes. If this is not
2025-07-17T07:05:47.1861290Z             specified, DCP will automatically infer the writer based on the
2025-07-17T07:05:47.1861410Z             checkpoint_id. If checkpoint_id is also None, an exception will
2025-07-17T07:05:47.1861470Z             be raised. (Default: ``None``)
2025-07-17T07:05:47.1861530Z         planner (Optional[SavePlanner]):
2025-07-17T07:05:47.1861650Z             Instance of SavePlanner. If this is not specified, the default
2025-07-17T07:05:47.1861730Z             planner will be used. (Default: ``None``)
2025-07-17T07:05:47.1861800Z         process_group (Optional[ProcessGroup]):
2025-07-17T07:05:47.1861920Z             ProcessGroup to be used for cross-rank synchronization.
2025-07-17T07:05:47.1861970Z             (Default: ``None``)
2025-07-17T07:05:47.1862020Z         no_dist (bool):
2025-07-17T07:05:47.1862120Z             If ``True``, this function will assume the intent is to load
2025-07-17T07:05:47.1862230Z             a checkpoint without using cross-rank synchronization.
2025-07-17T07:05:47.1862280Z             (Default: ``False``)
2025-07-17T07:05:47.1862320Z     
2025-07-17T07:05:47.1862360Z     Returns:
2025-07-17T07:05:47.1862460Z         Metadata: Metadata object for the saved checkpoint.
2025-07-17T07:05:47.1862500Z     
2025-07-17T07:05:47.1862540Z     Example:
2025-07-17T07:05:47.1862590Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1862650Z         >>> my_model = MyModule()
2025-07-17T07:05:47.1862690Z     
2025-07-17T07:05:47.1862750Z         >>> state_dict = {"model": my_model}
2025-07-17T07:05:47.1862800Z     
2025-07-17T07:05:47.1862940Z         >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter(
2025-07-17T07:05:47.1863020Z         ...     "/checkpoint/1"
2025-07-17T07:05:47.1863060Z         ... )
2025-07-17T07:05:47.1863140Z         >>> torch.distributed.checkpoint.save(
2025-07-17T07:05:47.1863190Z         >>>     state_dict=state_dict,
2025-07-17T07:05:47.1863290Z         >>>     storage_writer=fs_storage_writer,
2025-07-17T07:05:47.1863330Z         >>> )
2025-07-17T07:05:47.1863360Z     
2025-07-17T07:05:47.1863410Z     .. note::
2025-07-17T07:05:47.1863530Z         save_state_dict uses collectives to coordinate writes across ranks.
2025-07-17T07:05:47.1863660Z         For NCCL-based process groups, internal tensor representations of
2025-07-17T07:05:47.1863800Z         objects must be moved to the GPU device before communication takes place.
2025-07-17T07:05:47.1863930Z         In this case, the device used is given by ``torch.cuda.current_device()``
2025-07-17T07:05:47.1864080Z         and it is the user's responsibility to ensure that this is set so that
2025-07-17T07:05:47.1864220Z         each rank has an individual GPU, via ``torch.cuda.set_device()``.
2025-07-17T07:05:47.1864260Z     
2025-07-17T07:05:47.1864410Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1864450Z     
2025-07-17T07:05:47.1864500Z       warnings.warn(msg)
2025-07-17T07:05:47.1864540Z     
2025-07-17T07:05:47.1864640Z --- Parse Warning: 61 / 136 ---
2025-07-17T07:05:47.1865340Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=async_save in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=221.
2025-07-17T07:05:47.1865500Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1865660Z     Asynchronous version of ``save``. This code first de-stages the state_dict on to the
2025-07-17T07:05:47.1865830Z         staging storage (defaults to CPU memory), and then calls the `save` in a separate thread.
2025-07-17T07:05:47.1865870Z     
2025-07-17T07:05:47.1865920Z         .. warning::
2025-07-17T07:05:47.1866020Z             This feature is experimental and subject to change.
2025-07-17T07:05:47.1866100Z             MUST CALL CLOSE AFTER LAST CHECKPOINT IS SAVED
2025-07-17T07:05:47.1866140Z     
2025-07-17T07:05:47.1866180Z         Args:
2025-07-17T07:05:47.1866280Z             state_dict (Dict[str, Any]): The state_dict to save.
2025-07-17T07:05:47.1866360Z             checkpoint_id (Union[str, os.PathLike, None]):
2025-07-17T07:05:47.1866490Z                 The ID of this checkpoint instance. The meaning of the checkpoint_id
2025-07-17T07:05:47.1866610Z                 depends on the storage. It can be a path to a folder or to a file.
2025-07-17T07:05:47.1866720Z                 It can also be a key if the storage is a key-value store.
2025-07-17T07:05:47.1866770Z                 (Default: ``None``)
2025-07-17T07:05:47.1866850Z             storage_writer (Optional[StorageWriter]):
2025-07-17T07:05:47.1866980Z                 Instance of StorageWriter used to perform 'stage' and  'save'. If
2025-07-17T07:05:47.1867120Z                 this is not specified, DCP will automatically infer the writer based on the
2025-07-17T07:05:47.1867250Z                 checkpoint_id. If checkpoint_id is also None, an exception will
2025-07-17T07:05:47.1867310Z                 be raised. (Default: ``None``)
2025-07-17T07:05:47.1867380Z             planner (Optional[SavePlanner]):
2025-07-17T07:05:47.1867500Z                 Instance of SavePlanner. If this is not specified, the default
2025-07-17T07:05:47.1867580Z                 planner will be used. (Default: ``None``)
2025-07-17T07:05:47.1867650Z             process_group (Optional[ProcessGroup]):
2025-07-17T07:05:47.1867760Z                 ProcessGroup to be used for cross-rank synchronization.
2025-07-17T07:05:47.1867820Z                 (Default: ``None``)
2025-07-17T07:05:47.1867950Z             async_checkpointer_type (AsyncCheckpointerType):
2025-07-17T07:05:47.1868050Z                 whether to do checkpoint in separate thread or process
2025-07-17T07:05:47.1868140Z                 (Default: ``AsyncCheckpointerType.THREAD``)
2025-07-17T07:05:47.1868220Z             async_stager (AsyncStager):
2025-07-17T07:05:47.1868380Z                 provides staging implementation. If storage_writer implements AsyncStager
2025-07-17T07:05:47.1868510Z                 and async_stager is provided, async_stager will be used for staging
2025-07-17T07:05:47.1868550Z     
2025-07-17T07:05:47.1868590Z         Returns:
2025-07-17T07:05:47.1868720Z             Future: A future holding the resultant Metadata object from `save`.
2025-07-17T07:05:47.1868760Z     
2025-07-17T07:05:47.1868800Z         Example:
2025-07-17T07:05:47.1868850Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1868910Z             >>> my_model = MyModule()
2025-07-17T07:05:47.1868970Z     
2025-07-17T07:05:47.1869060Z             >>> state_dict = {"model": my_model}
2025-07-17T07:05:47.1869100Z     
2025-07-17T07:05:47.1869240Z             >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter(
2025-07-17T07:05:47.1869300Z             ...     "/checkpoint/1"
2025-07-17T07:05:47.1869340Z             ... )
2025-07-17T07:05:47.1869470Z             >>> checkpoint_future = torch.distributed.checkpoint.async_save(
2025-07-17T07:05:47.1869530Z             >>>     state_dict=state_dict,
2025-07-17T07:05:47.1869600Z             >>>     storage_writer=fs_storage_writer,
2025-07-17T07:05:47.1869640Z             >>> )
2025-07-17T07:05:47.1869680Z             >>>
2025-07-17T07:05:47.1869740Z             >>> # ... do some work ...
2025-07-17T07:05:47.1869780Z             >>>
2025-07-17T07:05:47.1869840Z             >>> checkpoint_future.result()
2025-07-17T07:05:47.1869880Z     
2025-07-17T07:05:47.1869920Z         
2025-07-17T07:05:47.1870070Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1870120Z     
2025-07-17T07:05:47.1870170Z       warnings.warn(msg)
2025-07-17T07:05:47.1870210Z     
2025-07-17T07:05:47.1870300Z --- Parse Warning: 62 / 136 ---
2025-07-17T07:05:47.1871000Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/state_dict_loader.py line=62.
2025-07-17T07:05:47.1871150Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1871190Z     
2025-07-17T07:05:47.1871310Z     Load a checkpoint into a distributed state dict in SPMD style.
2025-07-17T07:05:47.1871350Z     
2025-07-17T07:05:47.1871480Z     Each rank must have the same keys in their ``state_dict`` provided to this
2025-07-17T07:05:47.1871620Z     API. Mismatched keys may result in hangs or errors. If unsure, you can use
2025-07-17T07:05:47.1871750Z     the ``utils._assert_same_keys`` API to check (but may incur communication
2025-07-17T07:05:47.1871800Z     costs).
2025-07-17T07:05:47.1871840Z     
2025-07-17T07:05:47.1871940Z     Each rank will try to read the least amount of data necessary
2025-07-17T07:05:47.1872080Z     to fulfill the requested `state_dict`. When loading :class:`ShardedTensor`
2025-07-17T07:05:47.1872230Z     or :class:`DTensor` instances, each rank only reads data for their local shards.
2025-07-17T07:05:47.1872270Z     
2025-07-17T07:05:47.1875720Z     For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``),
2025-07-17T07:05:47.1875890Z     load will first call ``state_dict`` before attempting deserialization, followed by
2025-07-17T07:05:47.1875990Z     ``load_state_dict`` once the deserialization is complete.
2025-07-17T07:05:47.1876150Z     For each non-``Stateful`` object, load will deserialize the object, and then replace
2025-07-17T07:05:47.1876300Z     it in the ``state_dict`` with the deserialized object.
2025-07-17T07:05:47.1876350Z     
2025-07-17T07:05:47.1876400Z     .. warning::
2025-07-17T07:05:47.1876500Z         All tensors in ``state_dict`` must be allocated on their
2025-07-17T07:05:47.1876630Z         destination device *prior to* calling this function.
2025-07-17T07:05:47.1876670Z     
2025-07-17T07:05:47.1876800Z         All non-tensor data is loaded using `torch.load()` and modified in place
2025-07-17T07:05:47.1876850Z         on state_dict.
2025-07-17T07:05:47.1876890Z     
2025-07-17T07:05:47.1876940Z     .. warning::
2025-07-17T07:05:47.1877060Z         Users must call `load_state_dict` on the root module to ensure load
2025-07-17T07:05:47.1877170Z         pos-processing and non-tensor data properly propagates.
2025-07-17T07:05:47.1877210Z     
2025-07-17T07:05:47.1877250Z     .. note:
2025-07-17T07:05:47.1877380Z         If no process group is initialized, this function will assume the intent
2025-07-17T07:05:47.1877530Z         is to load a checkpoint into the local process. This can be useful in the
2025-07-17T07:05:47.1877700Z         case of local inference, and when using regular Tensors (as opposed to DTensor
2025-07-17T07:05:47.1877760Z          or ShardedTensor)
2025-07-17T07:05:47.1877800Z     
2025-07-17T07:05:47.1877840Z     .. note:
2025-07-17T07:05:47.1877920Z         Rank 0 is assumed to be the coordinator rank.
2025-07-17T07:05:47.1877960Z     
2025-07-17T07:05:47.1878000Z     Args:
2025-07-17T07:05:47.1878130Z         state_dict (Dict[str, Any]): The state_dict to load the checkpoint into.
2025-07-17T07:05:47.1878210Z         checkpoint_id (Union[str, os.PathLike, None]):
2025-07-17T07:05:47.1878340Z             The ID of this checkpoint instance. The meaning of the checkpoint_id
2025-07-17T07:05:47.1878460Z             depends on the storage. It can be a path to a folder or to a file.
2025-07-17T07:05:47.1878560Z             It can also be a key if the storage is a key-value store.
2025-07-17T07:05:47.1878620Z             (Default: ``None``)
2025-07-17T07:05:47.1878700Z         storage_reader (Optional[StorageReader]):
2025-07-17T07:05:47.1878820Z             Instance of StorageWriter used to perform reads. If this is not
2025-07-17T07:05:47.1878940Z             specified, DCP will automatically infer the reader based on the
2025-07-17T07:05:47.1879060Z             checkpoint_id. If checkpoint_id is also None, an exception will
2025-07-17T07:05:47.1879130Z             be raised. (Default: ``None``)
2025-07-17T07:05:47.1879190Z         planner (Optional[LoadPlanner]):
2025-07-17T07:05:47.1879310Z             Instance of LoadPlanner. If this is not specified, the default
2025-07-17T07:05:47.1879380Z             planner will be used. (Default: ``None``)
2025-07-17T07:05:47.1879460Z         process_group (Optional[ProcessGroup]):
2025-07-17T07:05:47.1879570Z             ProcessGroup to be used for cross-rank synchronization.
2025-07-17T07:05:47.1879620Z             (Default: ``None``)
2025-07-17T07:05:47.1879750Z         no_dist (bool): If ``True``, this function will assume the intent is to load
2025-07-17T07:05:47.1879900Z             a checkpoint without using cross-rank synchronization. (Default: ``False``)
2025-07-17T07:05:47.1879950Z     Returns:
2025-07-17T07:05:47.1879990Z         None.
2025-07-17T07:05:47.1880030Z     
2025-07-17T07:05:47.1880070Z     Examples
2025-07-17T07:05:47.1880130Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1880180Z         >>> my_model = MyModule()
2025-07-17T07:05:47.1880260Z         >>> optimizer = Adagrad(my_model.parameters())
2025-07-17T07:05:47.1880340Z         >>> model_state_dict = my_model.state_dict()
2025-07-17T07:05:47.1880480Z         >>> fs_storage_reader = torch.distributed.checkpoint.FileSystemReader(
2025-07-17T07:05:47.1880530Z         ...     "/checkpoint/1"
2025-07-17T07:05:47.1880570Z         ... )
2025-07-17T07:05:47.1880610Z     
2025-07-17T07:05:47.1880700Z         >>> torch.distributed.checkpoint.load_state_dict(
2025-07-17T07:05:47.1880770Z         >>>     state_dict=model_state_dict,
2025-07-17T07:05:47.1880890Z         >>>     storage_reader=fs_storage_reader,
2025-07-17T07:05:47.1880930Z         >>> )
2025-07-17T07:05:47.1880970Z     
2025-07-17T07:05:47.1881090Z         >>> # module.load_state_dict() function might have customized steps
2025-07-17T07:05:47.1881190Z         >>> # to flush the state_dict, must call it to
2025-07-17T07:05:47.1881250Z         >>> # ensure correct behavior.
2025-07-17T07:05:47.1881330Z         >>> my_model.load_state_dict(model_state_dict)
2025-07-17T07:05:47.1881370Z     
2025-07-17T07:05:47.1881410Z     .. note::
2025-07-17T07:05:47.1881530Z         load_state_dict uses collectives to coordinate reads across ranks.
2025-07-17T07:05:47.1881660Z         For NCCL-based process groups, internal tensor representations of
2025-07-17T07:05:47.1881800Z         objects must be moved to the GPU device before communication takes place.
2025-07-17T07:05:47.1882730Z         In this case, the device used is given by ``torch.cuda.current_device()``
2025-07-17T07:05:47.1883090Z         and it is the user's responsibility to ensure that this is set so that each
2025-07-17T07:05:47.1883220Z         rank has an individual GPU, via ``torch.cuda.set_device()``.
2025-07-17T07:05:47.1883260Z     
2025-07-17T07:05:47.1883420Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1883460Z     
2025-07-17T07:05:47.1883510Z       warnings.warn(msg)
2025-07-17T07:05:47.1883550Z     
2025-07-17T07:05:47.1883730Z --- Parse Warning: 63 / 136 ---
2025-07-17T07:05:47.1884490Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_sharded_optimizer_state_dict in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/checkpoint/optimizer.py line=221.
2025-07-17T07:05:47.1884640Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1884690Z     
2025-07-17T07:05:47.1884810Z     Load a state_dict in conjunction with FSDP sharded optimizer state.
2025-07-17T07:05:47.1884860Z     
2025-07-17T07:05:47.1884950Z     This is the current recommended way to checkpoint FSDP.
2025-07-17T07:05:47.1885010Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1885100Z     >>> import torch.distributed.checkpoint as dist_cp
2025-07-17T07:05:47.1885150Z     >>> # Save
2025-07-17T07:05:47.1885200Z     >>> model: torch.nn.Model
2025-07-17T07:05:47.1885270Z     >>> optim_params = model.parameters()
2025-07-17T07:05:47.1885360Z     >>> optim = torch.optim.SGD(optim_params, lr=0.01)
2025-07-17T07:05:47.1885400Z     >>> # Save
2025-07-17T07:05:47.1885540Z     >>> with FSDP.state_dict_type(model, StateDictType.SHARDED_STATE_DICT):
2025-07-17T07:05:47.1885590Z     >>>     state_dict = {
2025-07-17T07:05:47.1885690Z     >>>         "optimizer": FSDP.optim_state_dict(model, optim),
2025-07-17T07:05:47.1885750Z     >>>         "model": model.state_dict()
2025-07-17T07:05:47.1885790Z     >>>     }
2025-07-17T07:05:47.1885850Z     >>>     dist_cp.save_state_dict(
2025-07-17T07:05:47.1885910Z     >>>         state_dict=optim_state,
2025-07-17T07:05:47.1886020Z     >>>         storage_writer=dist_cp.FileSystemWriter("checkpoint"),
2025-07-17T07:05:47.1886100Z     >>>         planner=dist_cp.DefaultSavePlanner(),
2025-07-17T07:05:47.1886140Z     >>>     )
2025-07-17T07:05:47.1886190Z     >>>
2025-07-17T07:05:47.1886230Z     >>> # Load
2025-07-17T07:05:47.1886370Z     >>> with FSDP.state_dict_type(model_tp, StateDictType.SHARDED_STATE_DICT):
2025-07-17T07:05:47.1886440Z     >>>     model_state_dict = model_tp.state_dict()
2025-07-17T07:05:47.1886490Z     >>>     checkpoint = {
2025-07-17T07:05:47.1886550Z     >>>         "model": model_state_dict
2025-07-17T07:05:47.1886590Z     >>>     }
2025-07-17T07:05:47.1886650Z     >>>     dist_cp.load_state_dict(
2025-07-17T07:05:47.1886710Z     >>>         state_dict=checkpoint,
2025-07-17T07:05:47.1886860Z     >>>         storage_reader=dist_cp.FileSystemReader(checkpoint_file),
2025-07-17T07:05:47.1886950Z     >>>         planner=dist_cp.DefaultLoadPlanner(),
2025-07-17T07:05:47.1886990Z     >>>     )
2025-07-17T07:05:47.1887080Z     >>>     model.load_state_dict(checkpoint["model_state"])
2025-07-17T07:05:47.1887160Z     >>>
2025-07-17T07:05:47.1887260Z     >>>     optim_state = dist_cp.load_sharded_optimizer_state_dict(
2025-07-17T07:05:47.1887320Z     >>>         model_state_dict,
2025-07-17T07:05:47.1887380Z     >>>         optimizer_key="optimizer",
2025-07-17T07:05:47.1887490Z     >>>         storage_reader=dist_cp.FileSystemReader("checkpoint"),
2025-07-17T07:05:47.1887530Z     >>>     )
2025-07-17T07:05:47.1887570Z     >>>
2025-07-17T07:05:47.1887660Z     >>>     flattened_osd = FSDP.optim_state_dict_to_load(
2025-07-17T07:05:47.1887730Z     >>>        model, optim, optim_state["optimizer"]
2025-07-17T07:05:47.1887770Z     >>>     )
2025-07-17T07:05:47.1887810Z     >>>
2025-07-17T07:05:47.1887910Z     >>>     optim.load_state_dict(flattened_osd)
2025-07-17T07:05:47.1887980Z     
2025-07-17T07:05:47.1888130Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1888170Z     
2025-07-17T07:05:47.1888220Z       warnings.warn(msg)
2025-07-17T07:05:47.1888270Z     
2025-07-17T07:05:47.1888370Z --- Parse Warning: 64 / 136 ---
2025-07-17T07:05:47.1889090Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_RemoteModule.__init__ in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/nn/api/remote_module.py line=129.
2025-07-17T07:05:47.1889240Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1889280Z     
2025-07-17T07:05:47.1889420Z     RemoteModule instance can only be created after RPC initialization.
2025-07-17T07:05:47.1889460Z     
2025-07-17T07:05:47.1889580Z     It creates a user-specified module on a specified remote node.
2025-07-17T07:05:47.1889720Z     It behaves like a regular ``nn.Module`` except that the ``forward`` method is
2025-07-17T07:05:47.1889780Z     executed on the remote node.
2025-07-17T07:05:47.1889920Z     It takes care of autograd recording to ensure the backward pass propagates
2025-07-17T07:05:47.1890010Z     gradients back to the corresponding remote module.
2025-07-17T07:05:47.1890220Z     It can be shared across processors using `RPC framework <https://pytorch.org/docs/stable/rpc.html>`__,
2025-07-17T07:05:47.1890340Z     without incurring any overheads of copying the actual module,
2025-07-17T07:05:47.1890460Z     which is equivalent to an :class:`~torch.distributed.rpc.RRef`
2025-07-17T07:05:47.1890520Z     pointing to the remote module.
2025-07-17T07:05:47.1890560Z     
2025-07-17T07:05:47.1890680Z     The arguments of ``forward_async`` and ``forward`` are the same as
2025-07-17T07:05:47.1890830Z     the ``forward`` method of the module returned by the ``module_cls``.
2025-07-17T07:05:47.1890870Z     
2025-07-17T07:05:47.1891060Z     Apart from ``forward_async`` and ``forward``, no other methods are supported from nn.Module for now.
2025-07-17T07:05:47.1891100Z     
2025-07-17T07:05:47.1891250Z     Particularly, to create a hybrid model, typically the local modules should be
2025-07-17T07:05:47.1891470Z     created outside of remote modules, rather than as submodules of any remote module (by calling ``add_module``).
2025-07-17T07:05:47.1891520Z     Hybrid Example:
2025-07-17T07:05:47.1891590Z             >>> class HybridModel(nn.Module):
2025-07-17T07:05:47.1891650Z             >>>     def __init__(self) -> None:
2025-07-17T07:05:47.1891720Z             >>>         nn.Module.__init__(self)
2025-07-17T07:05:47.1891810Z             >>>         self.remote_embedding = RemoteModule(...)
2025-07-17T07:05:47.1891890Z             >>>         self.local_linear = nn.Linear(...)
2025-07-17T07:05:47.1891930Z     
2025-07-17T07:05:47.1892100Z     For example, if ``module_cls`` returns an instance of ``nn.Linear``,
2025-07-17T07:05:47.1892260Z     that has ``forward`` method signature, ``def forward(input: Tensor) -> Tensor:``,
2025-07-17T07:05:47.1892380Z     the generated ``RemoteModule`` will have 2 methods in signature of
2025-07-17T07:05:47.1892480Z     ``def forward(input: Tensor) -> Tensor:`` and
2025-07-17T07:05:47.1892580Z     ``def forward_async(input: Tensor) -> Future[Tensor]:``.
2025-07-17T07:05:47.1892620Z     
2025-07-17T07:05:47.1892660Z     .. note::
2025-07-17T07:05:47.1892750Z         If the remote module is placed on a cuda device,
2025-07-17T07:05:47.1892890Z         any input CPU tensors will be automatically moved to the same cuda device,
2025-07-17T07:05:47.1893130Z         and GPU tensors are returned over the wire according to the device map of the remote worker on TensorPipe RPC backend.
2025-07-17T07:05:47.1893170Z     
2025-07-17T07:05:47.1893210Z     Args:
2025-07-17T07:05:47.1893410Z         remote_device (str): Device on the destination worker where we'd like to place this module.
2025-07-17T07:05:47.1893610Z             The device can be a local device or a remote device specified by one of the following remote
2025-07-17T07:05:47.1893650Z             formats:
2025-07-17T07:05:47.1893700Z     
2025-07-17T07:05:47.1893780Z                 1. "rank:<rank>/<device>" (ex: "rank:0/cuda:0").
2025-07-17T07:05:47.1893880Z                 2. "<worker_name>/<device>" (ex: "trainer0/cuda:0").
2025-07-17T07:05:47.1893920Z     
2025-07-17T07:05:47.1894060Z             In addition, the device field can be optional and the default value is "cpu".
2025-07-17T07:05:47.1894130Z         module_cls (nn.Module): For example,
2025-07-17T07:05:47.1894190Z             >>> class MyModule(nn.Module):
2025-07-17T07:05:47.1894250Z             >>>     def forward(input):
2025-07-17T07:05:47.1894310Z             >>>         return input + 1
2025-07-17T07:05:47.1894350Z             >>>
2025-07-17T07:05:47.1894400Z             >>> module_cls = MyModule
2025-07-17T07:05:47.1894530Z         args (Sequence, optional): args to be passed to ``module_cls``.
2025-07-17T07:05:47.1894650Z         kwargs (Dict, optional): kwargs to be passed to ``module_cls``.
2025-07-17T07:05:47.1894820Z         _module_interface_cls (type, optional): The TorchScript interface type for the module
2025-07-17T07:05:47.1894960Z             to be created. The type object should be decorated by @torch.jit.interface.
2025-07-17T07:05:47.1895100Z             If not provided, the generated RemoteModule is not torchscript-able.
2025-07-17T07:05:47.1895240Z             Warning, this is an experimental API and susceptible to frequent changes.
2025-07-17T07:05:47.1895280Z     
2025-07-17T07:05:47.1895320Z     Returns:
2025-07-17T07:05:47.1895470Z         A remote module instance which wraps the :class:`~nn.Module` created by the
2025-07-17T07:05:47.1895600Z         user-provided ``module_cls``, it has a blocking ``forward`` method and an
2025-07-17T07:05:47.1895770Z         asynchronous ``forward_async`` method that returns a future of the ``forward`` call
2025-07-17T07:05:47.1895860Z         on the user-provided module on the remote side.
2025-07-17T07:05:47.1895900Z     
2025-07-17T07:05:47.1895950Z     Example::
2025-07-17T07:05:47.1896040Z         Run the following code in two different processes:
2025-07-17T07:05:47.1896080Z     
2025-07-17T07:05:47.1896150Z         >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:47.1896200Z         >>> # On worker 0:
2025-07-17T07:05:47.1896250Z         >>> import torch
2025-07-17T07:05:47.1896320Z         >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:47.1896380Z         >>> from torch import nn, Tensor
2025-07-17T07:05:47.1896510Z         >>> from torch.distributed.nn.api.remote_module import RemoteModule
2025-07-17T07:05:47.1896560Z         >>>
2025-07-17T07:05:47.1896640Z         >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-07-17T07:05:47.1896710Z         >>> remote_linear_module = RemoteModule(
2025-07-17T07:05:47.1896840Z         >>>     "worker1/cpu", nn.Linear, args=(20, 30),
2025-07-17T07:05:47.1896880Z         >>> )
2025-07-17T07:05:47.1896940Z         >>> input = torch.randn(128, 20)
2025-07-17T07:05:47.1897040Z         >>> ret_fut = remote_linear_module.forward_async(input)
2025-07-17T07:05:47.1897120Z         >>> ret = ret_fut.wait()
2025-07-17T07:05:47.1897180Z         >>> rpc.shutdown()
2025-07-17T07:05:47.1897220Z     
2025-07-17T07:05:47.1897270Z         >>> # On worker 1:
2025-07-17T07:05:47.1897310Z         >>> import torch
2025-07-17T07:05:47.1897390Z         >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:47.1897430Z         >>>
2025-07-17T07:05:47.1897510Z         >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-07-17T07:05:47.1897560Z         >>> rpc.shutdown()
2025-07-17T07:05:47.1897600Z     
2025-07-17T07:05:47.1897750Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1897790Z     
2025-07-17T07:05:47.1897860Z       warnings.warn(msg)
2025-07-17T07:05:47.1897920Z     
2025-07-17T07:05:47.1898020Z --- Parse Warning: 65 / 136 ---
2025-07-17T07:05:47.1898770Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_RemoteModule.init_from_module_rref in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/nn/api/remote_module.py line=506.
2025-07-17T07:05:47.1898930Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1898970Z     
2025-07-17T07:05:47.1899160Z     Besides the constructor, a RemoteModule instance can also be initialized given a module RRef.
2025-07-17T07:05:47.1899200Z     
2025-07-17T07:05:47.1899390Z     This alternate initialization method can be particularly useful if we want to create multiple
2025-07-17T07:05:47.1899570Z     RemoteModule instances that share the same underlying module and reduce memory consumption.
2025-07-17T07:05:47.1899620Z     
2025-07-17T07:05:47.1899780Z     Moreover, this also provides a workaround for passing script RemoteModule over RPC,
2025-07-17T07:05:47.1899890Z     which is not supported. The recommended way is as follows:
2025-07-17T07:05:47.1899930Z     
2025-07-17T07:05:47.1900000Z         1. the sender creates a RemoteModule;
2025-07-17T07:05:47.1900090Z         2. the sender sends its ``module_rref`` over RPC;
2025-07-17T07:05:47.1900290Z         3. the receiver calls this method to initialize another RemoteModule using the same ``module_rref``.
2025-07-17T07:05:47.1900330Z     
2025-07-17T07:05:47.1900370Z     Example::
2025-07-17T07:05:47.1900460Z         Run the following code in two different processes:
2025-07-17T07:05:47.1900500Z     
2025-07-17T07:05:47.1900570Z         >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:47.1900620Z         >>> # On worker 0:
2025-07-17T07:05:47.1900660Z         >>> import torch
2025-07-17T07:05:47.1900740Z         >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:47.1900800Z         >>> from torch import nn, Tensor
2025-07-17T07:05:47.1900930Z         >>> from torch.distributed.nn.api.remote_module import RemoteModule
2025-07-17T07:05:47.1900980Z         >>>
2025-07-17T07:05:47.1901060Z         >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-07-17T07:05:47.1901120Z         >>> remote_module = RemoteModule(
2025-07-17T07:05:47.1901200Z         >>>     "worker1/cpu", nn.Linear, args=(20, 30),
2025-07-17T07:05:47.1901240Z         >>> )
2025-07-17T07:05:47.1901280Z         >>>
2025-07-17T07:05:47.1901340Z         >>> remote_module1 = rpc.rpc_sync(
2025-07-17T07:05:47.1901400Z         >>>     "worker1/cpu",
2025-07-17T07:05:47.1901470Z         >>>     RemoteModule.init_from_module_rref,
2025-07-17T07:05:47.1901570Z         >>>     ("worker1/cpu", remote_module1.get_module_rref()),
2025-07-17T07:05:47.1901610Z         >>> )
2025-07-17T07:05:47.1901660Z         >>> rpc.shutdown()
2025-07-17T07:05:47.1901700Z     
2025-07-17T07:05:47.1901750Z         >>> # On worker 1:
2025-07-17T07:05:47.1901820Z         >>> import torch
2025-07-17T07:05:47.1901900Z         >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:47.1901940Z         >>>
2025-07-17T07:05:47.1902020Z         >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-07-17T07:05:47.1902090Z         >>> rpc.shutdown()
2025-07-17T07:05:47.1902130Z     
2025-07-17T07:05:47.1902180Z     Args:
2025-07-17T07:05:47.1902350Z         remote_device (str): Device on the destination worker where we'd like to place this module.
2025-07-17T07:05:47.1902530Z             The device can be a local device or a remote device specified by one of the following remote
2025-07-17T07:05:47.1902570Z             formats:
2025-07-17T07:05:47.1902610Z     
2025-07-17T07:05:47.1902700Z                 1. "rank:<rank>/<device>" (ex: "rank:0/cuda:0").
2025-07-17T07:05:47.1902790Z                 2. "<worker_name>/<device>" (ex: "trainer0/cuda:0").
2025-07-17T07:05:47.1902830Z     
2025-07-17T07:05:47.1903010Z             In addition, the device field can be optional and the default value is "cpu".
2025-07-17T07:05:47.1903180Z         module_rref (RRef[nn.Module]): The module reference shared by both the caller and
2025-07-17T07:05:47.1903250Z             the created remote module.
2025-07-17T07:05:47.1903410Z         _module_interface_cls (type, optional): The TorchScript interface type for the module
2025-07-17T07:05:47.1903560Z             to be created. The type object should be decorated by @torch.jit.interface.
2025-07-17T07:05:47.1903690Z             If not provided, the generated RemoteModule is not torchscript-able.
2025-07-17T07:05:47.1903830Z             Warning, this is an experimental API and susceptible to frequent changes.
2025-07-17T07:05:47.1903870Z     
2025-07-17T07:05:47.1903910Z     Returns:
2025-07-17T07:05:47.1904060Z         A remote module instance which wraps the :class:`~nn.Module` created by the
2025-07-17T07:05:47.1904200Z         user-provided ``module_rref``, it has a blocking ``forward`` method and an
2025-07-17T07:05:47.1904370Z         asynchronous ``forward_async`` method that returns a future of the ``forward`` call
2025-07-17T07:05:47.1904450Z         on the user-provided module on the remote side.
2025-07-17T07:05:47.1904490Z     
2025-07-17T07:05:47.1904640Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1904690Z     
2025-07-17T07:05:47.1904740Z       warnings.warn(msg)
2025-07-17T07:05:47.1904780Z     
2025-07-17T07:05:47.1904880Z --- Parse Warning: 66 / 136 ---
2025-07-17T07:05:47.1905580Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RemoteModule in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/nn/api/remote_module.py line=598.
2025-07-17T07:05:47.1905740Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1905780Z     
2025-07-17T07:05:47.1905910Z         A RemoteModule instance can only be created after RPC initialization.
2025-07-17T07:05:47.1905960Z     
2025-07-17T07:05:47.1906070Z         It creates a user-specified module on a specified remote node.
2025-07-17T07:05:47.1906210Z         It behaves like a regular ``nn.Module`` except that the ``forward`` method is
2025-07-17T07:05:47.1906280Z         executed on the remote node.
2025-07-17T07:05:47.1906410Z         It takes care of autograd recording to ensure the backward pass propagates
2025-07-17T07:05:47.1906510Z         gradients back to the corresponding remote module.
2025-07-17T07:05:47.1906550Z     
2025-07-17T07:05:47.1906680Z         It generates two methods ``forward_async`` and ``forward`` based on the
2025-07-17T07:05:47.1906810Z         signature of the ``forward`` method of ``module_cls``. ``forward_async``
2025-07-17T07:05:47.1906960Z         runs asynchronously and returns a Future. The arguments of ``forward_async``
2025-07-17T07:05:47.1907100Z         and ``forward`` are the same as the ``forward`` method of the module
2025-07-17T07:05:47.1907160Z         returned by the ``module_cls``.
2025-07-17T07:05:47.1907200Z     
2025-07-17T07:05:47.1907320Z         For example, if ``module_cls`` returns an instance of ``nn.Linear``,
2025-07-17T07:05:47.1907490Z         that has ``forward`` method signature: ``def forward(input: Tensor) -> Tensor:``,
2025-07-17T07:05:47.1907630Z         the generated ``RemoteModule`` will have 2 methods with the signatures:
2025-07-17T07:05:47.1907660Z     
2025-07-17T07:05:47.1907740Z         | ``def forward(input: Tensor) -> Tensor:``
2025-07-17T07:05:47.1907840Z         | ``def forward_async(input: Tensor) -> Future[Tensor]:``
2025-07-17T07:05:47.1907880Z     
2025-07-17T07:05:47.1907920Z     Args:
2025-07-17T07:05:47.1908100Z         remote_device (str): Device on the destination worker where we'd like to place this module.
2025-07-17T07:05:47.1908330Z             The format should be "<workername>/<device>", where the device field can be parsed as torch.device type.
2025-07-17T07:05:47.1908430Z             E.g., "trainer0/cpu", "trainer0", "ps0/cuda:0".
2025-07-17T07:05:47.1908580Z             In addition, the device field can be optional and the default value is "cpu".
2025-07-17T07:05:47.1908730Z         module_cls (nn.Module): Class for the module to be created remotely. For example,
2025-07-17T07:05:47.1908770Z     
2025-07-17T07:05:47.1908830Z             >>> class MyModule(nn.Module):
2025-07-17T07:05:47.1908890Z             >>>     def forward(input):
2025-07-17T07:05:47.1908950Z             >>>         return input + 1
2025-07-17T07:05:47.1908990Z             >>>
2025-07-17T07:05:47.1909040Z             >>> module_cls = MyModule
2025-07-17T07:05:47.1909090Z     
2025-07-17T07:05:47.1909200Z         args (Sequence, optional): args to be passed to ``module_cls``.
2025-07-17T07:05:47.1909320Z         kwargs (Dict, optional): kwargs to be passed to ``module_cls``.
2025-07-17T07:05:47.1909360Z     
2025-07-17T07:05:47.1909400Z     Returns:
2025-07-17T07:05:47.1909550Z         A remote module instance which wraps the :class:`~nn.Module` created by the
2025-07-17T07:05:47.1909690Z         user-provided ``module_cls``, it has a blocking ``forward`` method and an
2025-07-17T07:05:47.1909850Z         asynchronous ``forward_async`` method that returns a future of the ``forward`` call
2025-07-17T07:05:47.1909940Z         on the user-provided module on the remote side.
2025-07-17T07:05:47.1909980Z     
2025-07-17T07:05:47.1910020Z     Example::
2025-07-17T07:05:47.1910110Z         Run the following code in two different processes:
2025-07-17T07:05:47.1910150Z     
2025-07-17T07:05:47.1910220Z         >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:47.1910270Z         >>> # On worker 0:
2025-07-17T07:05:47.1910320Z         >>> import torch
2025-07-17T07:05:47.1910390Z         >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:47.1910450Z         >>> from torch import nn, Tensor
2025-07-17T07:05:47.1910580Z         >>> from torch.distributed.nn.api.remote_module import RemoteModule
2025-07-17T07:05:47.1910630Z         >>>
2025-07-17T07:05:47.1910710Z         >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-07-17T07:05:47.1910780Z         >>> remote_linear_module = RemoteModule(
2025-07-17T07:05:47.1910860Z         >>>     "worker1/cpu", nn.Linear, args=(20, 30),
2025-07-17T07:05:47.1910900Z         >>> )
2025-07-17T07:05:47.1910960Z         >>> input = torch.randn(128, 20)
2025-07-17T07:05:47.1911050Z         >>> ret_fut = remote_linear_module.forward_async(input)
2025-07-17T07:05:47.1911110Z         >>> ret = ret_fut.wait()
2025-07-17T07:05:47.1911160Z         >>> rpc.shutdown()
2025-07-17T07:05:47.1911200Z     
2025-07-17T07:05:47.1911250Z         >>> # On worker 1:
2025-07-17T07:05:47.1911290Z         >>> import torch
2025-07-17T07:05:47.1911360Z         >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:47.1911400Z         >>>
2025-07-17T07:05:47.1911490Z         >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-07-17T07:05:47.1911570Z         >>> rpc.shutdown()
2025-07-17T07:05:47.1911610Z     
2025-07-17T07:05:47.1911730Z         Furthermore, a more practical example that is combined with
2025-07-17T07:05:47.1912010Z         `DistributedDataParallel <https://pytorch.org/docs/stable/nn.html#torch.nn.parallel.DistributedDataParallel>`__ (DDP)
2025-07-17T07:05:47.1912220Z         can be found in this `tutorial <https://pytorch.org/tutorials/advanced/rpc_ddp_tutorial.html>`__.
2025-07-17T07:05:47.1912260Z     
2025-07-17T07:05:47.1912410Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1912450Z     
2025-07-17T07:05:47.1912500Z       warnings.warn(msg)
2025-07-17T07:05:47.1912540Z     
2025-07-17T07:05:47.1912640Z --- Parse Warning: 67 / 136 ---
2025-07-17T07:05:47.1913400Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=construct_and_record_rdzv_event in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/elastic/events/__init__.py line=94.
2025-07-17T07:05:47.1913580Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1913620Z     
2025-07-17T07:05:47.1913750Z     Initialize rendezvous event object and record its operations.
2025-07-17T07:05:47.1913780Z     
2025-07-17T07:05:47.1913830Z     Args:
2025-07-17T07:05:47.1913900Z         run_id (str): The run id of the rendezvous.
2025-07-17T07:05:47.1913990Z         message (str): The message describing the event.
2025-07-17T07:05:47.1914140Z         node_state (NodeState): The state of the node (INIT, RUNNING, SUCCEEDED, FAILED).
2025-07-17T07:05:47.1914250Z         name (str): Event name. (E.g. Current action being performed).
2025-07-17T07:05:47.1914320Z         hostname (str): Hostname of the node.
2025-07-17T07:05:47.1914410Z         pid (Optional[int]): The process id of the node.
2025-07-17T07:05:47.1914560Z         master_endpoint (str): The master endpoint for the rendezvous store, if known.
2025-07-17T07:05:47.1914720Z         local_id (Optional[int]):  The local_id of the node, if defined in dynamic_rendezvous.py
2025-07-17T07:05:47.1914820Z         rank (Optional[int]): The rank of the node, if known.
2025-07-17T07:05:47.1914860Z     Returns:
2025-07-17T07:05:47.1914900Z         None
2025-07-17T07:05:47.1914940Z     Example:
2025-07-17T07:05:47.1915020Z         >>> # See DynamicRendezvousHandler class
2025-07-17T07:05:47.1915070Z         >>> def _record(
2025-07-17T07:05:47.1915110Z         ...     self,
2025-07-17T07:05:47.1915160Z         ...     message: str,
2025-07-17T07:05:47.1915250Z         ...     node_state: NodeState = NodeState.RUNNING,
2025-07-17T07:05:47.1915310Z         ...     rank: Optional[int] = None,
2025-07-17T07:05:47.1915350Z         ... ) -> None:
2025-07-17T07:05:47.1915420Z         ...     construct_and_record_rdzv_event(
2025-07-17T07:05:47.1915530Z         ...         name=f"{self.__class__.__name__}.{get_method_name()}",
2025-07-17T07:05:47.1915600Z         ...         run_id=self._settings.run_id,
2025-07-17T07:05:47.1915660Z         ...         message=message,
2025-07-17T07:05:47.1915710Z         ...         node_state=node_state,
2025-07-17T07:05:47.1915790Z         ...         hostname=self._this_node.addr,
2025-07-17T07:05:47.1915850Z         ...         pid=self._this_node.pid,
2025-07-17T07:05:47.1915920Z         ...         local_id=self._this_node.local_id,
2025-07-17T07:05:47.1915970Z         ...         rank=rank,
2025-07-17T07:05:47.1916010Z         ...     )
2025-07-17T07:05:47.1916060Z     
2025-07-17T07:05:47.1916200Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1916240Z     
2025-07-17T07:05:47.1916290Z       warnings.warn(msg)
2025-07-17T07:05:47.1916340Z     
2025-07-17T07:05:47.1916430Z --- Parse Warning: 68 / 136 ---
2025-07-17T07:05:47.1917160Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_CustomReducer in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/pipelining/microbatch.py line=29.
2025-07-17T07:05:47.1917340Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1917380Z     
2025-07-17T07:05:47.1917520Z     Custom reducer class that can be used to specify a custom operation that
2025-07-17T07:05:47.1917620Z     reduces losses of multiple microbatches into one value.
2025-07-17T07:05:47.1917660Z     
2025-07-17T07:05:47.1917700Z     Example:
2025-07-17T07:05:47.1917750Z     >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1917810Z     >>> sum_reducer = _CustomReducer(
2025-07-17T07:05:47.1917870Z     >>>     torch.tensor(0.0),
2025-07-17T07:05:47.1917920Z     >>>     lambda a, b: a + b
2025-07-17T07:05:47.1917980Z     >>> )
2025-07-17T07:05:47.1918030Z     
2025-07-17T07:05:47.1918190Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1918220Z     
2025-07-17T07:05:47.1918280Z       warnings.warn(msg)
2025-07-17T07:05:47.1918310Z     
2025-07-17T07:05:47.1918410Z --- Parse Warning: 69 / 136 ---
2025-07-17T07:05:47.1919170Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PeriodicModelAverager in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/algorithms/model_averaging/averagers.py line=38.
2025-07-17T07:05:47.1919330Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1919370Z     
2025-07-17T07:05:47.1919480Z     Averages parameters periodically after the warm-up stage.
2025-07-17T07:05:47.1919520Z     
2025-07-17T07:05:47.1919670Z     This can be used for running `post-local SGD <https://arxiv.org/abs/1808.07217>`_,
2025-07-17T07:05:47.1919790Z     by running :class:`~torch.nn.DistributedDataParallel` (DDP)
2025-07-17T07:05:47.1919930Z     using the subgroups created by :meth:`~torch.distributed.new_subgroups`.
2025-07-17T07:05:47.1919980Z     
2025-07-17T07:05:47.1920020Z     Args:
2025-07-17T07:05:47.1920120Z         period (int): The number of steps per model averaging.
2025-07-17T07:05:47.1920280Z                       Usually the period should be greater than ``1`` to reduce the communication cost.
2025-07-17T07:05:47.1920360Z                       Otherwise, only DDP needs to be used.
2025-07-17T07:05:47.1920480Z         warmup_steps (int): The number of warm-up steps. During this stage,
2025-07-17T07:05:47.1920560Z                             model averaging is skipped.
2025-07-17T07:05:47.1920670Z         process_group: The process group to be used for all-reduce.
2025-07-17T07:05:47.1920760Z                        If ``None``, the default process group, which
2025-07-17T07:05:47.1920890Z                        is created by :func:`torch.distributed.init_process_group`,
2025-07-17T07:05:47.1920960Z                        will be used. (default: ``None``)
2025-07-17T07:05:47.1921000Z     
2025-07-17T07:05:47.1921050Z     Example::
2025-07-17T07:05:47.1921090Z     
2025-07-17T07:05:47.1921160Z         >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:47.1921210Z         >>> import torch
2025-07-17T07:05:47.1921280Z         >>> import torch.distributed as dist
2025-07-17T07:05:47.1921470Z         >>> import torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook as post_localSGD
2025-07-17T07:05:47.1921630Z         >>> import torch.distributed.algorithms.model_averaging.averagers as averagers
2025-07-17T07:05:47.1921690Z         >>> import torch.nn as nn
2025-07-17T07:05:47.1921730Z         >>>
2025-07-17T07:05:47.1921840Z         >>> dist.init_process_group("nccl", rank=rank, world_size=16)
2025-07-17T07:05:47.1921900Z         >>> torch.cuda.set_device(rank)
2025-07-17T07:05:47.1922000Z         >>> module = nn.Linear(1, 1, bias=False).cuda()
2025-07-17T07:05:47.1922090Z         >>> model = nn.parallel.DistributedDataParallel(
2025-07-17T07:05:47.1922180Z         >>>    module, device_ids=[rank], output_device=rank
2025-07-17T07:05:47.1922240Z         >>> )
2025-07-17T07:05:47.1922330Z         >>> # Register a post-localSGD communication hook.
2025-07-17T07:05:47.1922500Z         >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100)
2025-07-17T07:05:47.1922600Z         >>> model.register_comm_hook(state, post_localSGD_hook)
2025-07-17T07:05:47.1922640Z         >>>
2025-07-17T07:05:47.1922800Z         >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step.
2025-07-17T07:05:47.1922900Z         >>> # After 100 steps, run model averaging every 4 steps.
2025-07-17T07:05:47.1923120Z         >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``.
2025-07-17T07:05:47.1923300Z         >>> averager = averagers.PeriodicModelAverager(period=4, warmup_steps=100)
2025-07-17T07:05:47.1923360Z         >>> for step in range(0, 200):
2025-07-17T07:05:47.1923410Z         >>>    optimizer.zero_grad()
2025-07-17T07:05:47.1923480Z         >>>    loss = loss_fn(output, labels)
2025-07-17T07:05:47.1923540Z         >>>    loss.backward()
2025-07-17T07:05:47.1923590Z         >>>    optimizer.step()
2025-07-17T07:05:47.1923710Z         >>>    # Will average model parameters globally every 4 steps. Thus,
2025-07-17T07:05:47.1923830Z         >>>    # inter-node communication only occurs every 4 iterations after
2025-07-17T07:05:47.1923910Z         >>>    # the initial ``warmup_steps`` period.
2025-07-17T07:05:47.1924000Z         >>>    averager.average_parameters(model.parameters())
2025-07-17T07:05:47.1924040Z     
2025-07-17T07:05:47.1924190Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1924230Z     
2025-07-17T07:05:47.1924290Z       warnings.warn(msg)
2025-07-17T07:05:47.1924330Z     
2025-07-17T07:05:47.1924430Z --- Parse Warning: 70 / 136 ---
2025-07-17T07:05:47.1925250Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=HierarchicalModelAverager in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/algorithms/model_averaging/hierarchical_model_averager.py line=19.
2025-07-17T07:05:47.1925410Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1925440Z     
2025-07-17T07:05:47.1925640Z     Runs hierarchical model averaging (`hierarchical SGD <https://arxiv.org/pdf/2010.12998.pdf>`_).
2025-07-17T07:05:47.1925680Z     
2025-07-17T07:05:47.1925860Z     Process groups of different sizes are organized in a hierarchy, and they average parameters
2025-07-17T07:05:47.1925990Z     by using different periods concurrently after the warm-up stage.
2025-07-17T07:05:47.1926240Z     This is an extension of :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`
2025-07-17T07:05:47.1926440Z     that supports `post-local SGD <https://arxiv.org/abs/1808.07217>`_, which essentially only supports
2025-07-17T07:05:47.1926620Z     a two-level hierarchy: the intra-machine level and the global level, where the intra-machine
2025-07-17T07:05:47.1926830Z     level is usually embedded in :meth:`~torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook`.
2025-07-17T07:05:47.1927010Z     Similarly, the process groups within this class do not have such an intra-machine process
2025-07-17T07:05:47.1927170Z     subgroup, which should be embedded by the post-local SGD communication hook instead.
2025-07-17T07:05:47.1927210Z     
2025-07-17T07:05:47.1927250Z     Args:
2025-07-17T07:05:47.1927410Z         period_group_size_dict: An ordered dict mapping keys of model averaging period to
2025-07-17T07:05:47.1927580Z                                 process group size, used for initializing process groups of
2025-07-17T07:05:47.1927720Z                                 different sizes in a hierarchy to average parameters concurrently.
2025-07-17T07:05:47.1931840Z                                 Particularly, at each iteration, there will be at most a single
2025-07-17T07:05:47.1932010Z                                 process group that runs averaging -- the period of such group should
2025-07-17T07:05:47.1932140Z                                 have the largest period which the current step can be divided by.
2025-07-17T07:05:47.1932240Z                                 For example, if the dict has three keys: 2, 4, and 8,
2025-07-17T07:05:47.1932370Z                                 then this means totally three process groups will be created to
2025-07-17T07:05:47.1932500Z                                 average parameters every 2, 4, and 8 iterations, respectively.
2025-07-17T07:05:47.1932740Z                                 At the 4th iteration, only the second process group will run
2025-07-17T07:05:47.1932880Z                                 averaging, because the first process group should be a
2025-07-17T07:05:47.1933010Z                                 subset of the second process group, and no need to execute the first
2025-07-17T07:05:47.1933090Z                                 process group redundantly.
2025-07-17T07:05:47.1933210Z                                 On the other hand, the third process group can only be triggered
2025-07-17T07:05:47.1933350Z                                 every 8 iterations, so it will not be triggered at the 4th iteration.
2025-07-17T07:05:47.1933540Z         warmup_steps (int): The number of warm-up steps. During this stage, model averaging is skipped.
2025-07-17T07:05:47.1933790Z         process_group (ProcessGroup, optional): The overall process group containing all the processes that runs model averaging.
2025-07-17T07:05:47.1933910Z                                                 If ``None``, the default process group, which is created
2025-07-17T07:05:47.1934040Z                                                 by :func:`torch.distributed.init_process_group`, will be used.
2025-07-17T07:05:47.1934120Z                                                 (default: ``None``)
2025-07-17T07:05:47.1934160Z     
2025-07-17T07:05:47.1934200Z     Example::
2025-07-17T07:05:47.1934270Z         >>> # xdoctest: +SKIP('undefined rank')
2025-07-17T07:05:47.1934350Z         >>> from collections import OrderedDict
2025-07-17T07:05:47.1934390Z         >>> import torch
2025-07-17T07:05:47.1934460Z         >>> import torch.distributed as dist
2025-07-17T07:05:47.1934630Z         >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import (
2025-07-17T07:05:47.1934690Z         >>>     PostLocalSGDState,
2025-07-17T07:05:47.1934740Z         >>>     post_localSGD_hook,
2025-07-17T07:05:47.1934790Z         >>> )
2025-07-17T07:05:47.1935010Z         >>> import torch.distributed.algorithms.model_averaging.hierarchical_model_averager as hierarchicalSGD
2025-07-17T07:05:47.1935070Z         >>> import torch.nn as nn
2025-07-17T07:05:47.1935110Z         >>>
2025-07-17T07:05:47.1935220Z         >>> dist.init_process_group("nccl", rank=rank, world_size=16)
2025-07-17T07:05:47.1935280Z         >>> torch.cuda.set_device(rank)
2025-07-17T07:05:47.1935360Z         >>> module = nn.Linear(1, 1, bias=False).to(rank)
2025-07-17T07:05:47.1935450Z         >>> model = nn.parallel.DistributedDataParallel(
2025-07-17T07:05:47.1935540Z         >>>    module, device_ids=[rank], output_device=rank
2025-07-17T07:05:47.1935580Z         >>> )
2025-07-17T07:05:47.1935670Z         >>> # Register a post-localSGD communication hook.
2025-07-17T07:05:47.1935830Z         >>> # Assume that each machine has 4 GPUs, then each intra-machine subgroup has a size of 4.
2025-07-17T07:05:47.1935900Z         >>> subgroup, _ = dist.new_subgroups()
2025-07-17T07:05:47.1936090Z         >>> state = PostLocalSGDState(process_group=None, subgroup=subgroup, start_localSGD_iter=100)
2025-07-17T07:05:47.1936220Z         >>> model.register_comm_hook(state, post_localSGD_hook)
2025-07-17T07:05:47.1936260Z         >>>
2025-07-17T07:05:47.1936430Z         >>> # Average parameters among each group of 8 processes every 4 iterations, and among all
2025-07-17T07:05:47.1936520Z         >>> # the 16 processes every 16 iterations.
2025-07-17T07:05:47.1936640Z         >>> averager = hierarchicalSGD.HierarchicalModelAverager(
2025-07-17T07:05:47.1936780Z         >>>     period_group_size_dict=OrderedDict([(4, 8), (16, 16)]), warmup_steps=100)
2025-07-17T07:05:47.1936970Z         >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``.
2025-07-17T07:05:47.1937130Z         >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step.
2025-07-17T07:05:47.1937230Z         >>> # After 100 steps, run model averaging at two levels.
2025-07-17T07:05:47.1937310Z         >>> for step in range(0, 200):
2025-07-17T07:05:47.1937390Z         >>>    optimizer.zero_grad()
2025-07-17T07:05:47.1937450Z         >>>    loss = loss_fn(output, labels)
2025-07-17T07:05:47.1937510Z         >>>    loss.backward()
2025-07-17T07:05:47.1937560Z         >>>    optimizer.step()
2025-07-17T07:05:47.1937660Z         >>>    # Average parameters after ``optimizer.step()``.
2025-07-17T07:05:47.1937830Z         >>>    # Thus, the inter-node communication only occurs periodically after ``warmup_steps``.
2025-07-17T07:05:47.1937930Z         >>>    averager.average_parameters(model.parameters())
2025-07-17T07:05:47.1937970Z     
2025-07-17T07:05:47.1938010Z     .. warning ::
2025-07-17T07:05:47.1938170Z         The last group size in the dict must be the size of the provided ``process_group``,
2025-07-17T07:05:47.1938310Z         which indicates model averaging at the highest level of the hierarchy.
2025-07-17T07:05:47.1938490Z         If ``process_group`` is not provided, then the last group size should be equal to the world size.
2025-07-17T07:05:47.1938540Z     
2025-07-17T07:05:47.1938580Z     .. warning ::
2025-07-17T07:05:47.1938720Z         `HierarchicalModelAverager` is experimental and subject to change.
2025-07-17T07:05:47.1938760Z     
2025-07-17T07:05:47.1938910Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1938950Z     
2025-07-17T07:05:47.1939000Z       warnings.warn(msg)
2025-07-17T07:05:47.1939040Z     
2025-07-17T07:05:47.1939160Z --- Parse Warning: 71 / 136 ---
2025-07-17T07:05:47.1939940Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=post_localSGD_hook in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/post_localSGD_hook.py line=72.
2025-07-17T07:05:47.1940090Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1940140Z     
2025-07-17T07:05:47.1940190Z     Run post-localSGD algorithm.
2025-07-17T07:05:47.1940230Z     
2025-07-17T07:05:47.1940370Z     This DDP communication hook is used for running post-localSGD algorithm,
2025-07-17T07:05:47.1940470Z     by combining with a model averaging component (e.g.,
2025-07-17T07:05:47.1940670Z     :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`)
2025-07-17T07:05:47.1940730Z     that runs after the optimizer step.
2025-07-17T07:05:47.1940770Z     
2025-07-17T07:05:47.1940810Z     Args:
2025-07-17T07:05:47.1940950Z         state (PostLocalSGDState): State information to run post-localSGD.
2025-07-17T07:05:47.1941110Z             Users mainly need to tune ``start_localSGD_iter`` to determine when to start local SGD.
2025-07-17T07:05:47.1941360Z         bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors.
2025-07-17T07:05:47.1941530Z             Note that since DDP comm hook only supports single process single device mode,
2025-07-17T07:05:47.1941630Z             only exactly one tensor is stored in this bucket.
2025-07-17T07:05:47.1941670Z     
2025-07-17T07:05:47.1941710Z     Returns:
2025-07-17T07:05:47.1941890Z         Future handler of the communication, which updates the gradients in place.
2025-07-17T07:05:47.1941930Z     
2025-07-17T07:05:47.1941970Z     Example::
2025-07-17T07:05:47.1942030Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1942180Z         >>> state = PostLocalSGDState(process_group=process_group, subgroup=subgroup,
2025-07-17T07:05:47.1942250Z                                   start_localSGD_iter=10)
2025-07-17T07:05:47.1942360Z         >>> ddp_model.register_comm_hook(state, post_localSGD_hook)
2025-07-17T07:05:47.1942550Z         >>> # Also need to establish a model averaging module and run model averaging after ``optimizer.step()``.
2025-07-17T07:05:47.1942780Z         >>> # Please refer to the examples in ``torch.distributed.algorithms.model_averaging.averagers`` module.
2025-07-17T07:05:47.1942840Z     
2025-07-17T07:05:47.1942990Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1943030Z     
2025-07-17T07:05:47.1943080Z       warnings.warn(msg)
2025-07-17T07:05:47.1943120Z     
2025-07-17T07:05:47.1943230Z --- Parse Warning: 72 / 136 ---
2025-07-17T07:05:47.1943970Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=powerSGD_hook in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py line=342.
2025-07-17T07:05:47.1944130Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1944170Z     
2025-07-17T07:05:47.1944230Z     Implement PowerSGD algorithm.
2025-07-17T07:05:47.1944270Z     
2025-07-17T07:05:47.1944410Z     This DDP communication hook implements PowerSGD gradient compression
2025-07-17T07:05:47.1944550Z     algorithm described in the `paper <https://arxiv.org/abs/1905.13727>`_.
2025-07-17T07:05:47.1944690Z     Once gradient tensors are aggregated across all workers, this hook applies
2025-07-17T07:05:47.1944750Z     compression as follows:
2025-07-17T07:05:47.1944790Z     
2025-07-17T07:05:47.1945050Z     1. Views the input flattened 1D gradient tensor as a list of per-parameter tensors, and divides all the tensors into two groups:
2025-07-17T07:05:47.1945090Z     
2025-07-17T07:05:47.1945340Z         1.1 The tensors that should be compressed before allreduce, because the compression can give enough saving in bandwidth.
2025-07-17T07:05:47.1945380Z     
2025-07-17T07:05:47.1945620Z         1.2 Rest of the tensors will be directly allreduced without compression, including all the vector tensors (for biases).
2025-07-17T07:05:47.1945650Z     
2025-07-17T07:05:47.1945720Z     2. Handles uncompressed tensors:
2025-07-17T07:05:47.1945760Z     
2025-07-17T07:05:47.1946060Z         2.1. Allocate contiguous memory for those uncompressed tensors, and allreduces all the uncompressed tensors as a batch, without compression;
2025-07-17T07:05:47.1946100Z     
2025-07-17T07:05:47.1946300Z         2.2. Copies the individual uncompressed tensors from the contiguous memory back to the input tensor.
2025-07-17T07:05:47.1946340Z     
2025-07-17T07:05:47.1946480Z     3. Handles the tensors that should be compressed by PowerSGD compression:
2025-07-17T07:05:47.1946520Z     
2025-07-17T07:05:47.1946660Z         3.1. For each tensor M, creates two low-rank tensors P and Q for decomposing M,
2025-07-17T07:05:47.1946850Z         such that M = PQ^T, where Q is initialized from a standard normal distribution and orthogonalized;
2025-07-17T07:05:47.1946880Z     
2025-07-17T07:05:47.1946970Z         3.2. Computes each P in Ps, which is equal to MQ;
2025-07-17T07:05:47.1947010Z     
2025-07-17T07:05:47.1947080Z         3.3. Allreduces Ps as a batch;
2025-07-17T07:05:47.1947120Z     
2025-07-17T07:05:47.1947200Z         3.4. Orthogonalizes each P in Ps;
2025-07-17T07:05:47.1947240Z     
2025-07-17T07:05:47.1947360Z         3.5. Computes each Q in Qs, which is approximately equal to M^TP;
2025-07-17T07:05:47.1947420Z     
2025-07-17T07:05:47.1947480Z         3.6. Allreduces Qs as a batch;
2025-07-17T07:05:47.1947520Z     
2025-07-17T07:05:47.1947700Z         3.7. Computes each M among all the compressed tensors, which is approximately equal to PQ^T.
2025-07-17T07:05:47.1947740Z     
2025-07-17T07:05:47.1947980Z     Note that this communication hook enforces vanilla allreduce for the first ``state.start_powerSGD_iter`` iterations.
2025-07-17T07:05:47.1948150Z     This not only gives the user more control over the tradeoff between speedup and accuracy,
2025-07-17T07:05:47.1948400Z     but also helps abstract away some complexity of the internal optimization of DDP for future communication hook developers.
2025-07-17T07:05:47.1948470Z     
2025-07-17T07:05:47.1948530Z     Args:
2025-07-17T07:05:47.1948790Z         state (PowerSGDState): State information to configure the compression rate and support error feedback, warm start, etc.
2025-07-17T07:05:47.1949000Z             To tune the compression configs, mainly need to tune ``matrix_approximation_rank``, ``start_powerSGD_iter``
2025-07-17T07:05:47.1949070Z             and ``min_compression_rate``.
2025-07-17T07:05:47.1949310Z         bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors.
2025-07-17T07:05:47.1949460Z             Note that since DDP comm hook only supports single process single device mode,
2025-07-17T07:05:47.1949550Z             only exactly one tensor is stored in this bucket.
2025-07-17T07:05:47.1949590Z     
2025-07-17T07:05:47.1949640Z     Returns:
2025-07-17T07:05:47.1949780Z         Future handler of the communication, which updates the gradients in place.
2025-07-17T07:05:47.1949820Z     
2025-07-17T07:05:47.1949870Z     Example::
2025-07-17T07:05:47.1949920Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1950090Z         >>> state = PowerSGDState(process_group=process_group, matrix_approximation_rank=1,
2025-07-17T07:05:47.1950190Z                                   start_powerSGD_iter=10, min_compression_rate=0.5)
2025-07-17T07:05:47.1950290Z         >>> ddp_model.register_comm_hook(state, powerSGD_hook)
2025-07-17T07:05:47.1950330Z     
2025-07-17T07:05:47.1950480Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1950520Z     
2025-07-17T07:05:47.1950570Z       warnings.warn(msg)
2025-07-17T07:05:47.1950610Z     
2025-07-17T07:05:47.1950710Z --- Parse Warning: 73 / 136 ---
2025-07-17T07:05:47.1951470Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PostLocalSGDOptimizer in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/optim/post_localSGD_optimizer.py line=9.
2025-07-17T07:05:47.1951630Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1951670Z     
2025-07-17T07:05:47.1951900Z     Wraps an arbitrary :class:`torch.optim.Optimizer` and runs `post-local SGD <https://arxiv.org/abs/1808.07217>`_,
2025-07-17T07:05:47.1951990Z     This optimizer runs local optimizer at every step.
2025-07-17T07:05:47.1952190Z     After the warm-up stage, it averages parameters periodically after the local optimizer is applied.
2025-07-17T07:05:47.1952230Z     
2025-07-17T07:05:47.1952270Z     Args:
2025-07-17T07:05:47.1952330Z         optim: The local optimizer.
2025-07-17T07:05:47.1952460Z         averager: A model averager instance to run post-localSGD algorithm.
2025-07-17T07:05:47.1952500Z     
2025-07-17T07:05:47.1952550Z     Example::
2025-07-17T07:05:47.1952580Z     
2025-07-17T07:05:47.1952660Z         >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:47.1952710Z         >>> import torch
2025-07-17T07:05:47.1952800Z         >>> import torch.distributed as dist
2025-07-17T07:05:47.1952960Z         >>> import torch.distributed.algorithms.model_averaging.averagers as averagers
2025-07-17T07:05:47.1953050Z         >>> import torch.nn as nn
2025-07-17T07:05:47.1953160Z         >>> from torch.distributed.optim import PostLocalSGDOptimizer
2025-07-17T07:05:47.1953320Z         >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import (
2025-07-17T07:05:47.1953380Z         >>>   PostLocalSGDState,
2025-07-17T07:05:47.1953430Z         >>>   post_localSGD_hook,
2025-07-17T07:05:47.1953470Z         >>> )
2025-07-17T07:05:47.1953520Z         >>>
2025-07-17T07:05:47.1953610Z         >>> model = nn.parallel.DistributedDataParallel(
2025-07-17T07:05:47.1953700Z         >>>    module, device_ids=[rank], output_device=rank
2025-07-17T07:05:47.1953740Z         >>> )
2025-07-17T07:05:47.1953780Z         >>>
2025-07-17T07:05:47.1953880Z         >>> # Register a post-localSGD communication hook.
2025-07-17T07:05:47.1954080Z         >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100)
2025-07-17T07:05:47.1954180Z         >>> model.register_comm_hook(state, post_localSGD_hook)
2025-07-17T07:05:47.1954220Z         >>>
2025-07-17T07:05:47.1954350Z         >>> # Create a post-localSGD optimizer that wraps a local optimizer.
2025-07-17T07:05:47.1954500Z         >>> # Note that ``warmup_steps`` used in ``PostLocalSGDOptimizer`` must be the same as
2025-07-17T07:05:47.1954600Z         >>> # ``start_localSGD_iter`` used in ``PostLocalSGDState``.
2025-07-17T07:05:47.1954730Z         >>> local_optim = torch.optim.SGD(params=model.parameters(), lr=0.01)
2025-07-17T07:05:47.1954790Z         >>> opt = PostLocalSGDOptimizer(
2025-07-17T07:05:47.1954850Z         >>>     optim=local_optim,
2025-07-17T07:05:47.1955000Z         >>>     averager=averagers.PeriodicModelAverager(period=4, warmup_steps=100)
2025-07-17T07:05:47.1955040Z         >>> )
2025-07-17T07:05:47.1955080Z         >>>
2025-07-17T07:05:47.1955220Z         >>> # In the first 100 steps, DDP runs global gradient averaging at every step.
2025-07-17T07:05:47.1955400Z         >>> # After 100 steps, DDP runs gradient averaging within each subgroup (intra-node by default),
2025-07-17T07:05:47.1955620Z         >>> # and post-localSGD optimizer runs global model averaging every 4 steps after applying the local optimizer.
2025-07-17T07:05:47.1955680Z         >>> for step in range(0, 200):
2025-07-17T07:05:47.1955740Z         >>>    opt.zero_grad()
2025-07-17T07:05:47.1955810Z         >>>    loss = loss_fn(output, labels)
2025-07-17T07:05:47.1955860Z         >>>    loss.backward()
2025-07-17T07:05:47.1955910Z         >>>    opt.step()
2025-07-17T07:05:47.1955950Z     
2025-07-17T07:05:47.1956100Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1956140Z     
2025-07-17T07:05:47.1956190Z       warnings.warn(msg)
2025-07-17T07:05:47.1956230Z     
2025-07-17T07:05:47.1956330Z --- Parse Warning: 74 / 136 ---
2025-07-17T07:05:47.1957040Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedOptimizer in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/optim/optimizer.py line=129.
2025-07-17T07:05:47.1957190Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1957230Z     
2025-07-17T07:05:47.1957370Z     DistributedOptimizer takes remote references to parameters scattered
2025-07-17T07:05:47.1957520Z     across workers and applies the given optimizer locally for each parameter.
2025-07-17T07:05:47.1957560Z     
2025-07-17T07:05:47.1957700Z     This class uses :meth:`~torch.distributed.autograd.get_gradients` in order
2025-07-17T07:05:47.1957790Z     to retrieve the gradients for specific parameters.
2025-07-17T07:05:47.1957830Z     
2025-07-17T07:05:47.1957930Z     Concurrent calls to
2025-07-17T07:05:47.1958060Z     :meth:`~torch.distributed.optim.DistributedOptimizer.step`,
2025-07-17T07:05:47.1958150Z     either from the same or different clients, will
2025-07-17T07:05:47.1958300Z     be serialized on each worker -- as each worker's optimizer can only work
2025-07-17T07:05:47.1958420Z     on one set of gradients at a time. However, there is no guarantee that
2025-07-17T07:05:47.1958570Z     the full forward-backward-optimizer sequence will execute for one client
2025-07-17T07:05:47.1958700Z     at a time. This means that the gradients being applied may not correspond
2025-07-17T07:05:47.1958830Z     to the latest forward pass executed on a given worker. Also, there is no
2025-07-17T07:05:47.1958890Z     guaranteed ordering across workers.
2025-07-17T07:05:47.1958930Z     
2025-07-17T07:05:47.1959090Z     `DistributedOptimizer` creates the local optimizer with TorchScript enabled
2025-07-17T07:05:47.1959240Z     by default, so that optimizer updates are not blocked by the Python Global
2025-07-17T07:05:47.1959410Z     Interpreter Lock (GIL) in the case of multithreaded training (e.g. Distributed
2025-07-17T07:05:47.1959550Z     Model Parallel). This feature is currently enabled for most optimizers. You
2025-07-17T07:05:47.1959710Z     can also follow `the recipe`__ in PyTorch tutorials to enable TorchScript support
2025-07-17T07:05:47.1959770Z     for your own custom optimizers.
2025-07-17T07:05:47.1959810Z     
2025-07-17T07:05:47.1959850Z     Args:
2025-07-17T07:05:47.1959970Z         optimizer_class (optim.Optimizer): the class of optimizer to
2025-07-17T07:05:47.1960030Z             instantiate on each worker.
2025-07-17T07:05:47.1960160Z         params_rref (list[RRef]): list of RRefs to local or remote parameters
2025-07-17T07:05:47.1960210Z             to optimize.
2025-07-17T07:05:47.1960340Z         args: arguments to pass to the optimizer constructor on each worker.
2025-07-17T07:05:47.1960470Z         kwargs: arguments to pass to the optimizer constructor on each worker.
2025-07-17T07:05:47.1960510Z     
2025-07-17T07:05:47.1960560Z     Example::
2025-07-17T07:05:47.1960620Z         >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:47.1960720Z         >>> import torch.distributed.autograd as dist_autograd
2025-07-17T07:05:47.1960800Z         >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:47.1960850Z         >>> from torch import optim
2025-07-17T07:05:47.1960970Z         >>> from torch.distributed.optim import DistributedOptimizer
2025-07-17T07:05:47.1961010Z         >>>
2025-07-17T07:05:47.1961090Z         >>> with dist_autograd.context() as context_id:
2025-07-17T07:05:47.1961140Z         >>>   # Forward pass.
2025-07-17T07:05:47.1961270Z         >>>   rref1 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 3))
2025-07-17T07:05:47.1961380Z         >>>   rref2 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 1))
2025-07-17T07:05:47.1961460Z         >>>   loss = rref1.to_here() + rref2.to_here()
2025-07-17T07:05:47.1961500Z         >>>
2025-07-17T07:05:47.1961560Z         >>>   # Backward pass.
2025-07-17T07:05:47.1961650Z         >>>   dist_autograd.backward(context_id, [loss.sum()])
2025-07-17T07:05:47.1961690Z         >>>
2025-07-17T07:05:47.1961740Z         >>>   # Optimizer.
2025-07-17T07:05:47.1961820Z         >>>   dist_optim = DistributedOptimizer(
2025-07-17T07:05:47.1961860Z         >>>      optim.SGD,
2025-07-17T07:05:47.1961920Z         >>>      [rref1, rref2],
2025-07-17T07:05:47.1961960Z         >>>      lr=0.05,
2025-07-17T07:05:47.1962000Z         >>>   )
2025-07-17T07:05:47.1962070Z         >>>   dist_optim.step(context_id)
2025-07-17T07:05:47.1962110Z     
2025-07-17T07:05:47.1962200Z     __ https://github.com/pytorch/tutorials/pull/1465
2025-07-17T07:05:47.1962240Z     
2025-07-17T07:05:47.1962390Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1962430Z     
2025-07-17T07:05:47.1962480Z       warnings.warn(msg)
2025-07-17T07:05:47.1962520Z     
2025-07-17T07:05:47.1962670Z --- Parse Warning: 75 / 136 ---
2025-07-17T07:05:47.1963430Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ZeroRedundancyOptimizer in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/optim/zero_redundancy_optimizer.py line=284.
2025-07-17T07:05:47.1963620Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1963660Z     
2025-07-17T07:05:47.1963900Z     Wrap an arbitrary :class:`optim.Optimizer <torch.optim.Optimizer>` and shards its states across ranks in the group.
2025-07-17T07:05:47.1963940Z     
2025-07-17T07:05:47.1964080Z     The sharing is done as described by `ZeRO <https://arxiv.org/abs/1910.02054>`_.
2025-07-17T07:05:47.1964120Z     
2025-07-17T07:05:47.1964230Z     The local optimizer instance in each rank is only
2025-07-17T07:05:47.1964390Z     responsible for updating approximately ``1 / world_size`` parameters and
2025-07-17T07:05:47.1964510Z     hence only needs to keep ``1 / world_size`` optimizer states. After
2025-07-17T07:05:47.1964660Z     parameters are updated locally, each rank will broadcast its parameters to
2025-07-17T07:05:47.1964770Z     all other peers to keep all model replicas in the same state.
2025-07-17T07:05:47.1964890Z     ``ZeroRedundancyOptimizer`` can be used in conjunction with
2025-07-17T07:05:47.1965040Z     :class:`torch.nn.parallel.DistributedDataParallel` to reduce per-rank peak
2025-07-17T07:05:47.1965100Z     memory consumption.
2025-07-17T07:05:47.1965130Z     
2025-07-17T07:05:47.1965290Z     ``ZeroRedundancyOptimizer`` uses a sorted-greedy algorithm to pack a number
2025-07-17T07:05:47.1965420Z     of parameters at each rank. Each parameter belongs to a single rank and is
2025-07-17T07:05:47.1965570Z     not divided among ranks. The partition is arbitrary and might not match the
2025-07-17T07:05:47.1965650Z     the parameter registration or usage order.
2025-07-17T07:05:47.1965690Z     
2025-07-17T07:05:47.1965730Z     Arguments:
2025-07-17T07:05:47.1965850Z         params (``Iterable``): an ``Iterable`` of :class:`torch.Tensor` s
2025-07-17T07:05:47.1965960Z             or :class:`dict` s giving all parameters, which will be sharded
2025-07-17T07:05:47.1966010Z             across ranks.
2025-07-17T07:05:47.1966050Z     
2025-07-17T07:05:47.1966100Z     Keyword Args:
2025-07-17T07:05:47.1966230Z         optimizer_class (:class:`torch.nn.Optimizer`): the class of the local
2025-07-17T07:05:47.1966280Z             optimizer.
2025-07-17T07:05:47.1966410Z         process_group (``ProcessGroup``, optional): ``torch.distributed``
2025-07-17T07:05:47.1966520Z             ``ProcessGroup`` (default: ``dist.group.WORLD`` initialized by
2025-07-17T07:05:47.1966610Z             :meth:`torch.distributed.init_process_group`).
2025-07-17T07:05:47.1966750Z         parameters_as_bucket_view (bool, optional): if ``True``, parameters are
2025-07-17T07:05:47.1966880Z             packed into buckets to speed up communication, and ``param.data``
2025-07-17T07:05:47.1967000Z             fields point to bucket views at different offsets; if ``False``,
2025-07-17T07:05:47.1967130Z             each individual parameter is communicated separately, and each
2025-07-17T07:05:47.1967220Z             ``params.data`` stays intact (default: ``False``).
2025-07-17T07:05:47.1967340Z         overlap_with_ddp (bool, optional): if ``True``, :meth:`step` is
2025-07-17T07:05:47.1967460Z             overlapped with :class:`DistributedDataParallel` 's gradient
2025-07-17T07:05:47.1967580Z             synchronization; this requires (1) either a functional optimizer
2025-07-17T07:05:47.1967690Z             for the ``optimizer_class`` argument or one with a functional
2025-07-17T07:05:47.1967800Z             equivalent and (2) registering a DDP communication hook
2025-07-17T07:05:47.1967920Z             constructed from one of the functions in ``ddp_zero_hook.py``;
2025-07-17T07:05:47.1968040Z             parameters are packed into buckets matching those in
2025-07-17T07:05:47.1968140Z             :class:`DistributedDataParallel`, meaning that the
2025-07-17T07:05:47.1968220Z             ``parameters_as_bucket_view`` argument is ignored.
2025-07-17T07:05:47.1968360Z             If ``False``, :meth:`step` runs disjointly after the backward pass
2025-07-17T07:05:47.1968410Z             (per normal).
2025-07-17T07:05:47.1968470Z             (default: ``False``)
2025-07-17T07:05:47.1968590Z         **defaults: any trailing arguments, which are forwarded to the local
2025-07-17T07:05:47.1968640Z             optimizer.
2025-07-17T07:05:47.1968680Z     
2025-07-17T07:05:47.1968720Z     Example::
2025-07-17T07:05:47.1968760Z     
2025-07-17T07:05:47.1968820Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.1968870Z         >>> import torch.nn as nn
2025-07-17T07:05:47.1969020Z         >>> from torch.distributed.optim import ZeroRedundancyOptimizer
2025-07-17T07:05:47.1969180Z         >>> from torch.nn.parallel import DistributedDataParallel as DDP
2025-07-17T07:05:47.1969320Z         >>> model = nn.Sequential(*[nn.Linear(2000, 2000).to(rank) for _ in range(20)])
2025-07-17T07:05:47.1969390Z         >>> ddp = DDP(model, device_ids=[rank])
2025-07-17T07:05:47.1969460Z         >>> opt = ZeroRedundancyOptimizer(
2025-07-17T07:05:47.1969510Z         >>>     ddp.parameters(),
2025-07-17T07:05:47.1969590Z         >>>     optimizer_class=torch.optim.Adam,
2025-07-17T07:05:47.1969630Z         >>>     lr=0.01
2025-07-17T07:05:47.1969670Z         >>> )
2025-07-17T07:05:47.1969730Z         >>> ddp(inputs).sum().backward()
2025-07-17T07:05:47.1969780Z         >>> opt.step()
2025-07-17T07:05:47.1969820Z     
2025-07-17T07:05:47.1969860Z     .. warning::
2025-07-17T07:05:47.1969990Z         Currently, ``ZeroRedundancyOptimizer`` requires that all of the
2025-07-17T07:05:47.1970070Z         passed-in parameters are the same dense type.
2025-07-17T07:05:47.1970110Z     
2025-07-17T07:05:47.1970160Z     .. warning::
2025-07-17T07:05:47.1970290Z         If you pass ``overlap_with_ddp=True``, be wary of the following: Given
2025-07-17T07:05:47.1970410Z         the way that overlapping :class:`DistributedDataParallel` with
2025-07-17T07:05:47.1970550Z         :class:`ZeroRedundancyOptimizer` is currently implemented, the first
2025-07-17T07:05:47.1970680Z         two or three training iterations do not perform parameter updates in
2025-07-17T07:05:47.1970790Z         the optimizer step, depending on if ``static_graph=False`` or
2025-07-17T07:05:47.1970910Z         ``static_graph=True``, respectively. This is because it needs
2025-07-17T07:05:47.1971010Z         information about the gradient bucketing strategy used by
2025-07-17T07:05:47.1971150Z         :class:`DistributedDataParallel`, which is not finalized until the
2025-07-17T07:05:47.1971270Z         second forward pass if ``static_graph=False`` or until the third
2025-07-17T07:05:47.1971390Z         forward pass if ``static_graph=True``. To adjust for this, one option
2025-07-17T07:05:47.1971450Z         is to prepend dummy inputs.
2025-07-17T07:05:47.1971490Z     
2025-07-17T07:05:47.1971640Z     .. warning:: ZeroRedundancyOptimizer is experimental and subject to change.
2025-07-17T07:05:47.1971680Z     
2025-07-17T07:05:47.1971840Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1971870Z     
2025-07-17T07:05:47.1971930Z       warnings.warn(msg)
2025-07-17T07:05:47.1971960Z     
2025-07-17T07:05:47.1972060Z --- Parse Warning: 76 / 136 ---
2025-07-17T07:05:47.1972880Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.set_state_dict_type in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=637.
2025-07-17T07:05:47.1973050Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1973200Z     Set the ``state_dict_type`` of all the descendant FSDP modules of the target module.
2025-07-17T07:05:47.1973250Z     
2025-07-17T07:05:47.1973400Z             Also takes (optional) configuration for the model's and optimizer's state dict.
2025-07-17T07:05:47.1973550Z             The target module does not have to be a FSDP module. If the target
2025-07-17T07:05:47.1973680Z             module is a FSDP module, its ``state_dict_type`` will also be changed.
2025-07-17T07:05:47.1973720Z     
2025-07-17T07:05:47.1973840Z             .. note:: This API should be called for only the top-level (root)
2025-07-17T07:05:47.1973880Z                 module.
2025-07-17T07:05:47.1973920Z     
2025-07-17T07:05:47.1974050Z             .. note:: This API enables users to transparently use the conventional
2025-07-17T07:05:47.1974190Z                 ``state_dict`` API to take model checkpoints in cases where the
2025-07-17T07:05:47.1974330Z                 root FSDP module is wrapped by another ``nn.Module``. For example,
2025-07-17T07:05:47.1974460Z                 the following will ensure ``state_dict`` is called on all non-FSDP
2025-07-17T07:05:47.1974600Z                 instances, while dispatching into `sharded_state_dict` implementation
2025-07-17T07:05:47.1974650Z                 for FSDP:
2025-07-17T07:05:47.1974690Z     
2025-07-17T07:05:47.1974740Z             Example::
2025-07-17T07:05:47.1974770Z     
2025-07-17T07:05:47.1974860Z                 >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:47.1974920Z                 >>> model = DDP(FSDP(...))
2025-07-17T07:05:47.1974980Z                 >>> FSDP.set_state_dict_type(
2025-07-17T07:05:47.1975030Z                 >>>     model,
2025-07-17T07:05:47.1975110Z                 >>>     StateDictType.SHARDED_STATE_DICT,
2025-07-17T07:05:47.1975240Z                 >>>     state_dict_config = ShardedStateDictConfig(offload_to_cpu=True),
2025-07-17T07:05:47.1975390Z                 >>>     optim_state_dict_config = OptimStateDictConfig(offload_to_cpu=True),
2025-07-17T07:05:47.1975430Z                 >>> )
2025-07-17T07:05:47.1975510Z                 >>> param_state_dict = model.state_dict()
2025-07-17T07:05:47.1975620Z                 >>> optim_state_dict = FSDP.optim_state_dict(model, optim)
2025-07-17T07:05:47.1975660Z     
2025-07-17T07:05:47.1975700Z             Args:
2025-07-17T07:05:47.1975770Z                 module (torch.nn.Module): Root module.
2025-07-17T07:05:47.1975910Z                 state_dict_type (StateDictType): the desired ``state_dict_type`` to set.
2025-07-17T07:05:47.1976060Z                 state_dict_config (Optional[StateDictConfig]): the configuration for the
2025-07-17T07:05:47.1976120Z                     target ``state_dict_type``.
2025-07-17T07:05:47.1976280Z                 optim_state_dict_config (Optional[OptimStateDictConfig]): the configuration
2025-07-17T07:05:47.1976350Z                     for the optimizer state dict.
2025-07-17T07:05:47.1976390Z     
2025-07-17T07:05:47.1976440Z             Returns:
2025-07-17T07:05:47.1976570Z                 A StateDictSettings that include the previous state_dict type and
2025-07-17T07:05:47.1976640Z                 configuration for the module.
2025-07-17T07:05:47.1976680Z             
2025-07-17T07:05:47.1976830Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1976870Z     
2025-07-17T07:05:47.1976920Z       warnings.warn(msg)
2025-07-17T07:05:47.1976960Z     
2025-07-17T07:05:47.1977060Z --- Parse Warning: 77 / 136 ---
2025-07-17T07:05:47.1977860Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.state_dict_type in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=795.
2025-07-17T07:05:47.1978050Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1978200Z     Set the ``state_dict_type`` of all the descendant FSDP modules of the target module.
2025-07-17T07:05:47.1978240Z     
2025-07-17T07:05:47.1978450Z             This context manager has the same functions as :meth:`set_state_dict_type`. Read the document of
2025-07-17T07:05:47.1978530Z             :meth:`set_state_dict_type` for the detail.
2025-07-17T07:05:47.1978570Z     
2025-07-17T07:05:47.1978620Z             Example::
2025-07-17T07:05:47.1978660Z     
2025-07-17T07:05:47.1978740Z                 >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:47.1978800Z                 >>> model = DDP(FSDP(...))
2025-07-17T07:05:47.1978870Z                 >>> with FSDP.state_dict_type(
2025-07-17T07:05:47.1978910Z                 >>>     model,
2025-07-17T07:05:47.1978990Z                 >>>     StateDictType.SHARDED_STATE_DICT,
2025-07-17T07:05:47.1979060Z                 >>> ):
2025-07-17T07:05:47.1979150Z                 >>>     checkpoint = model.state_dict()
2025-07-17T07:05:47.1979190Z     
2025-07-17T07:05:47.1979240Z             Args:
2025-07-17T07:05:47.1979310Z                 module (torch.nn.Module): Root module.
2025-07-17T07:05:47.1979450Z                 state_dict_type (StateDictType): the desired ``state_dict_type`` to set.
2025-07-17T07:05:47.1979590Z                 state_dict_config (Optional[StateDictConfig]): the model ``state_dict``
2025-07-17T07:05:47.1979690Z                     configuration for the target ``state_dict_type``.
2025-07-17T07:05:47.1979830Z                 optim_state_dict_config (Optional[OptimStateDictConfig]): the optimizer
2025-07-17T07:05:47.1979950Z                    ``state_dict`` configuration for the target ``state_dict_type``.
2025-07-17T07:05:47.1979990Z             
2025-07-17T07:05:47.1980150Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1980180Z     
2025-07-17T07:05:47.1980240Z       warnings.warn(msg)
2025-07-17T07:05:47.1980280Z     
2025-07-17T07:05:47.1980380Z --- Parse Warning: 78 / 136 ---
2025-07-17T07:05:47.1981180Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.optim_state_dict in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1808.
2025-07-17T07:05:47.1981340Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1981380Z     
2025-07-17T07:05:47.1981520Z     Transform the state-dict of an optimizer corresponding to a sharded model.
2025-07-17T07:05:47.1981560Z     
2025-07-17T07:05:47.1981680Z     The given state-dict can be transformed to one of three types:
2025-07-17T07:05:47.1981860Z     1) full optimizer state_dict, 2) sharded optimizer state_dict, 3) local optimizer state_dict.
2025-07-17T07:05:47.1981900Z     
2025-07-17T07:05:47.1982040Z     For full optimizer state_dict, all states are unflattened and not sharded.
2025-07-17T07:05:47.1982170Z     Rank0 only and CPU only can be specified via :meth:`state_dict_type` to
2025-07-17T07:05:47.1982220Z     avoid OOM.
2025-07-17T07:05:47.1982260Z     
2025-07-17T07:05:47.1982400Z     For sharded optimizer state_dict, all states are unflattened but sharded.
2025-07-17T07:05:47.1982520Z     CPU only can be specified via :meth:`state_dict_type` to further save
2025-07-17T07:05:47.1982560Z     memory.
2025-07-17T07:05:47.1982600Z     
2025-07-17T07:05:47.1982800Z     For local state_dict, no transformation will be performed. But a state
2025-07-17T07:05:47.1982940Z     will be converted from nn.Tensor to ShardedTensor to represent its sharding
2025-07-17T07:05:47.1983000Z     nature (this is not supported yet).
2025-07-17T07:05:47.1983040Z     
2025-07-17T07:05:47.1983090Z     Example::
2025-07-17T07:05:47.1983130Z     
2025-07-17T07:05:47.1983270Z         >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:47.1983420Z         >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-07-17T07:05:47.1983520Z         >>> from torch.distributed.fsdp import StateDictType
2025-07-17T07:05:47.1983660Z         >>> from torch.distributed.fsdp import FullStateDictConfig
2025-07-17T07:05:47.1983780Z         >>> from torch.distributed.fsdp import FullOptimStateDictConfig
2025-07-17T07:05:47.1983830Z         >>> # Save a checkpoint
2025-07-17T07:05:47.1983890Z         >>> model, optim = ...
2025-07-17T07:05:47.1983950Z         >>> FSDP.set_state_dict_type(
2025-07-17T07:05:47.1983990Z         >>>     model,
2025-07-17T07:05:47.1984060Z         >>>     StateDictType.FULL_STATE_DICT,
2025-07-17T07:05:47.1984130Z         >>>     FullStateDictConfig(rank0_only=False),
2025-07-17T07:05:47.1984220Z         >>>     FullOptimStateDictConfig(rank0_only=False),
2025-07-17T07:05:47.1984260Z         >>> )
2025-07-17T07:05:47.1984340Z         >>> state_dict = model.state_dict()
2025-07-17T07:05:47.1984460Z         >>> optim_state_dict = FSDP.optim_state_dict(model, optim)
2025-07-17T07:05:47.1984550Z         >>> save_a_checkpoint(state_dict, optim_state_dict)
2025-07-17T07:05:47.1984600Z         >>> # Load a checkpoint
2025-07-17T07:05:47.1984660Z         >>> model, optim = ...
2025-07-17T07:05:47.1984750Z         >>> state_dict, optim_state_dict = load_a_checkpoint()
2025-07-17T07:05:47.1984810Z         >>> FSDP.set_state_dict_type(
2025-07-17T07:05:47.1984860Z         >>>     model,
2025-07-17T07:05:47.1984920Z         >>>     StateDictType.FULL_STATE_DICT,
2025-07-17T07:05:47.1985000Z         >>>     FullStateDictConfig(rank0_only=False),
2025-07-17T07:05:47.1985090Z         >>>     FullOptimStateDictConfig(rank0_only=False),
2025-07-17T07:05:47.1985130Z         >>> )
2025-07-17T07:05:47.1985190Z         >>> model.load_state_dict(state_dict)
2025-07-17T07:05:47.1985290Z         >>> optim_state_dict = FSDP.optim_state_dict_to_load(
2025-07-17T07:05:47.1985360Z         >>>     model, optim, optim_state_dict
2025-07-17T07:05:47.1985400Z         >>> )
2025-07-17T07:05:47.1985470Z         >>> optim.load_state_dict(optim_state_dict)
2025-07-17T07:05:47.1985510Z     
2025-07-17T07:05:47.1985550Z     Args:
2025-07-17T07:05:47.1985670Z         model (torch.nn.Module): Root module (which may or may not be a
2025-07-17T07:05:47.1985800Z             :class:`FullyShardedDataParallel` instance) whose parameters
2025-07-17T07:05:47.1985880Z             were passed into the optimizer ``optim``.
2025-07-17T07:05:47.1985990Z         optim (torch.optim.Optimizer): Optimizer for ``model`` 's
2025-07-17T07:05:47.1986030Z             parameters.
2025-07-17T07:05:47.1986160Z         optim_state_dict (Dict[str, Any]): the target optimizer state_dict to
2025-07-17T07:05:47.1986290Z             transform. If the value is None, optim.state_dict() will be used. (
2025-07-17T07:05:47.1989870Z             Default: ``None``)
2025-07-17T07:05:47.1990060Z         group (dist.ProcessGroup): Model's process group across which parameters
2025-07-17T07:05:47.1990180Z             are sharded or ``None`` if using the default process group. (
2025-07-17T07:05:47.1990230Z             Default: ``None``)
2025-07-17T07:05:47.1990270Z     
2025-07-17T07:05:47.1990320Z     Returns:
2025-07-17T07:05:47.1990430Z         Dict[str, Any]: A :class:`dict` containing the optimizer state for
2025-07-17T07:05:47.1990540Z         ``model``. The sharding of the optimizer state is based on
2025-07-17T07:05:47.1990590Z         ``state_dict_type``.
2025-07-17T07:05:47.1990630Z     
2025-07-17T07:05:47.1990780Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1990820Z     
2025-07-17T07:05:47.1990870Z       warnings.warn(msg)
2025-07-17T07:05:47.1990910Z     
2025-07-17T07:05:47.1991030Z --- Parse Warning: 79 / 136 ---
2025-07-17T07:05:47.1991960Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.optim_state_dict_to_load in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1906.
2025-07-17T07:05:47.1992140Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1992180Z     
2025-07-17T07:05:47.1992390Z     Convert an optimizer state-dict so that it can be loaded into the optimizer associated with the FSDP model.
2025-07-17T07:05:47.1992430Z     
2025-07-17T07:05:47.1992540Z     Given a ``optim_state_dict`` that is transformed through
2025-07-17T07:05:47.1992660Z     :meth:`optim_state_dict`, it gets converted to the flattened optimizer
2025-07-17T07:05:47.1992790Z     state_dict that can be loaded to ``optim`` which is the optimizer for
2025-07-17T07:05:47.1992900Z     ``model``. ``model`` must be sharded by FullyShardedDataParallel.
2025-07-17T07:05:47.1992990Z     
2025-07-17T07:05:47.1993100Z         >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:47.1993250Z         >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-07-17T07:05:47.1993340Z         >>> from torch.distributed.fsdp import StateDictType
2025-07-17T07:05:47.1993460Z         >>> from torch.distributed.fsdp import FullStateDictConfig
2025-07-17T07:05:47.1993570Z         >>> from torch.distributed.fsdp import FullOptimStateDictConfig
2025-07-17T07:05:47.1993630Z         >>> # Save a checkpoint
2025-07-17T07:05:47.1993680Z         >>> model, optim = ...
2025-07-17T07:05:47.1993740Z         >>> FSDP.set_state_dict_type(
2025-07-17T07:05:47.1993790Z         >>>     model,
2025-07-17T07:05:47.1993860Z         >>>     StateDictType.FULL_STATE_DICT,
2025-07-17T07:05:47.1993930Z         >>>     FullStateDictConfig(rank0_only=False),
2025-07-17T07:05:47.1994020Z         >>>     FullOptimStateDictConfig(rank0_only=False),
2025-07-17T07:05:47.1994060Z         >>> )
2025-07-17T07:05:47.1994120Z         >>> state_dict = model.state_dict()
2025-07-17T07:05:47.1994200Z         >>> original_osd = optim.state_dict()
2025-07-17T07:05:47.1994270Z         >>> optim_state_dict = FSDP.optim_state_dict(
2025-07-17T07:05:47.1994320Z         >>>     model,
2025-07-17T07:05:47.1994360Z         >>>     optim,
2025-07-17T07:05:47.1994430Z         >>>     optim_state_dict=original_osd
2025-07-17T07:05:47.1994470Z         >>> )
2025-07-17T07:05:47.1994560Z         >>> save_a_checkpoint(state_dict, optim_state_dict)
2025-07-17T07:05:47.1994610Z         >>> # Load a checkpoint
2025-07-17T07:05:47.1994660Z         >>> model, optim = ...
2025-07-17T07:05:47.1994750Z         >>> state_dict, optim_state_dict = load_a_checkpoint()
2025-07-17T07:05:47.1994810Z         >>> FSDP.set_state_dict_type(
2025-07-17T07:05:47.1994850Z         >>>     model,
2025-07-17T07:05:47.1994920Z         >>>     StateDictType.FULL_STATE_DICT,
2025-07-17T07:05:47.1995000Z         >>>     FullStateDictConfig(rank0_only=False),
2025-07-17T07:05:47.1995080Z         >>>     FullOptimStateDictConfig(rank0_only=False),
2025-07-17T07:05:47.1995130Z         >>> )
2025-07-17T07:05:47.1995190Z         >>> model.load_state_dict(state_dict)
2025-07-17T07:05:47.1995280Z         >>> optim_state_dict = FSDP.optim_state_dict_to_load(
2025-07-17T07:05:47.1995350Z         >>>     model, optim, optim_state_dict
2025-07-17T07:05:47.1995390Z         >>> )
2025-07-17T07:05:47.1995460Z         >>> optim.load_state_dict(optim_state_dict)
2025-07-17T07:05:47.1995500Z     
2025-07-17T07:05:47.1995540Z     Args:
2025-07-17T07:05:47.1995660Z         model (torch.nn.Module): Root module (which may or may not be a
2025-07-17T07:05:47.1995780Z             :class:`FullyShardedDataParallel` instance) whose parameters
2025-07-17T07:05:47.1995860Z             were passed into the optimizer ``optim``.
2025-07-17T07:05:47.1995970Z         optim (torch.optim.Optimizer): Optimizer for ``model`` 's
2025-07-17T07:05:47.1996020Z             parameters.
2025-07-17T07:05:47.1996170Z         optim_state_dict (Dict[str, Any]): The optimizer states to be loaded.
2025-07-17T07:05:47.1996290Z         is_named_optimizer (bool): Is this optimizer a NamedOptimizer or
2025-07-17T07:05:47.1996410Z             KeyedOptimizer. Only set to True if ``optim`` is TorchRec's
2025-07-17T07:05:47.1996540Z             KeyedOptimizer or torch.distributed's NamedOptimizer.
2025-07-17T07:05:47.1996660Z         load_directly (bool): If this is set to True, this API will also
2025-07-17T07:05:47.1996780Z             call optim.load_state_dict(result) before returning the result.
2025-07-17T07:05:47.1996910Z             Otherwise, users are responsible to call ``optim.load_state_dict()``
2025-07-17T07:05:47.1996970Z             (Default: ``False``)
2025-07-17T07:05:47.1997110Z         group (dist.ProcessGroup): Model's process group across which parameters
2025-07-17T07:05:47.1997220Z             are sharded or ``None`` if using the default process group. (
2025-07-17T07:05:47.1997290Z             Default: ``None``)
2025-07-17T07:05:47.1997360Z     
2025-07-17T07:05:47.1997510Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.1997550Z     
2025-07-17T07:05:47.1997600Z       warnings.warn(msg)
2025-07-17T07:05:47.1997640Z     
2025-07-17T07:05:47.1997740Z --- Parse Warning: 80 / 136 ---
2025-07-17T07:05:47.1998410Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MixedPrecision in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/fsdp/api.py line=114.
2025-07-17T07:05:47.1998560Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.1998610Z     
2025-07-17T07:05:47.1998710Z     This configures FSDP-native mixed precision training.
2025-07-17T07:05:47.1998750Z     
2025-07-17T07:05:47.1998790Z     Attributes:
2025-07-17T07:05:47.1998940Z         param_dtype (Optional[torch.dtype]): This specifies the dtype for model
2025-07-17T07:05:47.1999060Z             parameters during forward and backward and thus the dtype for
2025-07-17T07:05:47.1999190Z             forward and backward computation. Outside forward and backward, the
2025-07-17T07:05:47.1999310Z             *sharded* parameters are kept in full precision (e.g. for the
2025-07-17T07:05:47.1999430Z             optimizer step), and for model checkpointing, the parameters are
2025-07-17T07:05:47.1999530Z             always saved in full precision. (Default: ``None``)
2025-07-17T07:05:47.1999650Z         reduce_dtype (Optional[torch.dtype]): This specifies the dtype for
2025-07-17T07:05:47.1999780Z             gradient reduction (i.e. reduce-scatter or all-reduce). If this is
2025-07-17T07:05:47.1999890Z             ``None`` but ``param_dtype`` is not ``None``, then this takes on
2025-07-17T07:05:47.2000010Z             the ``param_dtype`` value, still running gradient reduction in low
2025-07-17T07:05:47.2000140Z             precision. This is permitted to differ from ``param_dtype``, e.g.
2025-07-17T07:05:47.2000260Z             to force gradient reduction to run in full precision. (Default:
2025-07-17T07:05:47.2000310Z             ``None``)
2025-07-17T07:05:47.2000440Z         buffer_dtype (Optional[torch.dtype]): This specifies the dtype for
2025-07-17T07:05:47.2000560Z             buffers. FSDP does not shard buffers. Rather, FSDP casts them to
2025-07-17T07:05:47.2000680Z             ``buffer_dtype`` in the first forward pass and keeps them in that
2025-07-17T07:05:47.2000800Z             dtype thereafter. For model checkpointing, the buffers are saved
2025-07-17T07:05:47.2000910Z             in full precision except for ``LOCAL_STATE_DICT``. (Default:
2025-07-17T07:05:47.2000950Z             ``None``)
2025-07-17T07:05:47.2001070Z         keep_low_precision_grads (bool): If ``False``, then FSDP upcasts
2025-07-17T07:05:47.2001200Z             gradients to full precision after the backward pass in preparation
2025-07-17T07:05:47.2001360Z             for the optimizer step. If ``True``, then FSDP keeps the gradients
2025-07-17T07:05:47.2001480Z             in the dtype used for gradient reduction, which can save memory if
2025-07-17T07:05:47.2001600Z             using a custom optimizer that supports running in low precision.
2025-07-17T07:05:47.2001680Z             (Default: ``False``)
2025-07-17T07:05:47.2001800Z         cast_forward_inputs (bool): If ``True``, then this FSDP module casts
2025-07-17T07:05:47.2001920Z             its forward args and kwargs to ``param_dtype``. This is to ensure
2025-07-17T07:05:47.2002050Z             that parameter and input dtypes match for forward computation, as
2025-07-17T07:05:47.2002170Z             required by many ops. This may need to be set to ``True`` when only
2025-07-17T07:05:47.2002300Z             applying mixed precision to some but not all FSDP modules, in which
2025-07-17T07:05:47.2002450Z             case a mixed-precision FSDP submodule needs to recast its inputs.
2025-07-17T07:05:47.2002520Z             (Default: ``False``)
2025-07-17T07:05:47.2002660Z         cast_root_forward_inputs (bool): If ``True``, then the root FSDP module
2025-07-17T07:05:47.2002780Z             casts its forward args and kwargs to ``param_dtype``, overriding
2025-07-17T07:05:47.2002890Z             the value of ``cast_forward_inputs``. For non-root FSDP modules,
2025-07-17T07:05:47.2002980Z             this does not do anything. (Default: ``True``)
2025-07-17T07:05:47.2003110Z         _module_classes_to_ignore: (Sequence[Type[nn.Module]]): This specifies
2025-07-17T07:05:47.2003220Z             module classes to ignore for mixed precision when using an
2025-07-17T07:05:47.2003330Z             ``auto_wrap_policy``: Modules of these classes will have FSDP
2025-07-17T07:05:47.2003450Z             applied to them separately with mixed precision disabled (meaning
2025-07-17T07:05:47.2003580Z             that the final FSDP construction would deviate from the specified
2025-07-17T07:05:47.2003690Z             policy). If ``auto_wrap_policy`` is not specified, then this does
2025-07-17T07:05:47.2003810Z             not do anything. This API is experimental and subject to change.
2025-07-17T07:05:47.2003870Z             (Default: ``(_BatchNorm,)``)
2025-07-17T07:05:47.2003910Z     
2025-07-17T07:05:47.2004020Z     .. note:: This API is experimental and subject to change.
2025-07-17T07:05:47.2004060Z     
2025-07-17T07:05:47.2004190Z     .. note:: Only floating point tensors are cast to their specified dtypes.
2025-07-17T07:05:47.2004230Z     
2025-07-17T07:05:47.2004340Z     .. note:: In ``summon_full_params``, parameters are forced to full
2025-07-17T07:05:47.2004400Z         precision, but buffers are not.
2025-07-17T07:05:47.2004440Z     
2025-07-17T07:05:47.2004560Z     .. note:: Layer norm and batch norm accumulate in ``float32`` even when
2025-07-17T07:05:47.2004690Z         their inputs are in a low precision like ``float16`` or ``bfloat16``.
2025-07-17T07:05:47.2004830Z         Disabling FSDP's mixed precision for those norm modules only means that
2025-07-17T07:05:47.2004960Z         the affine parameters are kept in ``float32``. However, this incurs
2025-07-17T07:05:47.2005100Z         separate all-gathers and reduce-scatters for those norm modules, which
2025-07-17T07:05:47.2005230Z         may be inefficient, so if the workload permits, the user should prefer
2025-07-17T07:05:47.2005320Z         to still apply mixed precision to those modules.
2025-07-17T07:05:47.2005360Z     
2025-07-17T07:05:47.2005480Z     .. note:: By default, if the user passes a model with any ``_BatchNorm``
2025-07-17T07:05:47.2005610Z         modules and specifies an ``auto_wrap_policy``, then the batch norm
2025-07-17T07:05:47.2005740Z         modules will have FSDP applied to them separately with mixed precision
2025-07-17T07:05:47.2005840Z         disabled. See the ``_module_classes_to_ignore`` argument.
2025-07-17T07:05:47.2005880Z     
2025-07-17T07:05:47.2006000Z     .. note:: ``MixedPrecision`` has ``cast_root_forward_inputs=True`` and
2025-07-17T07:05:47.2006160Z         ``cast_forward_inputs=False`` by default. For the root FSDP instance,
2025-07-17T07:05:47.2006260Z         its ``cast_root_forward_inputs`` takes precedence over its
2025-07-17T07:05:47.2006430Z         ``cast_forward_inputs``. For non-root FSDP instances, their
2025-07-17T07:05:47.2006560Z         ``cast_root_forward_inputs`` values are ignored. The default setting is
2025-07-17T07:05:47.2006690Z         sufficient for the typical case where each FSDP instance has the same
2025-07-17T07:05:47.2006820Z         ``MixedPrecision`` configuration and only needs to cast inputs to the
2025-07-17T07:05:47.2006940Z         ``param_dtype`` at the beginning of the model's forward pass.
2025-07-17T07:05:47.2006980Z     
2025-07-17T07:05:47.2007100Z     .. note:: For nested FSDP instances with different ``MixedPrecision``
2025-07-17T07:05:47.2007260Z         configurations, we recommend setting individual ``cast_forward_inputs``
2025-07-17T07:05:47.2007400Z         values to configure casting inputs or not before each instance's
2025-07-17T07:05:47.2007520Z         forward. In such a case, since the casts happen before each FSDP
2025-07-17T07:05:47.2007650Z         instance's forward, a parent FSDP instance should have its non-FSDP
2025-07-17T07:05:47.2007790Z         submodules run before its FSDP submodules to avoid the activation dtype
2025-07-17T07:05:47.2007910Z         being changed due to a different ``MixedPrecision`` configuration.
2025-07-17T07:05:47.2007950Z     
2025-07-17T07:05:47.2008000Z         Example::
2025-07-17T07:05:47.2008040Z     
2025-07-17T07:05:47.2008120Z             >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:47.2008220Z             >>> model = nn.Sequential(nn.Linear(3, 3), nn.Linear(3, 3))
2025-07-17T07:05:47.2008270Z             >>> model[1] = FSDP(
2025-07-17T07:05:47.2008330Z             >>>     model[1],
2025-07-17T07:05:47.2008510Z             >>>     mixed_precision=MixedPrecision(param_dtype=torch.float16, cast_forward_inputs=True),
2025-07-17T07:05:47.2008560Z             >>> )
2025-07-17T07:05:47.2008610Z             >>> model = FSDP(
2025-07-17T07:05:47.2008650Z             >>>     model,
2025-07-17T07:05:47.2008830Z             >>>     mixed_precision=MixedPrecision(param_dtype=torch.bfloat16, cast_forward_inputs=True),
2025-07-17T07:05:47.2008880Z             >>> )
2025-07-17T07:05:47.2008920Z     
2025-07-17T07:05:47.2009040Z         The above shows a working example. On the other hand, if ``model[1]``
2025-07-17T07:05:47.2009160Z         were replaced with ``model[0]``, meaning that the submodule using
2025-07-17T07:05:47.2009300Z         different ``MixedPrecision`` ran its forward first, then ``model[1]``
2025-07-17T07:05:47.2009420Z         would incorrectly see ``float16`` activations instead of ``bfloat16``
2025-07-17T07:05:47.2009470Z         ones.
2025-07-17T07:05:47.2009510Z     
2025-07-17T07:05:47.2009550Z     
2025-07-17T07:05:47.2009700Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2009740Z     
2025-07-17T07:05:47.2009790Z       warnings.warn(msg)
2025-07-17T07:05:47.2009830Z     
2025-07-17T07:05:47.2009930Z --- Parse Warning: 81 / 136 ---
2025-07-17T07:05:47.2010620Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullStateDictConfig in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/fsdp/api.py line=295.
2025-07-17T07:05:47.2010770Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2010810Z     
2025-07-17T07:05:47.2010930Z     ``FullStateDictConfig`` is a config class meant to be used with
2025-07-17T07:05:47.2011050Z     ``StateDictType.FULL_STATE_DICT``. We recommend enabling both
2025-07-17T07:05:47.2011180Z     ``offload_to_cpu=True`` and ``rank0_only=True`` when saving full state
2025-07-17T07:05:47.2011330Z     dicts to save GPU memory and CPU memory, respectively. This config class
2025-07-17T07:05:47.2011450Z     is meant to be used via the :func:`state_dict_type` context manager as
2025-07-17T07:05:47.2011500Z     follows:
2025-07-17T07:05:47.2011560Z     
2025-07-17T07:05:47.2011640Z         >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:47.2011780Z         >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
2025-07-17T07:05:47.2011860Z         >>> fsdp = FSDP(model, auto_wrap_policy=...)
2025-07-17T07:05:47.2011980Z         >>> cfg = FullStateDictConfig(offload_to_cpu=True, rank0_only=True)
2025-07-17T07:05:47.2012110Z         >>> with FSDP.state_dict_type(fsdp, StateDictType.FULL_STATE_DICT, cfg):
2025-07-17T07:05:47.2012170Z         >>>     state = fsdp.state_dict()
2025-07-17T07:05:47.2012300Z         >>> # `state` will be empty on non rank 0 and contain CPU tensors on rank 0.
2025-07-17T07:05:47.2012470Z         >>> # To reload checkpoint for inference, finetuning, transfer learning, etc:
2025-07-17T07:05:47.2012640Z         >>> model = model_fn()  # Initialize model in preparation for wrapping with FSDP
2025-07-17T07:05:47.2012700Z         >>> if dist.get_rank() == 0:
2025-07-17T07:05:47.2012810Z         >>> # Load checkpoint only on rank 0 to avoid memory redundancy
2025-07-17T07:05:47.2012900Z         >>>     state_dict = torch.load("my_checkpoint.pt")
2025-07-17T07:05:47.2012970Z         >>>     model.load_state_dict(state_dict)
2025-07-17T07:05:47.2013110Z         >>> # All ranks initialize FSDP module as usual. `sync_module_states` argument
2025-07-17T07:05:47.2013250Z         >>> # communicates loaded checkpoint states from rank 0 to rest of the world.
2025-07-17T07:05:47.2013300Z         >>> fsdp = FSDP(
2025-07-17T07:05:47.2013340Z         ...     model,
2025-07-17T07:05:47.2013420Z         ...     device_id=torch.cuda.current_device(),
2025-07-17T07:05:47.2013480Z         ...     auto_wrap_policy=...,
2025-07-17T07:05:47.2013540Z         ...     sync_module_states=True,
2025-07-17T07:05:47.2013580Z         ... )
2025-07-17T07:05:47.2013710Z         >>> # After this point, all ranks have FSDP model with loaded checkpoint.
2025-07-17T07:05:47.2013750Z     
2025-07-17T07:05:47.2013790Z     Attributes:
2025-07-17T07:05:47.2013910Z         rank0_only (bool): If ``True``, then only rank 0 saves the full state
2025-07-17T07:05:47.2014040Z             dict, and nonzero ranks save an empty dict. If ``False``, then all
2025-07-17T07:05:47.2014130Z             ranks save the full state dict. (Default: ``False``)
2025-07-17T07:05:47.2014170Z     
2025-07-17T07:05:47.2014320Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2014360Z     
2025-07-17T07:05:47.2014410Z       warnings.warn(msg)
2025-07-17T07:05:47.2014450Z     
2025-07-17T07:05:47.2014550Z --- Parse Warning: 82 / 136 ---
2025-07-17T07:05:47.2015290Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=init_from_local_shards in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py line=361.
2025-07-17T07:05:47.2015440Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2015480Z     
2025-07-17T07:05:47.2015620Z     Creates an :class:`ShardedTensor` from local shards and the global metadata.
2025-07-17T07:05:47.2015710Z     Needs to be called on all ranks in an SPMD fashion.
2025-07-17T07:05:47.2015750Z     
2025-07-17T07:05:47.2015790Z     Args:
2025-07-17T07:05:47.2015960Z         local_shards (List[:class `torch.distributed._shard.sharded_tensor.Shard`]): A list
2025-07-17T07:05:47.2016060Z             of shards that represent the local shards on this rank.
2025-07-17T07:05:47.2016200Z         global_size (int...):  a list, tuple, or `torch.Size` of integers defining the
2025-07-17T07:05:47.2016270Z             shape of the overall sharded tensor.
2025-07-17T07:05:47.2016330Z     
2025-07-17T07:05:47.2016380Z     Keyword args:
2025-07-17T07:05:47.2016540Z         process_group (ProcessGroup, optional): The process group to work on. If None,
2025-07-17T07:05:47.2016630Z             the default process group will be used.
2025-07-17T07:05:47.2016740Z         init_rrefs (bool, optional): Whether or not to initialize
2025-07-17T07:05:47.2016870Z             :class:`torch.distributed.rpc.RRef`s pointing to remote shards.
2025-07-17T07:05:47.2016980Z             Need to initialize the RPC Framework if specified as ``True``.
2025-07-17T07:05:47.2017040Z             Default: ``False``.
2025-07-17T07:05:47.2017080Z     
2025-07-17T07:05:47.2017120Z     Returns:
2025-07-17T07:05:47.2017210Z         A :class:`ShardedTensor` object handle on this rank
2025-07-17T07:05:47.2017250Z     
2025-07-17T07:05:47.2017290Z     
2025-07-17T07:05:47.2017330Z     Examples:
2025-07-17T07:05:47.2017500Z         Suppose we want construct a sharded tensor on two ranks, global size = (10, 5),
2025-07-17T07:05:47.2017640Z         each shard have a (5, 5) local tensor, we can do it like below:
2025-07-17T07:05:47.2017680Z     
2025-07-17T07:05:47.2017730Z         on rank 0:
2025-07-17T07:05:47.2017800Z         >>> # xdoctest: +SKIP("not distributed")
2025-07-17T07:05:47.2017870Z         >>> local_shard_metadata = ShardMetadata(
2025-07-17T07:05:47.2017930Z         >>>     shard_offsets=[0, 0],
2025-07-17T07:05:47.2017980Z         >>>     shard_lengths=[5, 5],
2025-07-17T07:05:47.2018040Z         >>>     placement="rank:0/cuda:0"
2025-07-17T07:05:47.2018090Z         >>> )
2025-07-17T07:05:47.2018210Z         >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)]
2025-07-17T07:05:47.2018320Z         >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5])
2025-07-17T07:05:47.2018360Z     
2025-07-17T07:05:47.2018400Z         on rank 1:
2025-07-17T07:05:47.2018480Z         >>> # xdoctest: +SKIP("not distributed")
2025-07-17T07:05:47.2018550Z         >>> local_shard_metadata = ShardMetadata(
2025-07-17T07:05:47.2018610Z         >>>     shard_offsets=[5, 0],
2025-07-17T07:05:47.2018660Z         >>>     shard_lengths=[5, 5],
2025-07-17T07:05:47.2018720Z         >>>     placement="rank:1/cuda:1"
2025-07-17T07:05:47.2018760Z         >>> )
2025-07-17T07:05:47.2018880Z         >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)]
2025-07-17T07:05:47.2018990Z         >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5])
2025-07-17T07:05:47.2019040Z     
2025-07-17T07:05:47.2019180Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2019220Z     
2025-07-17T07:05:47.2019270Z       warnings.warn(msg)
2025-07-17T07:05:47.2019310Z     
2025-07-17T07:05:47.2019410Z --- Parse Warning: 83 / 136 ---
2025-07-17T07:05:47.2020170Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardedTensor._init_from_local_tensor in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=835.
2025-07-17T07:05:47.2020330Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2020370Z     
2025-07-17T07:05:47.2020530Z     Initialize a ShardedTensor given only one local tensor, global sharded tensor
2025-07-17T07:05:47.2020590Z     size and sharding spec on each rank.
2025-07-17T07:05:47.2020630Z     
2025-07-17T07:05:47.2020670Z     Args:
2025-07-17T07:05:47.2020810Z         local_tensor (Tensor): Single tensor of local shard stored in each rank.
2025-07-17T07:05:47.2020960Z         sharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`):
2025-07-17T07:05:47.2021060Z             The specification describing how to shard the Tensor.
2025-07-17T07:05:47.2021160Z         global_size (Sequence[int]): Size of the sharded tensor.
2025-07-17T07:05:47.2021350Z         process_group (ProcessGroup, optional): The process group to aggregate on.
2025-07-17T07:05:47.2021400Z             Default: None
2025-07-17T07:05:47.2021510Z         init_rrefs (bool, optional): Whether or not to initialize
2025-07-17T07:05:47.2021650Z             :class:`torch.distributed.rpc.RRef`s pointing to remote shards.
2025-07-17T07:05:47.2021770Z             Need to initialize the RPC Framework if specified as ``True``.
2025-07-17T07:05:47.2021820Z             Default: ``False``.
2025-07-17T07:05:47.2021860Z     
2025-07-17T07:05:47.2021900Z     Returns:
2025-07-17T07:05:47.2022050Z         A :class:`ShardedTensor` sharded based on the given sharding_spec with local
2025-07-17T07:05:47.2022120Z             tensor stored in the current rank.
2025-07-17T07:05:47.2022160Z     
2025-07-17T07:05:47.2022200Z     Examples:
2025-07-17T07:05:47.2022250Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2022360Z         >>> # All tensors below are of torch.int64 type.
2025-07-17T07:05:47.2022450Z         >>> # We have 2 process groups, 2 ranks.
2025-07-17T07:05:47.2022550Z         >>> tensor = torch.arange(2, dtype=torch.int64) + 1 + 2 * rank
2025-07-17T07:05:47.2022670Z         >>> local_tensor = torch.unsqueeze(torch.cat([tensor, tensor + 2]))
2025-07-17T07:05:47.2022720Z         >>> local_tensor
2025-07-17T07:05:47.2022780Z         tensor([[1, 2, 3, 4]]) # Rank 0
2025-07-17T07:05:47.2022830Z         tensor([[3, 4, 5, 6]]) # Rank 1
2025-07-17T07:05:47.2022880Z         >>> sharding_dim = 0
2025-07-17T07:05:47.2022960Z         >>> sharding_spec = ChunkShardingSpec(
2025-07-17T07:05:47.2023010Z                 dim=sharding_dim,
2025-07-17T07:05:47.2023060Z                 placements=[
2025-07-17T07:05:47.2023120Z                     "rank:0/cuda:0",
2025-07-17T07:05:47.2023170Z                     "rank:1/cuda:1",
2025-07-17T07:05:47.2023210Z                 ],
2025-07-17T07:05:47.2023250Z             )
2025-07-17T07:05:47.2023330Z         >>> st = ShardedTensor._init_from_local_tensor(
2025-07-17T07:05:47.2023410Z         ...     local_tensor, sharding_spec, [2, 4]
2025-07-17T07:05:47.2023450Z         ... )
2025-07-17T07:05:47.2023490Z         >>> st
2025-07-17T07:05:47.2023540Z         ShardedTensor(
2025-07-17T07:05:47.2023600Z             ShardedTensorMetadata(
2025-07-17T07:05:47.2023660Z                 shards_metadata=[
2025-07-17T07:05:47.2023820Z                     ShardMetadata(shard_offsets=[0, 0], shard_sizes=[1, 4], placement=rank:0/cuda:0),
2025-07-17T07:05:47.2023980Z                     ShardMetadata(shard_offsets=[1, 0], shard_sizes=[1, 4], placement=rank:1/cuda:1),
2025-07-17T07:05:47.2024020Z                 ],
2025-07-17T07:05:47.2024080Z                 size=torch.Size([2, 4])
2025-07-17T07:05:47.2024120Z         )
2025-07-17T07:05:47.2024170Z         >>> st.local_tensor()
2025-07-17T07:05:47.2024230Z         tensor([1, 2, 3, 4]) # Rank 0
2025-07-17T07:05:47.2024280Z         tensor([3, 4, 5, 6]) # Rank 1
2025-07-17T07:05:47.2024320Z     
2025-07-17T07:05:47.2024480Z     Warning: This API is experimental and subject to change. It lacks of a fully across
2025-07-17T07:05:47.2024630Z              rank validations, and we only validate the local shard on the current rank.
2025-07-17T07:05:47.2024760Z              We fully rely on the user to ensure local tensor is sharded based on the
2025-07-17T07:05:47.2024810Z              sharding spec.
2025-07-17T07:05:47.2024850Z     
2025-07-17T07:05:47.2025000Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2025040Z     
2025-07-17T07:05:47.2025090Z       warnings.warn(msg)
2025-07-17T07:05:47.2025130Z     
2025-07-17T07:05:47.2025230Z --- Parse Warning: 84 / 136 ---
2025-07-17T07:05:47.2025960Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardedTensor.reshard in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=1076.
2025-07-17T07:05:47.2026140Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2026190Z     
2025-07-17T07:05:47.2026340Z     Reshard a sharded tensor given the ``resharding_spec``. For now, we only support
2025-07-17T07:05:47.2026420Z     single local shard.
2025-07-17T07:05:47.2026460Z     
2025-07-17T07:05:47.2026590Z     If ``resharding_spec`` is same as the original one, this becomes a no-op.
2025-07-17T07:05:47.2026740Z     If only ``resharding_spec`` shares the same sharding dim with the original one,
2025-07-17T07:05:47.2026800Z     we swap local shards directly.
2025-07-17T07:05:47.2026950Z     For more generic cases, we merge different shards across different ranks and split
2025-07-17T07:05:47.2027100Z     the local shards based on the ``resharding_spec`` via `all_to_all` collective API.
2025-07-17T07:05:47.2027140Z     
2025-07-17T07:05:47.2027180Z     Args:
2025-07-17T07:05:47.2027380Z         resharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): The
2025-07-17T07:05:47.2027490Z             specification describing how the tensor is sharded.
2025-07-17T07:05:47.2027540Z     
2025-07-17T07:05:47.2027580Z     Returns:
2025-07-17T07:05:47.2027710Z         A :class:`ShardedTensor` object whose local shards are resharded.
2025-07-17T07:05:47.2027740Z     
2025-07-17T07:05:47.2027790Z     Examples:
2025-07-17T07:05:47.2027840Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2027910Z         >>> # We have 2 process groups, 2 ranks.
2025-07-17T07:05:47.2028010Z         >>> tensor = torch.arange(4, dtype=torch.int64) + 1 + 2 * rank
2025-07-17T07:05:47.2028090Z         >>> tensor = torch.stack([tensor, tensor])
2025-07-17T07:05:47.2028130Z         >>> tensor
2025-07-17T07:05:47.2028200Z         tensor([[1, 2, 3, 4], [1, 2, 3, 4]]) # Rank 0
2025-07-17T07:05:47.2028270Z         tensor([[3, 4, 5, 6], [3, 4, 5, 6]]) # Rank 1
2025-07-17T07:05:47.2028340Z         tensor([[5, 6, 7, 8], [5, 6, 7, 8]]) # Rank 2
2025-07-17T07:05:47.2028420Z         tensor([[7, 8, 9, 10], [7, 8, 9, 10]]) # Rank 3
2025-07-17T07:05:47.2028470Z         >>> sharding_dim = 0
2025-07-17T07:05:47.2028530Z         >>> spec = ChunkShardingSpec(
2025-07-17T07:05:47.2028590Z                 dim=sharding_dim,
2025-07-17T07:05:47.2028640Z                 placements=[
2025-07-17T07:05:47.2028700Z                     "rank:0/cuda:0",
2025-07-17T07:05:47.2028750Z                     "rank:1/cuda:1",
2025-07-17T07:05:47.2028800Z                     "rank:2/cuda:2",
2025-07-17T07:05:47.2028850Z                     "rank:3/cuda:3",
2025-07-17T07:05:47.2028890Z                 ],
2025-07-17T07:05:47.2028930Z             )
2025-07-17T07:05:47.2028980Z         >>> current_offsets = [0] * 2
2025-07-17T07:05:47.2029040Z         >>> current_offsets[0] = rank * 2
2025-07-17T07:05:47.2029110Z         >>> shard_metadata = ShardMetadata(
2025-07-17T07:05:47.2029200Z                 shard_offsets=copy.deepcopy(current_offsets),
2025-07-17T07:05:47.2029270Z                 shard_sizes=tensor.size(),
2025-07-17T07:05:47.2029340Z                 placement=spec.placements[rank],
2025-07-17T07:05:47.2029380Z             )
2025-07-17T07:05:47.2029430Z         >>> local_shards = [
2025-07-17T07:05:47.2029480Z                 Shard(
2025-07-17T07:05:47.2029530Z                     tensor=tensor,
2025-07-17T07:05:47.2029590Z                     metadata=shard_metadata,
2025-07-17T07:05:47.2029630Z                 )
2025-07-17T07:05:47.2029670Z             ]
2025-07-17T07:05:47.2029810Z         >>> st = ShardedTensor._init_from_local_shards(local_shards, tensor.size())
2025-07-17T07:05:47.2029860Z         >>> sharding_dim = 1
2025-07-17T07:05:47.2029940Z         >>> resharding_spec = ChunkShardingSpec(
2025-07-17T07:05:47.2029990Z                 dim=sharding_dim,
2025-07-17T07:05:47.2030050Z                 placements=[
2025-07-17T07:05:47.2030100Z                     "rank:0/cuda:0",
2025-07-17T07:05:47.2030150Z                     "rank:1/cuda:1",
2025-07-17T07:05:47.2030240Z                     "rank:2/cuda:2",
2025-07-17T07:05:47.2030290Z                     "rank:3/cuda:3",
2025-07-17T07:05:47.2030330Z                 ],
2025-07-17T07:05:47.2030370Z             )
2025-07-17T07:05:47.2030430Z         >>> st.reshard(resharding_spec)
2025-07-17T07:05:47.2030520Z         >>> tensor = st.local_shards()[0].tensor
2025-07-17T07:05:47.2030570Z         >>> tensor
2025-07-17T07:05:47.2030660Z         tensor([[1], [1], [3], [3], [5], [5], [7], [7]]) # Rank 0
2025-07-17T07:05:47.2030740Z         tensor([[2], [2], [4], [4], [6], [6], [8], [8]]) # Rank 1
2025-07-17T07:05:47.2030820Z         tensor([[3], [3], [5], [5], [7], [7], [9], [9]]) # Rank 2
2025-07-17T07:05:47.2030910Z         tensor([[4], [4], [6], [6], [8], [8], [10], [10]]) # Rank 3
2025-07-17T07:05:47.2030950Z     
2025-07-17T07:05:47.2031100Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2031140Z     
2025-07-17T07:05:47.2031220Z       warnings.warn(msg)
2025-07-17T07:05:47.2031290Z     
2025-07-17T07:05:47.2031390Z --- Parse Warning: 85 / 136 ---
2025-07-17T07:05:47.2032090Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardingPlan in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/_shard/sharding_plan/api.py line=12.
2025-07-17T07:05:47.2032250Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2032290Z     
2025-07-17T07:05:47.2032420Z     Representation of a sharding plan, describes how to shard a module
2025-07-17T07:05:47.2032580Z     across hosts. `plan` is used to shard module parameters according to the spec provided,
2025-07-17T07:05:47.2032760Z     `output_plan` and `return_local_tensor` are optional, they are used to specify the output
2025-07-17T07:05:47.2032910Z     layout of a module with a spec, and when to convert back to data parallel fashion.
2025-07-17T07:05:47.2032950Z     
2025-07-17T07:05:47.2032990Z     Args:
2025-07-17T07:05:47.2033150Z         plan (Dict[str, Union[:class:`torch.distributed._shard.sharding_spec.ShardingSpec`,
2025-07-17T07:05:47.2033260Z               :class:`torch.distributed._shard.sharder.Sharder`]):
2025-07-17T07:05:47.2033430Z             a dict describes how to shard a module, there're currently two ways to shard a module:
2025-07-17T07:05:47.2033580Z                 1. directly shard a module parameter by a `ShardingSpec`, keyed by the name of
2025-07-17T07:05:47.2033650Z                    a parameter to a `ShardingSpec`.
2025-07-17T07:05:47.2033810Z                 2. shard a submodule by applying a `Sharder` on it, keyed by the name of a module
2025-07-17T07:05:47.2033870Z                    to a `Sharder` object.
2025-07-17T07:05:47.2034070Z         output_plan (Dict[str, :class:`torch.distributed._shard.sharding_spec.ShardingSpec`), optional):
2025-07-17T07:05:47.2034220Z             a dict specifies the layout of a module's output which produces a ShardedTensor,
2025-07-17T07:05:47.2034370Z             keyed by the name of module to ShardingSpec("" in key means the root module).
2025-07-17T07:05:47.2034420Z             Default: `None`
2025-07-17T07:05:47.2034570Z         return_local_tensor (List[str], optional): a list of string, each element enables
2025-07-17T07:05:47.2034720Z             a module's sharded output to be returned as a Tensor from its local shards to
2025-07-17T07:05:47.2034870Z             ensure further processing in a data parallel fashion. ("" in list means the
2025-07-17T07:05:47.2034920Z             root module).
2025-07-17T07:05:47.2034960Z             Default: None
2025-07-17T07:05:47.2035010Z     Example:
2025-07-17T07:05:47.2035180Z       Suppose we want to shard a module with two linear layers and then run it with DDP, we also
2025-07-17T07:05:47.2035340Z       want to convert the output of the second linear layer back to DDP, we can do it as follows:
2025-07-17T07:05:47.2035380Z     
2025-07-17T07:05:47.2035510Z         >>> # xdoctest: +REQUIRES(module:torch._C._distributed_c10d)
2025-07-17T07:05:47.2035580Z         >>> class MyModule(nn.Module):
2025-07-17T07:05:47.2035640Z         >>>     def __init__(self) -> None:
2025-07-17T07:05:47.2035720Z         >>>        super().__init__()
2025-07-17T07:05:47.2035780Z         >>>        self.fc1 = nn.Linear()
2025-07-17T07:05:47.2035830Z         >>>        self.gelu = nn.GELU()
2025-07-17T07:05:47.2035890Z         >>>        self.fc2 = nn.Linear()
2025-07-17T07:05:47.2035950Z         >>>        self.relu = nn.Linear()
2025-07-17T07:05:47.2035990Z         >>>
2025-07-17T07:05:47.2036050Z         >>>     def forward(self, input):
2025-07-17T07:05:47.2036150Z         >>>         return self.relu(self.fc2(self.gelu(self.fc1(input))))
2025-07-17T07:05:47.2036190Z     
2025-07-17T07:05:47.2036230Z     
2025-07-17T07:05:47.2036310Z         >>> # xdoctest: +SKIP("Undefined spec1, spec2)
2025-07-17T07:05:47.2036390Z         >>> sharding_plan = ShardingPlan(
2025-07-17T07:05:47.2036460Z         >>>    plan={
2025-07-17T07:05:47.2036520Z         >>>        "fc1.weight": spec1,
2025-07-17T07:05:47.2036580Z         >>>        "fc2.weight": spec2
2025-07-17T07:05:47.2036620Z         >>>    },
2025-07-17T07:05:47.2036670Z         >>>    output_plan={
2025-07-17T07:05:47.2036730Z         >>>        "fc2": output_spec
2025-07-17T07:05:47.2036770Z         >>>    },
2025-07-17T07:05:47.2036830Z         >>>    return_local_tensor=["fc2"]
2025-07-17T07:05:47.2036870Z         >>> )
2025-07-17T07:05:47.2036910Z     
2025-07-17T07:05:47.2037060Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2037100Z     
2025-07-17T07:05:47.2037150Z       warnings.warn(msg)
2025-07-17T07:05:47.2037190Z     
2025-07-17T07:05:47.2037290Z --- Parse Warning: 86 / 136 ---
2025-07-17T07:05:47.2038040Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_sharding in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/tensor/experimental/_register_sharding.py line=25.
2025-07-17T07:05:47.2038200Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2038240Z     
2025-07-17T07:05:47.2038410Z     :meth:`register_sharding` is an experimental API that allows users to register sharding
2025-07-17T07:05:47.2038560Z     strategies for an operator when the tensor inputs and outputs are DTensor.
2025-07-17T07:05:47.2038710Z     It can be useful when: (1) there doesn't exist a default sharding strategy for ``op``,
2025-07-17T07:05:47.2038860Z     e.g. when ``op`` is a custom operator that is not supported by :class:`DTensor`; (2)
2025-07-17T07:05:47.2039020Z     when users would like to overwrite default sharding strategies of existing operators.
2025-07-17T07:05:47.2039060Z     
2025-07-17T07:05:47.2039100Z     Args:
2025-07-17T07:05:47.2039180Z         op (Union[OpOverload, List[OpOverload]]):
2025-07-17T07:05:47.2039300Z             An op or a list of ops to register the customized sharding function.
2025-07-17T07:05:47.2039340Z     
2025-07-17T07:05:47.2039380Z     Returns:
2025-07-17T07:05:47.2039540Z         A function decorator which can be used to wrap a function that defines the sharding
2025-07-17T07:05:47.2039710Z         strategy for the operator specified in ``op``. The defined sharding strategy will be
2025-07-17T07:05:47.2039870Z         registered to DTensor and will override the default sharding strategy if DTensor has
2025-07-17T07:05:47.2040050Z         already implemented the operator. The customized sharding function takes the same inputs
2025-07-17T07:05:47.2040190Z         as the original op (except that if an arg is a :class:`torch.Tensor`, it will be
2025-07-17T07:05:47.2040350Z         replaced by a tensor-like object that DTensor uses internally). The function should
2025-07-17T07:05:47.2040550Z         return a sequence of 2-tuples, each specifying acceptable output placements and its
2025-07-17T07:05:47.2040620Z         corresponding intput placements.
2025-07-17T07:05:47.2040660Z     
2025-07-17T07:05:47.2040700Z     Example:
2025-07-17T07:05:47.2040780Z         >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:47.2040870Z         >>> @register_sharding(aten._softmax.default)
2025-07-17T07:05:47.2040960Z         >>> def custom_softmax_sharding(x, dim, half_to_float):
2025-07-17T07:05:47.2041050Z         >>>     softmax_dim = dim if dim >= 0 else dim + x.ndim
2025-07-17T07:05:47.2044490Z         >>>     acceptable_shardings = []
2025-07-17T07:05:47.2044540Z         >>>
2025-07-17T07:05:47.2044660Z         >>>     all_replicate = ([Replicate()], [Replicate(), None, None])
2025-07-17T07:05:47.2044740Z         >>>     acceptable_shardings.append(all_replicate)
2025-07-17T07:05:47.2044790Z         >>>
2025-07-17T07:05:47.2044960Z         >>>     for sharding_dim in range(x.ndim):
2025-07-17T07:05:47.2045050Z         >>>         if sharding_dim != softmax_dim:
2025-07-17T07:05:47.2045110Z         >>>             all_sharded = (
2025-07-17T07:05:47.2045170Z         >>>                 [Shard(sharding_dim)],
2025-07-17T07:05:47.2045250Z         >>>                 [Shard(sharding_dim), None, None],
2025-07-17T07:05:47.2045300Z         >>>             )
2025-07-17T07:05:47.2045380Z         >>>             acceptable_shardings.append(all_sharded)
2025-07-17T07:05:47.2045430Z         >>>
2025-07-17T07:05:47.2045490Z         >>>     return acceptable_shardings
2025-07-17T07:05:47.2045530Z     
2025-07-17T07:05:47.2045650Z     .. note:: This API is currently experimental and subject to change
2025-07-17T07:05:47.2045690Z     
2025-07-17T07:05:47.2045840Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2045880Z     
2025-07-17T07:05:47.2045930Z       warnings.warn(msg)
2025-07-17T07:05:47.2045970Z     
2025-07-17T07:05:47.2046090Z --- Parse Warning: 87 / 136 ---
2025-07-17T07:05:47.2046800Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=local_map in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/tensor/experimental/_func_map.py line=35.
2025-07-17T07:05:47.2046960Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2047000Z     
2025-07-17T07:05:47.2047160Z     :meth:`local_map` is an experimental API that allows users to pass :class:`DTensor` s
2025-07-17T07:05:47.2047330Z     to a function that is written to be applied on ``torch.Tensor`` s. It is done by extracting
2025-07-17T07:05:47.2047490Z     the local components of :class:`DTensor`, call the function, and wrap the outputs to
2025-07-17T07:05:47.2047580Z     :class:`DTensor` according to the ``out_placements``.
2025-07-17T07:05:47.2047630Z     
2025-07-17T07:05:47.2047670Z     Args:
2025-07-17T07:05:47.2047800Z         func (Callable): the function to be applied on each local shard of
2025-07-17T07:05:47.2047850Z             :class:`DTensor` s.
2025-07-17T07:05:47.2047990Z         out_placements (Union[`PlacementType`, Tuple[`PlacementType`, ...]]):
2025-07-17T07:05:47.2048140Z             the desired placements of the :class:`DTensor` s in ``func``'s flattened output.
2025-07-17T07:05:47.2048290Z             If the flattened ``output`` is a single value, the ``out_placements`` should be
2025-07-17T07:05:47.2048430Z             of type `PlacementType`. Otherwise if the flattened ``output`` has multiple
2025-07-17T07:05:47.2048590Z             values, the ``out_placements`` should be a tuple of `PlacementType` values 1:1
2025-07-17T07:05:47.2048660Z             mapping to the flattened ``output``.
2025-07-17T07:05:47.2048780Z             Besides, for :class:`Tensor` output, we use `PlacementType` as its
2025-07-17T07:05:47.2049000Z             placements (a `Tuple[Placement]` value). For non-Tensor output, the `PlacementType`
2025-07-17T07:05:47.2049060Z             should be `None`.
2025-07-17T07:05:47.2049200Z             Note that the only exception is when no :class:`DTensor` argument is passed
2025-07-17T07:05:47.2049370Z             in. In this case, even if `out_placements` is not `None`, the result function
2025-07-17T07:05:47.2049520Z             should ignore the desired placements because the function is not running with
2025-07-17T07:05:47.2049570Z             :class:`DTensor` s.
2025-07-17T07:05:47.2049670Z         in_placements (Tuple[`PlacementType`, ...], optional):
2025-07-17T07:05:47.2049840Z             the required placements of the :class:`DTensor` s in the flattened inputs of ``func``.
2025-07-17T07:05:47.2049980Z             If ``in_placements`` is specified, :meth:`local_map` would examine whether the
2025-07-17T07:05:47.2050130Z             placements of each :class:`DTensor` argument is the same as the required
2025-07-17T07:05:47.2050260Z             placements or not. If the placements are not the same and
2025-07-17T07:05:47.2050410Z             ``redistribute_inputs`` is ``False``, an exception will be raised. Otherwise if
2025-07-17T07:05:47.2050560Z             ``redistribute_inputs`` is ``True``, the argument will be first redistributed to
2025-07-17T07:05:47.2050710Z             the required sharding placements before passing its local tensor to ``func``.
2025-07-17T07:05:47.2050850Z             The only exception is when required placements are not ``None`` and the
2025-07-17T07:05:47.2050990Z             argument is a :class:`torch.Tensor`. In this case, the placements examination
2025-07-17T07:05:47.2051120Z             will be skipped and the argument will be directly passed to ``func``.
2025-07-17T07:05:47.2051260Z             If ``in_placements`` is ``None``, no placements examination will be performed.
2025-07-17T07:05:47.2051310Z             Default: None
2025-07-17T07:05:47.2051420Z         in_grad_placements (Tuple[`PlacementType`, ...], optional):
2025-07-17T07:05:47.2051550Z             the placements hint of the :class:`DTensor` s gradient corresponds
2025-07-17T07:05:47.2051680Z             to the flattened input DTensor. This argument is the hint that user
2025-07-17T07:05:47.2051790Z             can give to :meth:`to_local` in case the gradient layout of the
2025-07-17T07:05:47.2051920Z             local tensor input does not match its :class:`DTensor` input layout.
2025-07-17T07:05:47.2052040Z             If not specified, we will assume the gradient layout of the local
2025-07-17T07:05:47.2052170Z             tensor input remains the same as the original :class:`DTensor` input
2025-07-17T07:05:47.2052270Z             and use that for gradient computation. Default: None.
2025-07-17T07:05:47.2052360Z         device_mesh (:class:`DeviceMesh`, optional):
2025-07-17T07:05:47.2052490Z             the device mesh that the output :class:`DTensor` s are placed on. If not
2025-07-17T07:05:47.2052640Z             specified, this will be inferred from the first input :class:`DTensor`'s device
2025-07-17T07:05:47.2052700Z             mesh. Default: None.
2025-07-17T07:05:47.2052740Z     
2025-07-17T07:05:47.2052790Z     Keyword Args:
2025-07-17T07:05:47.2052860Z         redistribute_inputs (bool, optional):
2025-07-17T07:05:47.2053010Z             the bool value indicating whether to reshard the input :class:`DTensor` s when
2025-07-17T07:05:47.2053160Z             their placements are different from the required input placements. If this
2025-07-17T07:05:47.2053300Z             value is ``False`` and some :class:`DTensor` input has a different placement,
2025-07-17T07:05:47.2053380Z             an exception will be raised. Default: False.
2025-07-17T07:05:47.2053420Z     
2025-07-17T07:05:47.2053460Z     Returns:
2025-07-17T07:05:47.2053610Z         A ``Callable`` that applies ``func`` to each local shard of the input :class:`DTensor`
2025-07-17T07:05:47.2053760Z         and returns a :class:`DTensor` constructed from the return value of ``func``.
2025-07-17T07:05:47.2053800Z     
2025-07-17T07:05:47.2053860Z     Raises:
2025-07-17T07:05:47.2054010Z         AssertionError: For any non-DTensor output, we require its corresponding
2025-07-17T07:05:47.2054170Z             output placement in ``out_placements`` be None. An AssertionError will be raised
2025-07-17T07:05:47.2054250Z             if this is not the case.
2025-07-17T07:05:47.2054290Z     
2025-07-17T07:05:47.2054440Z         ValueError: If ``redistribute_inputs=False`` but the input :class:`DTensor` needs
2025-07-17T07:05:47.2054530Z             a redistribution according to ``in_placements``.
2025-07-17T07:05:47.2054570Z     
2025-07-17T07:05:47.2054620Z     Example:
2025-07-17T07:05:47.2054680Z         >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:47.2054770Z         >>> def mm_allreduce_forward(device_mesh, W, X):
2025-07-17T07:05:47.2054840Z         >>>     partial_sum_tensor = torch.mm(W, X)
2025-07-17T07:05:47.2055020Z         >>>     reduced_tensor = funcol.all_reduce(partial_sum_tensor, "sum", device_mesh)
2025-07-17T07:05:47.2055110Z         >>>     return reduced_tensor
2025-07-17T07:05:47.2055150Z         >>>
2025-07-17T07:05:47.2055230Z         >>> W = torch.randn(12, 8, requires_grad=False)
2025-07-17T07:05:47.2055310Z         >>> X = torch.randn(8, 16, requires_grad=False)
2025-07-17T07:05:47.2055360Z         >>> Y = torch.mm(W, X)
2025-07-17T07:05:47.2055480Z         >>> row_wise = [Shard(0)]  # row-wise sharding placements on 1-d mesh
2025-07-17T07:05:47.2055590Z         >>> col_wise = [Shard(1)]  # col-wise sharding placements on 1-d mesh
2025-07-17T07:05:47.2055630Z         >>>
2025-07-17T07:05:47.2055790Z         >>> # local_mm_allreduce_forward is the function wrapped with DTensor/Tensor convertion
2025-07-17T07:05:47.2055870Z         >>> local_mm_allreduce_forward = local_map(
2025-07-17T07:05:47.2055920Z         >>>     mm_allreduce_forward,
2025-07-17T07:05:47.2055990Z         >>>     out_placements=[Replicate()],
2025-07-17T07:05:47.2056060Z         >>>     in_placements=[col_wise, row_wise],
2025-07-17T07:05:47.2056120Z         >>>     device_mesh=device_mesh,
2025-07-17T07:05:47.2056170Z         >>> )
2025-07-17T07:05:47.2056210Z         >>>
2025-07-17T07:05:47.2056260Z         >>> W_dt = distribute_tensor(
2025-07-17T07:05:47.2056330Z         ...     W, device_mesh, (col_wise)
2025-07-17T07:05:47.2056390Z         ... )  # col-wisely sharded W tensor
2025-07-17T07:05:47.2056450Z         >>> X_dt = distribute_tensor(
2025-07-17T07:05:47.2056510Z         ...     X, device_mesh, (row_wise)
2025-07-17T07:05:47.2056570Z         ... )  # row-wisely sharded X tensor
2025-07-17T07:05:47.2056640Z         >>> Y_dt = local_mm_allreduce_forward(
2025-07-17T07:05:47.2056690Z         ...     device_mesh, W_dt, X_dt
2025-07-17T07:05:47.2056780Z         ... )  # apply local_mm_allreduce_forward to DTensors
2025-07-17T07:05:47.2056820Z     
2025-07-17T07:05:47.2056940Z     .. note:: This API is currently experimental and subject to change
2025-07-17T07:05:47.2056980Z     
2025-07-17T07:05:47.2057140Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2057180Z     
2025-07-17T07:05:47.2057230Z       warnings.warn(msg)
2025-07-17T07:05:47.2057270Z     
2025-07-17T07:05:47.2057370Z --- Parse Warning: 88 / 136 ---
2025-07-17T07:05:47.2058100Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleInput in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py line=428.
2025-07-17T07:05:47.2058250Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2058290Z     
2025-07-17T07:05:47.2058530Z     Configure the nn.Module's inputs to convert the input tensors of the nn.Module to DTensors at runtime according to
2025-07-17T07:05:47.2058720Z     ``input_layouts``, and perform layout redistribution according to the ``desired_input_layouts``.
2025-07-17T07:05:47.2058780Z     
2025-07-17T07:05:47.2058830Z     Keyword Args:
2025-07-17T07:05:47.2058950Z         input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-07-17T07:05:47.2059200Z             The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to
2025-07-17T07:05:47.2059410Z             DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified
2025-07-17T07:05:47.2059480Z             as a placeholder. default: None.
2025-07-17T07:05:47.2059620Z         desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-07-17T07:05:47.2059840Z             The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-07-17T07:05:47.2060090Z             have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None.
2025-07-17T07:05:47.2060190Z         input_kwarg_layouts (Dict[str, Placement]):
2025-07-17T07:05:47.2060410Z             The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors.
2025-07-17T07:05:47.2060470Z             default: None
2025-07-17T07:05:47.2060570Z         desired_input_kwarg_layouts: (Dict[str, Placement]):
2025-07-17T07:05:47.2060780Z             The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-07-17T07:05:47.2060870Z             have the desired DTensor layouts. default: None.
2025-07-17T07:05:47.2060940Z         use_local_output (bool, optional):
2025-07-17T07:05:47.2061150Z             Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False.
2025-07-17T07:05:47.2061190Z     Returns:
2025-07-17T07:05:47.2061390Z         A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs.
2025-07-17T07:05:47.2061430Z     
2025-07-17T07:05:47.2061480Z     Example::
2025-07-17T07:05:47.2061540Z         >>> # xdoctest: +SKIP(failing)
2025-07-17T07:05:47.2061720Z         >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInput
2025-07-17T07:05:47.2061840Z         >>> from torch.distributed.device_mesh import init_device_mesh
2025-07-17T07:05:47.2061890Z         >>> ...
2025-07-17T07:05:47.2062070Z         >>> block = TransformerBlock(...)  # block is a nn.Module that contains an "attn" Attention submodule
2025-07-17T07:05:47.2062150Z         >>> tp_mesh = init_device_mesh("cuda", (8,))
2025-07-17T07:05:47.2062190Z         >>>
2025-07-17T07:05:47.2062390Z         >>> # According to the style specified below, the first input of attn will be annotated to Sharded DTensor
2025-07-17T07:05:47.2062480Z         >>> # and then redistributed to Replicated DTensor.
2025-07-17T07:05:47.2062530Z         >>> parallelize_module(
2025-07-17T07:05:47.2062610Z         >>>     block, # this can be a submodule or module
2025-07-17T07:05:47.2062660Z         >>>     tp_mesh,
2025-07-17T07:05:47.2062720Z         >>>     parallelize_plan={
2025-07-17T07:05:47.2062790Z         >>>         "attn": PrepareModuleInput(
2025-07-17T07:05:47.2062880Z         >>>             input_layouts=(Shard(0), None, None, ...),
2025-07-17T07:05:47.2062980Z         >>>             desired_input_layouts=(Replicate(), None, None, ...)
2025-07-17T07:05:47.2063030Z         >>>         ),
2025-07-17T07:05:47.2063070Z         >>>     }
2025-07-17T07:05:47.2063110Z         >>> )
2025-07-17T07:05:47.2063150Z     
2025-07-17T07:05:47.2063300Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2063340Z     
2025-07-17T07:05:47.2063390Z       warnings.warn(msg)
2025-07-17T07:05:47.2063430Z     
2025-07-17T07:05:47.2063530Z --- Parse Warning: 89 / 136 ---
2025-07-17T07:05:47.2064310Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleOutput in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py line=597.
2025-07-17T07:05:47.2064490Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2064530Z     
2025-07-17T07:05:47.2064760Z     Configure the nn.Module's outputs to convert the output tensors of the nn.Module to DTensors at runtime according to
2025-07-17T07:05:47.2064950Z     ``output_layouts``, and perform layout redistribution according to the ``desired_output_layouts``.
2025-07-17T07:05:47.2064990Z     
2025-07-17T07:05:47.2065040Z     Keyword Args:
2025-07-17T07:05:47.2065140Z         output_layouts (Union[Placement, Tuple[Placement]]):
2025-07-17T07:05:47.2065340Z             The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to
2025-07-17T07:05:47.2065580Z             DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors,
2025-07-17T07:05:47.2065690Z             ``None`` need to be specified as a placeholder.
2025-07-17T07:05:47.2065810Z         desired_output_layouts (Union[Placement, Tuple[Placement]]):
2025-07-17T07:05:47.2066040Z             The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module
2025-07-17T07:05:47.2066110Z             have the desired DTensor layouts.
2025-07-17T07:05:47.2066180Z         use_local_output (bool, optional):
2025-07-17T07:05:47.2066390Z             Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True.
2025-07-17T07:05:47.2066440Z     Returns:
2025-07-17T07:05:47.2066610Z         A ParallelStyle object that prepares the sharding layouts of the nn.Module's outputs.
2025-07-17T07:05:47.2066650Z     
2025-07-17T07:05:47.2066690Z     Example::
2025-07-17T07:05:47.2066750Z         >>> # xdoctest: +SKIP(failing)
2025-07-17T07:05:47.2066940Z         >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleOutput
2025-07-17T07:05:47.2067060Z         >>> from torch.distributed.device_mesh import init_device_mesh
2025-07-17T07:05:47.2067110Z         >>> ...
2025-07-17T07:05:47.2067290Z         >>> block = TransformerBlock(...)  # block is a nn.Module that contains an "attn" Attention submodule
2025-07-17T07:05:47.2067370Z         >>> tp_mesh = init_device_mesh("cuda", (8,))
2025-07-17T07:05:47.2067410Z         >>>
2025-07-17T07:05:47.2067640Z         >>> # According to the style specified below, the output of the TransformerBlock will be converted to Replicated DTensor
2025-07-17T07:05:47.2067720Z         >>> # and then redistributed to Sharded DTensor.
2025-07-17T07:05:47.2067780Z         >>> parallelize_module(
2025-07-17T07:05:47.2067860Z         >>>     block, # this can be a submodule or module
2025-07-17T07:05:47.2067910Z         >>>     tp_mesh,
2025-07-17T07:05:47.2068000Z         >>>     parallelize_plan = PrepareModuleOutput(
2025-07-17T07:05:47.2068060Z         >>>         output_layouts=Replicate(),
2025-07-17T07:05:47.2068130Z         >>>         desired_output_layouts=Shard(0)
2025-07-17T07:05:47.2068180Z         >>>     )
2025-07-17T07:05:47.2068220Z         >>> )
2025-07-17T07:05:47.2068260Z     
2025-07-17T07:05:47.2068410Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2068450Z     
2025-07-17T07:05:47.2068500Z       warnings.warn(msg)
2025-07-17T07:05:47.2068540Z     
2025-07-17T07:05:47.2068640Z --- Parse Warning: 90 / 136 ---
2025-07-17T07:05:47.2069380Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleInputOutput in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/tensor/parallel/style.py line=705.
2025-07-17T07:05:47.2069550Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2069600Z     
2025-07-17T07:05:47.2069860Z     Configure the nn.Module's inputs (and outputs) to convert the input tensors (and output tensors, respectively) of the nn.Module
2025-07-17T07:05:47.2070130Z     to DTensors at runtime according to ``input_layouts`` (and output_layouts, respectively), and perform layout redistribution
2025-07-17T07:05:47.2070360Z     according to the ``desired_input_layouts`` (and ``desired_output_layouts``, respectively). This is a combination of
2025-07-17T07:05:47.2070490Z     :class:`PrepareModuleInput` and :class:`PrepareModuleOutput`.
2025-07-17T07:05:47.2070530Z     
2025-07-17T07:05:47.2070570Z     Keyword Args:
2025-07-17T07:05:47.2070690Z         input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-07-17T07:05:47.2070900Z             The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to
2025-07-17T07:05:47.2071130Z             DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified
2025-07-17T07:05:47.2071200Z             as a placeholder. default: None.
2025-07-17T07:05:47.2071340Z         desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]):
2025-07-17T07:05:47.2071560Z             The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-07-17T07:05:47.2071790Z             have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None.
2025-07-17T07:05:47.2071870Z         input_kwarg_layouts (Dict[str, Placement]):
2025-07-17T07:05:47.2072090Z             The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors.
2025-07-17T07:05:47.2072140Z             default: None
2025-07-17T07:05:47.2072240Z         desired_input_kwarg_layouts: (Dict[str, Placement]):
2025-07-17T07:05:47.2072460Z             The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module
2025-07-17T07:05:47.2072550Z             have the desired DTensor layouts. default: None.
2025-07-17T07:05:47.2072620Z         use_local_input (bool, optional):
2025-07-17T07:05:47.2072830Z             Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False.
2025-07-17T07:05:47.2072930Z         output_layouts (Union[Placement, Tuple[Placement]]):
2025-07-17T07:05:47.2073130Z             The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to
2025-07-17T07:05:47.2073350Z             DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors,
2025-07-17T07:05:47.2073440Z             ``None`` need to be specified as a placeholder.
2025-07-17T07:05:47.2073560Z         desired_output_layouts (Union[Placement, Tuple[Placement]]):
2025-07-17T07:05:47.2073780Z             The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module
2025-07-17T07:05:47.2073850Z             have the desired DTensor layouts.
2025-07-17T07:05:47.2073920Z         use_local_output (bool, optional):
2025-07-17T07:05:47.2074130Z             Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True.
2025-07-17T07:05:47.2074170Z     Returns:
2025-07-17T07:05:47.2074390Z         A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs and outputs.
2025-07-17T07:05:47.2074430Z     
2025-07-17T07:05:47.2074480Z     Example::
2025-07-17T07:05:47.2074530Z         >>> # xdoctest: +SKIP(failing)
2025-07-17T07:05:47.2074740Z         >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInputOutput
2025-07-17T07:05:47.2074850Z         >>> from torch.distributed.device_mesh import init_device_mesh
2025-07-17T07:05:47.2074920Z         >>> ...
2025-07-17T07:05:47.2075100Z         >>> block = TransformerBlock(...)  # block is a nn.Module that contains an "attn" Attention submodule
2025-07-17T07:05:47.2075180Z         >>> tp_mesh = init_device_mesh("cuda", (8,))
2025-07-17T07:05:47.2075250Z         >>>
2025-07-17T07:05:47.2075450Z         >>> # According to the style specified below, the first input of attn will be annotated as Sharded DTensor
2025-07-17T07:05:47.2075660Z         >>> # and then redistributed to Replicated DTensor, and the output of the TransformerBlock will be annotated
2025-07-17T07:05:47.2075780Z         >>> # as Replicated DTensor and then redistributed to Sharded DTensor.
2025-07-17T07:05:47.2075840Z         >>> parallelize_module(
2025-07-17T07:05:47.2075920Z         >>>     block, # this can be a submodule or module
2025-07-17T07:05:47.2075970Z         >>>     tp_mesh,
2025-07-17T07:05:47.2076030Z         >>>     parallelize_plan={
2025-07-17T07:05:47.2076140Z         >>>         "attn": PrepareModuleInputOutput(
2025-07-17T07:05:47.2076250Z         >>>             input_layouts=(Shard(0), None, None, ...),
2025-07-17T07:05:47.2076360Z         >>>             desired_input_layouts=(Replicate(), None, None, ...),
2025-07-17T07:05:47.2076430Z         >>>             output_layouts=Replicate(),
2025-07-17T07:05:47.2076510Z         >>>             desired_output_layouts=Shard(0),
2025-07-17T07:05:47.2076550Z         >>>         ),
2025-07-17T07:05:47.2076590Z         >>>     }
2025-07-17T07:05:47.2076630Z         >>> )
2025-07-17T07:05:47.2076670Z     
2025-07-17T07:05:47.2076830Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2076870Z     
2025-07-17T07:05:47.2076920Z       warnings.warn(msg)
2025-07-17T07:05:47.2076960Z     
2025-07-17T07:05:47.2077060Z --- Parse Warning: 91 / 136 ---
2025-07-17T07:05:47.2077730Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=async_execution in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/rpc/functions.py line=6.
2025-07-17T07:05:47.2077890Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2077930Z     
2025-07-17T07:05:47.2078080Z     A decorator for a function indicating that the return value of the function
2025-07-17T07:05:47.2078200Z     is guaranteed to be a :class:`~torch.futures.Future` object and this
2025-07-17T07:05:47.2078350Z     function can run asynchronously on the RPC callee. More specifically, the
2025-07-17T07:05:47.2078490Z     callee extracts the :class:`~torch.futures.Future` returned by the wrapped
2025-07-17T07:05:47.2078630Z     function and installs subsequent processing steps as a callback to that
2025-07-17T07:05:47.2078770Z     :class:`~torch.futures.Future`. The installed callback will read the value
2025-07-17T07:05:47.2078900Z     from the :class:`~torch.futures.Future` when completed and send the
2025-07-17T07:05:47.2079000Z     value back as the RPC response. That also means the returned
2025-07-17T07:05:47.2079140Z     :class:`~torch.futures.Future` only exists on the callee side and is never
2025-07-17T07:05:47.2079280Z     sent through RPC. This decorator is useful when the wrapped function's
2025-07-17T07:05:47.2079400Z     (``fn``) execution needs to pause and resume due to, e.g., containing
2025-07-17T07:05:47.2079530Z     :meth:`~torch.distributed.rpc.rpc_async` or waiting for other signals.
2025-07-17T07:05:47.2079570Z     
2025-07-17T07:05:47.2079700Z     .. note:: To enable asynchronous execution, applications must pass the
2025-07-17T07:05:47.2079840Z         function object returned by this decorator to RPC APIs. If RPC detected
2025-07-17T07:05:47.2079970Z         attributes installed by this decorator, it knows that this function
2025-07-17T07:05:47.2080080Z         returns a ``Future`` object and will handle that accordingly.
2025-07-17T07:05:47.2080260Z         However, this does not mean this decorator has to be outmost one when
2025-07-17T07:05:47.2080390Z         defining a function. For example, when combined with ``@staticmethod``
2025-07-17T07:05:47.2080540Z         or ``@classmethod``, ``@rpc.functions.async_execution`` needs to be the
2025-07-17T07:05:47.2080680Z         inner decorator to allow the target function be recognized as a static
2025-07-17T07:05:47.2080810Z         or class function. This target function can still execute asynchronously
2025-07-17T07:05:47.2080940Z         because, when accessed, the static or class method preserves attributes
2025-07-17T07:05:47.2081040Z         installed by ``@rpc.functions.async_execution``.
2025-07-17T07:05:47.2081080Z     
2025-07-17T07:05:47.2081120Z     
2025-07-17T07:05:47.2081160Z     Example::
2025-07-17T07:05:47.2081280Z         The returned :class:`~torch.futures.Future` object can come from
2025-07-17T07:05:47.2081380Z         :meth:`~torch.distributed.rpc.rpc_async`,
2025-07-17T07:05:47.2081540Z         :meth:`~torch.futures.Future.then`, or :class:`~torch.futures.Future`
2025-07-17T07:05:47.2081640Z         constructor. The example below shows directly using the
2025-07-17T07:05:47.2081720Z         :class:`~torch.futures.Future` returned by
2025-07-17T07:05:47.2081790Z         :meth:`~torch.futures.Future.then`.
2025-07-17T07:05:47.2081830Z     
2025-07-17T07:05:47.2081900Z         >>> from torch.distributed import rpc
2025-07-17T07:05:47.2081940Z         >>>
2025-07-17T07:05:47.2082010Z         >>> # omitting setup and shutdown RPC
2025-07-17T07:05:47.2082050Z         >>>
2025-07-17T07:05:47.2082100Z         >>> # On all workers
2025-07-17T07:05:47.2082170Z         >>> @rpc.functions.async_execution
2025-07-17T07:05:47.2082230Z         >>> def async_add_chained(to, x, y, z):
2025-07-17T07:05:47.2082350Z         >>>     # This function runs on "worker1" and returns immediately when
2025-07-17T07:05:47.2082460Z         >>>     # the callback is installed through the `then(cb)` API. In the
2025-07-17T07:05:47.2082580Z         >>>     # mean time, the `rpc_async` to "worker2" can run concurrently.
2025-07-17T07:05:47.2082680Z         >>>     # When the return value of that `rpc_async` arrives at
2025-07-17T07:05:47.2082850Z         >>>     # "worker1", "worker1" will run the lambda function accordingly
2025-07-17T07:05:47.2082970Z         >>>     # and set the value for the previously returned `Future`, which
2025-07-17T07:05:47.2083080Z         >>>     # will then trigger RPC to send the result back to "worker0".
2025-07-17T07:05:47.2083180Z         >>>     return rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-07-17T07:05:47.2083240Z         >>>         lambda fut: fut.wait() + z
2025-07-17T07:05:47.2083280Z         >>>     )
2025-07-17T07:05:47.2083330Z         >>>
2025-07-17T07:05:47.2083370Z         >>> # On worker0
2025-07-17T07:05:47.2083430Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2083480Z         >>> ret = rpc.rpc_sync(
2025-07-17T07:05:47.2083530Z         >>>     "worker1",
2025-07-17T07:05:47.2083590Z         >>>     async_add_chained,
2025-07-17T07:05:47.2083660Z         >>>     args=("worker2", torch.ones(2), 1, 1)
2025-07-17T07:05:47.2083700Z         >>> )
2025-07-17T07:05:47.2083770Z         >>> print(ret)  # prints tensor([3., 3.])
2025-07-17T07:05:47.2083810Z     
2025-07-17T07:05:47.2083950Z         When combined with TorchScript decorators, this decorator must be the
2025-07-17T07:05:47.2083990Z         outmost one.
2025-07-17T07:05:47.2084030Z     
2025-07-17T07:05:47.2084090Z         >>> from torch import Tensor
2025-07-17T07:05:47.2084150Z         >>> from torch.futures import Future
2025-07-17T07:05:47.2084230Z         >>> from torch.distributed import rpc
2025-07-17T07:05:47.2084270Z         >>>
2025-07-17T07:05:47.2084330Z         >>> # omitting setup and shutdown RPC
2025-07-17T07:05:47.2084370Z         >>>
2025-07-17T07:05:47.2084420Z         >>> # On all workers
2025-07-17T07:05:47.2084470Z         >>> @torch.jit.script
2025-07-17T07:05:47.2084610Z         >>> def script_add(x: Tensor, y: Tensor) -> Tensor:
2025-07-17T07:05:47.2084660Z         >>>     return x + y
2025-07-17T07:05:47.2084700Z         >>>
2025-07-17T07:05:47.2084770Z         >>> @rpc.functions.async_execution
2025-07-17T07:05:47.2084840Z         >>> @torch.jit.script
2025-07-17T07:05:47.2084950Z         >>> def async_add(to: str, x: Tensor, y: Tensor) -> Future[Tensor]:
2025-07-17T07:05:47.2085040Z         >>>     return rpc.rpc_async(to, script_add, (x, y))
2025-07-17T07:05:47.2085080Z         >>>
2025-07-17T07:05:47.2085130Z         >>> # On worker0
2025-07-17T07:05:47.2085180Z         >>> ret = rpc.rpc_sync(
2025-07-17T07:05:47.2085230Z         >>>     "worker1",
2025-07-17T07:05:47.2085270Z         >>>     async_add,
2025-07-17T07:05:47.2085340Z         >>>     args=("worker2", torch.ones(2), 1)
2025-07-17T07:05:47.2085380Z         >>> )
2025-07-17T07:05:47.2085450Z         >>> print(ret)  # prints tensor([2., 2.])
2025-07-17T07:05:47.2085510Z     
2025-07-17T07:05:47.2085660Z         When combined with static or class method, this decorator must be the
2025-07-17T07:05:47.2085710Z         inner one.
2025-07-17T07:05:47.2085750Z     
2025-07-17T07:05:47.2085820Z         >>> from torch.distributed import rpc
2025-07-17T07:05:47.2085860Z         >>>
2025-07-17T07:05:47.2085930Z         >>> # omitting setup and shutdown RPC
2025-07-17T07:05:47.2085970Z         >>>
2025-07-17T07:05:47.2086010Z         >>> # On all workers
2025-07-17T07:05:47.2086080Z         >>> class AsyncExecutionClass:
2025-07-17T07:05:47.2086120Z         >>>
2025-07-17T07:05:47.2086170Z         >>>     @staticmethod
2025-07-17T07:05:47.2086240Z         >>>     @rpc.functions.async_execution
2025-07-17T07:05:47.2086300Z         >>>     def static_async_add(to, x, y, z):
2025-07-17T07:05:47.2086410Z         >>>         return rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-07-17T07:05:47.2086470Z         >>>             lambda fut: fut.wait() + z
2025-07-17T07:05:47.2086520Z         >>>         )
2025-07-17T07:05:47.2086560Z         >>>
2025-07-17T07:05:47.2086610Z         >>>     @classmethod
2025-07-17T07:05:47.2086680Z         >>>     @rpc.functions.async_execution
2025-07-17T07:05:47.2086750Z         >>>     def class_async_add(cls, to, x, y, z):
2025-07-17T07:05:47.2086830Z         >>>         ret_fut = torch.futures.Future()
2025-07-17T07:05:47.2086920Z         >>>         rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-07-17T07:05:47.2087010Z         >>>             lambda fut: ret_fut.set_result(fut.wait() + z)
2025-07-17T07:05:47.2087050Z         >>>         )
2025-07-17T07:05:47.2087110Z         >>>         return ret_fut
2025-07-17T07:05:47.2087150Z         >>>
2025-07-17T07:05:47.2087220Z         >>>     @rpc.functions.async_execution
2025-07-17T07:05:47.2087290Z         >>>     def bound_async_add(self, to, x, y, z):
2025-07-17T07:05:47.2087390Z         >>>         return rpc.rpc_async(to, torch.add, args=(x, y)).then(
2025-07-17T07:05:47.2087460Z         >>>             lambda fut: fut.wait() + z
2025-07-17T07:05:47.2087510Z         >>>         )
2025-07-17T07:05:47.2087550Z         >>>
2025-07-17T07:05:47.2087590Z         >>> # On worker0
2025-07-17T07:05:47.2087650Z         >>> ret = rpc.rpc_sync(
2025-07-17T07:05:47.2087690Z         >>>     "worker1",
2025-07-17T07:05:47.2087770Z         >>>     AsyncExecutionClass.static_async_add,
2025-07-17T07:05:47.2087840Z         >>>     args=("worker2", torch.ones(2), 1, 2)
2025-07-17T07:05:47.2087890Z         >>> )
2025-07-17T07:05:47.2087950Z         >>> print(ret)  # prints tensor([4., 4.])
2025-07-17T07:05:47.2087990Z         >>>
2025-07-17T07:05:47.2088050Z         >>> ret = rpc.rpc_sync(
2025-07-17T07:05:47.2088090Z         >>>     "worker1",
2025-07-17T07:05:47.2088170Z         >>>     AsyncExecutionClass.class_async_add,
2025-07-17T07:05:47.2088240Z         >>>     args=("worker2", torch.ones(2), 1, 2)
2025-07-17T07:05:47.2088280Z         >>> )
2025-07-17T07:05:47.2088350Z         >>> print(ret)  # prints tensor([4., 4.])
2025-07-17T07:05:47.2088390Z     
2025-07-17T07:05:47.2088510Z         This decorator also works with RRef helpers, i.e., .
2025-07-17T07:05:47.2088600Z         :meth:`torch.distributed.rpc.RRef.rpc_sync`,
2025-07-17T07:05:47.2088690Z         :meth:`torch.distributed.rpc.RRef.rpc_async`, and
2025-07-17T07:05:47.2088810Z         :meth:`torch.distributed.rpc.RRef.remote`.
2025-07-17T07:05:47.2088850Z     
2025-07-17T07:05:47.2088920Z         >>> from torch.distributed import rpc
2025-07-17T07:05:47.2088960Z         >>>
2025-07-17T07:05:47.2089040Z         >>> # reuse the AsyncExecutionClass class above
2025-07-17T07:05:47.2089130Z         >>> rref = rpc.remote("worker1", AsyncExecutionClass)
2025-07-17T07:05:47.2089260Z         >>> ret = rref.rpc_sync().static_async_add("worker2", torch.ones(2), 1, 2)
2025-07-17T07:05:47.2089330Z         >>> print(ret)  # prints tensor([4., 4.])
2025-07-17T07:05:47.2089370Z         >>>
2025-07-17T07:05:47.2089470Z         >>> rref = rpc.remote("worker1", AsyncExecutionClass)
2025-07-17T07:05:47.2089630Z         >>> ret = rref.rpc_async().static_async_add("worker2", torch.ones(2), 1, 2).wait()
2025-07-17T07:05:47.2089700Z         >>> print(ret)  # prints tensor([4., 4.])
2025-07-17T07:05:47.2089740Z         >>>
2025-07-17T07:05:47.2089830Z         >>> rref = rpc.remote("worker1", AsyncExecutionClass)
2025-07-17T07:05:47.2089970Z         >>> ret = rref.remote().static_async_add("worker2", torch.ones(2), 1, 2).to_here()
2025-07-17T07:05:47.2090040Z         >>> print(ret)  # prints tensor([4., 4.])
2025-07-17T07:05:47.2090080Z     
2025-07-17T07:05:47.2090230Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2090270Z     
2025-07-17T07:05:47.2090320Z       warnings.warn(msg)
2025-07-17T07:05:47.2090360Z     
2025-07-17T07:05:47.2090460Z --- Parse Warning: 92 / 136 ---
2025-07-17T07:05:47.2091210Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=TensorPipeRpcBackendOptions.set_device_map in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/rpc/options.py line=113.
2025-07-17T07:05:47.2091370Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2091410Z     
2025-07-17T07:05:47.2091540Z     Set device mapping between each RPC caller and callee pair. This
2025-07-17T07:05:47.2091640Z     function can be called multiple times to incrementally add
2025-07-17T07:05:47.2091700Z     device placement configurations.
2025-07-17T07:05:47.2091740Z     
2025-07-17T07:05:47.2091780Z     Args:
2025-07-17T07:05:47.2091840Z         to (str): Callee name.
2025-07-17T07:05:47.2091950Z         device_map (Dict of int, str, or torch.device): Device placement
2025-07-17T07:05:47.2092060Z             mappings from this worker to the callee. This map must be
2025-07-17T07:05:47.2092110Z             invertible.
2025-07-17T07:05:47.2092150Z     
2025-07-17T07:05:47.2092200Z     Example:
2025-07-17T07:05:47.2092260Z         >>> # xdoctest: +SKIP("distributed")
2025-07-17T07:05:47.2092310Z         >>> # both workers
2025-07-17T07:05:47.2092360Z         >>> def add(x, y):
2025-07-17T07:05:47.2092440Z         >>>     print(x)  # tensor([1., 1.], device='cuda:1')
2025-07-17T07:05:47.2092510Z         >>>     return x + y, (x + y).to(2)
2025-07-17T07:05:47.2092550Z         >>>
2025-07-17T07:05:47.2092590Z         >>> # on worker 0
2025-07-17T07:05:47.2092670Z         >>> options = TensorPipeRpcBackendOptions(
2025-07-17T07:05:47.2092730Z         >>>     num_worker_threads=8,
2025-07-17T07:05:47.2092800Z         >>>     device_maps={"worker1": {0: 1}}
2025-07-17T07:05:47.2092870Z         >>> # maps worker0's cuda:0 to worker1's cuda:1
2025-07-17T07:05:47.2092910Z         >>> )
2025-07-17T07:05:47.2092990Z         >>> options.set_device_map("worker1", {1: 2})
2025-07-17T07:05:47.2093070Z         >>> # maps worker0's cuda:1 to worker1's cuda:2
2025-07-17T07:05:47.2093110Z         >>>
2025-07-17T07:05:47.2093210Z         >>> rpc.init_rpc(
2025-07-17T07:05:47.2093260Z         >>>     "worker0",
2025-07-17T07:05:47.2093300Z         >>>     rank=0,
2025-07-17T07:05:47.2093350Z         >>>     world_size=2,
2025-07-17T07:05:47.2093440Z         >>>     backend=rpc.BackendType.TENSORPIPE,
2025-07-17T07:05:47.2093510Z         >>>     rpc_backend_options=options
2025-07-17T07:05:47.2093550Z         >>> )
2025-07-17T07:05:47.2093590Z         >>>
2025-07-17T07:05:47.2093640Z         >>> x = torch.ones(2)
2025-07-17T07:05:47.2093740Z         >>> rets = rpc.rpc_sync("worker1", add, args=(x.to(0), 1))
2025-07-17T07:05:47.2093850Z         >>> # The first argument will be moved to cuda:1 on worker1. When
2025-07-17T07:05:47.2093960Z         >>> # sending the return value back, it will follow the invert of
2025-07-17T07:05:47.2094070Z         >>> # the device map, and hence will be moved back to cuda:0 and
2025-07-17T07:05:47.2094150Z         >>> # cuda:1 on worker0
2025-07-17T07:05:47.2094270Z         >>> print(rets[0])  # tensor([2., 2.], device='cuda:0')
2025-07-17T07:05:47.2094360Z         >>> print(rets[1])  # tensor([2., 2.], device='cuda:1')
2025-07-17T07:05:47.2094400Z     
2025-07-17T07:05:47.2094550Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2094590Z     
2025-07-17T07:05:47.2094640Z       warnings.warn(msg)
2025-07-17T07:05:47.2094680Z     
2025-07-17T07:05:47.2094780Z --- Parse Warning: 93 / 136 ---
2025-07-17T07:05:47.2095550Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_server_process_global_profile in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributed/rpc/server_process_global_profiler.py line=19.
2025-07-17T07:05:47.2095700Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2095750Z     
2025-07-17T07:05:47.2095870Z     It has the same API as ``torch.autograd.profiler.profile`` class,
2025-07-17T07:05:47.2096030Z     except that it enables profiling on all threads running RPC server request callbacks.
2025-07-17T07:05:47.2096070Z     
2025-07-17T07:05:47.2096240Z     Context manager that manages autograd profiler state and holds a summary of results.
2025-07-17T07:05:47.2096380Z     Under the hood it just records events of functions being executed in C++ and
2025-07-17T07:05:47.2096520Z     exposes those events to Python. You can wrap any code into it and it will
2025-07-17T07:05:47.2096600Z     only report runtime of PyTorch functions.
2025-07-17T07:05:47.2096760Z     Note: profiler is thread local and is automatically propagated into the async tasks
2025-07-17T07:05:47.2096800Z     
2025-07-17T07:05:47.2096840Z     Args:
2025-07-17T07:05:47.2097000Z         enabled (bool, optional): Setting this to False makes this context manager a no-op.
2025-07-17T07:05:47.2097050Z             Default: ``True``.
2025-07-17T07:05:47.2097090Z     
2025-07-17T07:05:47.2097260Z         use_cuda (bool, optional): Enables timing of CUDA events as well using the cudaEvent API.
2025-07-17T07:05:47.2097380Z             Adds approximately 4us of overhead to each tensor operation.
2025-07-17T07:05:47.2097440Z             Default: ``False``
2025-07-17T07:05:47.2100790Z     
2025-07-17T07:05:47.2100940Z         record_shapes (bool, optional): If shapes recording is set, information
2025-07-17T07:05:47.2101070Z             about input dimensions will be collected. This allows one to see which
2025-07-17T07:05:47.2101200Z             dimensions have been used under the hood and further group by them
2025-07-17T07:05:47.2101330Z             using prof.key_averages(group_by_input_shape=True). Please note that
2025-07-17T07:05:47.2101460Z             shape recording might skew your profiling data. It is recommended to
2025-07-17T07:05:47.2101610Z             use separate runs with and without shape recording to validate the timing.
2025-07-17T07:05:47.2101830Z             Most likely the skew will be negligible for bottom most events (in a case
2025-07-17T07:05:47.2101960Z             of nested function calls). But for higher level functions the total
2025-07-17T07:05:47.2102140Z             self cpu time might be artificially increased because of the shape
2025-07-17T07:05:47.2102190Z             collection.
2025-07-17T07:05:47.2102230Z     
2025-07-17T07:05:47.2102390Z         profile_memory (bool, optional): Whether to report memory usage, default: ``False``
2025-07-17T07:05:47.2102430Z     
2025-07-17T07:05:47.2102480Z     .. warning::
2025-07-17T07:05:47.2102600Z         Enabling memory profiling incurs additional profiler overhead
2025-07-17T07:05:47.2102640Z     
2025-07-17T07:05:47.2102690Z     .. warning::
2025-07-17T07:05:47.2102860Z         Due to some CUDA multiprocessing limitations (see :ref:`multiprocessing-cuda-note`),
2025-07-17T07:05:47.2103000Z         one cannot use the profiler with ``use_cuda = True`` to benchmark
2025-07-17T07:05:47.2103160Z         DataLoaders with ``num_workers > 0``. If you wish to benchmark data loading,
2025-07-17T07:05:47.2103260Z         please use ``use_cuda = False`` or ``num_workers = 0``.
2025-07-17T07:05:47.2103300Z     
2025-07-17T07:05:47.2103350Z     Example:
2025-07-17T07:05:47.2103400Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2103450Z         >>> # On worker 0:
2025-07-17T07:05:47.2103500Z         >>> import torch
2025-07-17T07:05:47.2103570Z         >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:47.2103660Z         >>> rpc.init_rpc("worker0", rank=0, world_size=2)
2025-07-17T07:05:47.2103730Z         >>> x, y = torch.tensor(1), torch.tensor(2)
2025-07-17T07:05:47.2103790Z         >>> outer_profile_rref = rpc.remote(
2025-07-17T07:05:47.2103890Z         ...     dst_worker_name, rpc._server_process_global_profile
2025-07-17T07:05:47.2103930Z         ... )
2025-07-17T07:05:47.2104010Z         >>> outer_profile_rref.rpc_sync().__enter__()
2025-07-17T07:05:47.2104100Z         >>> rpc.rpc_sync(dst_worker_name, torch.add, (x, y))
2025-07-17T07:05:47.2104170Z         >>> inner_profile_rref = rpc.remote(
2025-07-17T07:05:47.2104270Z         ...     dst_worker_name, rpc._server_process_global_profile
2025-07-17T07:05:47.2104310Z         ... )
2025-07-17T07:05:47.2104390Z         >>> inner_profile_rref.rpc_sync().__enter__()
2025-07-17T07:05:47.2104480Z         >>> rpc.rpc_sync(dst_worker_name, torch.sub, (x, y))
2025-07-17T07:05:47.2104580Z         >>> inner_profile_rref.rpc_sync().__exit__(None, None, None)
2025-07-17T07:05:47.2104680Z         >>> outer_profile_rref.rpc_sync().__exit__(None, None, None)
2025-07-17T07:05:47.2104780Z         >>> print(inner_profile_rref.rpc_sync().key_averages())
2025-07-17T07:05:47.2104930Z         ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-07-17T07:05:47.2105120Z         Name       Self CPU total %  Self CPU total   CPU total %      CPU total        CPU time avg     Number of Calls
2025-07-17T07:05:47.2105270Z         ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-07-17T07:05:47.2105390Z         sub        85.06%           76.275us         100.00%          89.667us         89.667us         1
2025-07-17T07:05:47.2105510Z         empty      14.94%           13.392us         14.94%           13.392us         13.392us         1
2025-07-17T07:05:47.2105650Z         ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-07-17T07:05:47.2105710Z         Self CPU time total: 89.667us
2025-07-17T07:05:47.2105810Z         >>> print(outer_profile_rref.rpc_sync().key_averages())
2025-07-17T07:05:47.2105950Z         ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-07-17T07:05:47.2106130Z         Name       Self CPU total %  Self CPU total   CPU total %      CPU total        CPU time avg     Number of Calls
2025-07-17T07:05:47.2106300Z         ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-07-17T07:05:47.2106420Z         sub        35.65%           76.275us         41.91%           89.667us         89.667us         1
2025-07-17T07:05:47.2106550Z         empty      12.67%           27.101us         12.67%           27.101us         13.551us         2
2025-07-17T07:05:47.2106660Z         add        51.68%           110.550us        58.09%           124.259us        124.259us        1
2025-07-17T07:05:47.2106800Z         ---------  ---------------  ---------------  ---------------  ---------------  ---------------  ---------------
2025-07-17T07:05:47.2106860Z         Self CPU time total: 213.926us
2025-07-17T07:05:47.2106920Z         >>> rpc.shutdown()
2025-07-17T07:05:47.2106960Z     
2025-07-17T07:05:47.2107010Z         >>> # On worker 1:
2025-07-17T07:05:47.2107100Z         >>> import torch.distributed.rpc as rpc
2025-07-17T07:05:47.2107210Z         >>> rpc.init_rpc("worker1", rank=1, world_size=2)
2025-07-17T07:05:47.2107300Z         >>> # wait for worker 0 to finish work, and then shutdown.
2025-07-17T07:05:47.2107360Z         >>> rpc.shutdown()
2025-07-17T07:05:47.2107400Z     
2025-07-17T07:05:47.2107550Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2107590Z     
2025-07-17T07:05:47.2107640Z       warnings.warn(msg)
2025-07-17T07:05:47.2107680Z     
2025-07-17T07:05:47.2107790Z --- Parse Warning: 94 / 136 ---
2025-07-17T07:05:47.2108460Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=record_function in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/profiler.py line=734.
2025-07-17T07:05:47.2108610Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2108840Z     Context manager/function decorator that adds a label to a code block/function when running autograd profiler.
2025-07-17T07:05:47.2108950Z         Label will only appear if CPU activity tracing is enabled.
2025-07-17T07:05:47.2109000Z     
2025-07-17T07:05:47.2109070Z         It is useful when tracing the code profile.
2025-07-17T07:05:47.2109110Z     
2025-07-17T07:05:47.2109150Z         Args:
2025-07-17T07:05:47.2109240Z             name (str): Label assigned to the block of code.
2025-07-17T07:05:47.2109350Z             node_id (int): ID of node, for distributed profiling. Unset in
2025-07-17T07:05:47.2109410Z             non-distributed cases.
2025-07-17T07:05:47.2109450Z     
2025-07-17T07:05:47.2109490Z         Example:
2025-07-17T07:05:47.2109600Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_AUTOGRAD_PROFILER)
2025-07-17T07:05:47.2109680Z             >>> x = torch.randn((1, 1), requires_grad=True)
2025-07-17T07:05:47.2109780Z             >>> with torch.autograd.profiler.profile() as prof:
2025-07-17T07:05:47.2109830Z             ...     y = x**2
2025-07-17T07:05:47.2109930Z             ...     with torch.autograd.profiler.record_function(
2025-07-17T07:05:47.2109990Z             ...         "label-z"
2025-07-17T07:05:47.2110040Z             ...     ):  # label the block
2025-07-17T07:05:47.2110090Z             ...         z = y**3
2025-07-17T07:05:47.2110150Z             ...     y.backward()
2025-07-17T07:05:47.2110200Z             >>> # xdoctest: +IGNORE_WANT
2025-07-17T07:05:47.2110290Z             >>> # NOTE: some columns were removed for brevity
2025-07-17T07:05:47.2110410Z             >>> print(prof.key_averages().table(sort_by="self_cpu_time_total"))
2025-07-17T07:05:47.2110530Z             -----------------------------------  ---------------  ---------------  ---------------
2025-07-17T07:05:47.2110650Z             Name                                 Self CPU total %  CPU time avg     Number of Calls
2025-07-17T07:05:47.2110790Z             -----------------------------------  ---------------  ---------------  ---------------
2025-07-17T07:05:47.2110880Z             pow                                  60.77%           47.470us         3
2025-07-17T07:05:47.2110960Z             mul                                  21.73%           25.465us         2
2025-07-17T07:05:47.2111100Z             PowBackward0                         12.03%           121.891us        1
2025-07-17T07:05:47.2111230Z             torch::autograd::AccumulateGrad      2.70%            6.324us          1
2025-07-17T07:05:47.2111330Z             label-z                              2.13%            12.421us         1
2025-07-17T07:05:47.2111440Z             torch::autograd::GraphRoot           0.64%            1.503us          1
2025-07-17T07:05:47.2111570Z             -----------------------------------  ---------------  ---------------  ---------------
2025-07-17T07:05:47.2111630Z             Self CPU time total: 234.344us
2025-07-17T07:05:47.2111700Z             CUDA time total: 0.000us
2025-07-17T07:05:47.2111760Z     
2025-07-17T07:05:47.2111800Z         
2025-07-17T07:05:47.2111950Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2111990Z     
2025-07-17T07:05:47.2112040Z       warnings.warn(msg)
2025-07-17T07:05:47.2112080Z     
2025-07-17T07:05:47.2112180Z --- Parse Warning: 95 / 136 ---
2025-07-17T07:05:47.2112910Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assoc_in in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=245.
2025-07-17T07:05:47.2113060Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2113170Z     Return a new dict with new, potentially nested, key value pair
2025-07-17T07:05:47.2113210Z     
2025-07-17T07:05:47.2113270Z         >>> purchase = {
2025-07-17T07:05:47.2113320Z         ...     "name": "Alice",
2025-07-17T07:05:47.2113430Z         ...     "order": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]},
2025-07-17T07:05:47.2113500Z         ...     "credit card": "5555-1234-1234-1234",
2025-07-17T07:05:47.2113540Z         ... }
2025-07-17T07:05:47.2113660Z         >>> assoc_in(purchase, ["order", "costs"], [0.25, 1.00])  # doctest: +SKIP
2025-07-17T07:05:47.2113730Z         {'credit card': '5555-1234-1234-1234',
2025-07-17T07:05:47.2113780Z          'name': 'Alice',
2025-07-17T07:05:47.2113880Z          'order': {'costs': [0.25, 1.00], 'items': ['Apple', 'Orange']}}
2025-07-17T07:05:47.2113920Z         
2025-07-17T07:05:47.2114070Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2114110Z     
2025-07-17T07:05:47.2114160Z       warnings.warn(msg)
2025-07-17T07:05:47.2114200Z     
2025-07-17T07:05:47.2114290Z --- Parse Warning: 96 / 136 ---
2025-07-17T07:05:47.2115020Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=update_in in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=261.
2025-07-17T07:05:47.2115170Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2115270Z     Update value in a (potentially) nested dictionary
2025-07-17T07:05:47.2115300Z     
2025-07-17T07:05:47.2115340Z         inputs:
2025-07-17T07:05:47.2115410Z         d - dictionary on which to operate
2025-07-17T07:05:47.2115540Z         keys - list or tuple giving the location of the value to be changed in d
2025-07-17T07:05:47.2115610Z         func - function to operate on that value
2025-07-17T07:05:47.2115650Z     
2025-07-17T07:05:47.2115770Z         If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the
2025-07-17T07:05:47.2115930Z         original dictionary with v replaced by func(v), but does not mutate the
2025-07-17T07:05:47.2115990Z         original dictionary.
2025-07-17T07:05:47.2116030Z     
2025-07-17T07:05:47.2116160Z         If k0 is not a key in d, update_in creates nested dictionaries to the depth
2025-07-17T07:05:47.2116310Z         specified by the keys, with the innermost value set to func(default).
2025-07-17T07:05:47.2116350Z     
2025-07-17T07:05:47.2116410Z         >>> inc = lambda x: x + 1
2025-07-17T07:05:47.2116470Z         >>> update_in({"a": 0}, ["a"], inc)
2025-07-17T07:05:47.2116510Z         {'a': 1}
2025-07-17T07:05:47.2116550Z     
2025-07-17T07:05:47.2116600Z         >>> transaction = {
2025-07-17T07:05:47.2116650Z         ...     "name": "Alice",
2025-07-17T07:05:47.2116770Z         ...     "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]},
2025-07-17T07:05:47.2116840Z         ...     "credit card": "5555-1234-1234-1234",
2025-07-17T07:05:47.2116880Z         ... }
2025-07-17T07:05:47.2117040Z         >>> update_in(transaction, ["purchase", "costs"], sum)  # doctest: +SKIP
2025-07-17T07:05:47.2117130Z         {'credit card': '5555-1234-1234-1234',
2025-07-17T07:05:47.2117180Z          'name': 'Alice',
2025-07-17T07:05:47.2117280Z          'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}}
2025-07-17T07:05:47.2117320Z     
2025-07-17T07:05:47.2117400Z         >>> # updating a value when k0 is not in d
2025-07-17T07:05:47.2117470Z         >>> update_in({}, [1, 2, 3], str, default="bar")
2025-07-17T07:05:47.2117520Z         {1: {2: {3: 'bar'}}}
2025-07-17T07:05:47.2117590Z         >>> update_in({1: "foo"}, [2, 3, 4], inc, 0)
2025-07-17T07:05:47.2117640Z         {1: 'foo', 2: {3: {4: 1}}}
2025-07-17T07:05:47.2117690Z         
2025-07-17T07:05:47.2117830Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2117880Z     
2025-07-17T07:05:47.2117930Z       warnings.warn(msg)
2025-07-17T07:05:47.2117970Z     
2025-07-17T07:05:47.2118070Z --- Parse Warning: 97 / 136 ---
2025-07-17T07:05:47.2118780Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=get_in in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=320.
2025-07-17T07:05:47.2118930Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2119040Z     Returns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys.
2025-07-17T07:05:47.2119070Z     
2025-07-17T07:05:47.2119190Z         If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless
2025-07-17T07:05:47.2119310Z         ``no_default`` is specified, then it raises KeyError or IndexError.
2025-07-17T07:05:47.2119350Z     
2025-07-17T07:05:47.2119470Z         ``get_in`` is a generalization of ``operator.getitem`` for nested data
2025-07-17T07:05:47.2119550Z         structures such as dictionaries and lists.
2025-07-17T07:05:47.2119590Z     
2025-07-17T07:05:47.2119640Z         >>> transaction = {
2025-07-17T07:05:47.2119700Z         ...     "name": "Alice",
2025-07-17T07:05:47.2119810Z         ...     "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]},
2025-07-17T07:05:47.2119890Z         ...     "credit card": "5555-1234-1234-1234",
2025-07-17T07:05:47.2119930Z         ... }
2025-07-17T07:05:47.2120010Z         >>> get_in(["purchase", "items", 0], transaction)
2025-07-17T07:05:47.2120050Z         'Apple'
2025-07-17T07:05:47.2120120Z         >>> get_in(["name"], transaction)
2025-07-17T07:05:47.2120160Z         'Alice'
2025-07-17T07:05:47.2120230Z         >>> get_in(["purchase", "total"], transaction)
2025-07-17T07:05:47.2120320Z         >>> get_in(["purchase", "items", "apple"], transaction)
2025-07-17T07:05:47.2120410Z         >>> get_in(["purchase", "items", 10], transaction)
2025-07-17T07:05:47.2120490Z         >>> get_in(["purchase", "total"], transaction, 0)
2025-07-17T07:05:47.2120530Z         0
2025-07-17T07:05:47.2120610Z         >>> get_in(["y"], {}, no_default=True)
2025-07-17T07:05:47.2120680Z         Traceback (most recent call last):
2025-07-17T07:05:47.2120720Z             ...
2025-07-17T07:05:47.2120760Z         KeyError: 'y'
2025-07-17T07:05:47.2120830Z     
2025-07-17T07:05:47.2120870Z         See Also:
2025-07-17T07:05:47.2120920Z             itertoolz.get
2025-07-17T07:05:47.2120970Z             operator.getitem
2025-07-17T07:05:47.2121010Z         
2025-07-17T07:05:47.2121160Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2121200Z     
2025-07-17T07:05:47.2121250Z       warnings.warn(msg)
2025-07-17T07:05:47.2121290Z     
2025-07-17T07:05:47.2121390Z --- Parse Warning: 98 / 136 ---
2025-07-17T07:05:47.2122130Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=groupby in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/unification/unification_tools.py line=373.
2025-07-17T07:05:47.2122300Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2122370Z     Group a collection by a key function
2025-07-17T07:05:47.2122410Z     
2025-07-17T07:05:47.2122510Z         >>> names = ["Alice", "Bob", "Charlie", "Dan", "Edith", "Frank"]
2025-07-17T07:05:47.2122580Z         >>> groupby(len, names)  # doctest: +SKIP
2025-07-17T07:05:47.2122680Z         {3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']}
2025-07-17T07:05:47.2122720Z     
2025-07-17T07:05:47.2122780Z         >>> iseven = lambda x: x % 2 == 0
2025-07-17T07:05:47.2122880Z         >>> groupby(iseven, [1, 2, 3, 4, 5, 6, 7, 8])  # doctest: +SKIP
2025-07-17T07:05:47.2122950Z         {False: [1, 3, 5, 7], True: [2, 4, 6, 8]}
2025-07-17T07:05:47.2122990Z     
2025-07-17T07:05:47.2123070Z         Non-callable keys imply grouping on a member.
2025-07-17T07:05:47.2123110Z     
2025-07-17T07:05:47.2123160Z         >>> groupby(
2025-07-17T07:05:47.2123210Z         ...     "gender",
2025-07-17T07:05:47.2123250Z         ...     [
2025-07-17T07:05:47.2123320Z         ...         {"name": "Alice", "gender": "F"},
2025-07-17T07:05:47.2123390Z         ...         {"name": "Bob", "gender": "M"},
2025-07-17T07:05:47.2123460Z         ...         {"name": "Charlie", "gender": "M"},
2025-07-17T07:05:47.2123500Z         ...     ],
2025-07-17T07:05:47.2123550Z         ... )  # doctest:+SKIP
2025-07-17T07:05:47.2123630Z         {'F': [{'gender': 'F', 'name': 'Alice'}],
2025-07-17T07:05:47.2123690Z          'M': [{'gender': 'M', 'name': 'Bob'},
2025-07-17T07:05:47.2123760Z                {'gender': 'M', 'name': 'Charlie'}]}
2025-07-17T07:05:47.2123790Z     
2025-07-17T07:05:47.2123880Z         Not to be confused with ``itertools.groupby``
2025-07-17T07:05:47.2123920Z     
2025-07-17T07:05:47.2123960Z         See Also:
2025-07-17T07:05:47.2124000Z             countby
2025-07-17T07:05:47.2124040Z         
2025-07-17T07:05:47.2124200Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2124240Z     
2025-07-17T07:05:47.2124290Z       warnings.warn(msg)
2025-07-17T07:05:47.2124330Z     
2025-07-17T07:05:47.2124430Z --- Parse Warning: 99 / 136 ---
2025-07-17T07:05:47.2125080Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SequentialLR in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=808.
2025-07-17T07:05:47.2125240Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2125430Z     Contains a list of schedulers expected to be called sequentially during the optimization process.
2025-07-17T07:05:47.2125480Z     
2025-07-17T07:05:47.2125720Z         Specifically, the schedulers will be called according to the milestone points, which should provide exact
2025-07-17T07:05:47.2125860Z         intervals by which each scheduler should be called at a given epoch.
2025-07-17T07:05:47.2125900Z     
2025-07-17T07:05:47.2125950Z         Args:
2025-07-17T07:05:47.2126040Z             optimizer (Optimizer): Wrapped optimizer.
2025-07-17T07:05:47.2126130Z             schedulers (list): List of chained schedulers.
2025-07-17T07:05:47.2126260Z             milestones (list): List of integers that reflects milestone points.
2025-07-17T07:05:47.2126360Z             last_epoch (int): The index of last epoch. Default: -1.
2025-07-17T07:05:47.2126400Z     
2025-07-17T07:05:47.2126450Z         Example:
2025-07-17T07:05:47.2126500Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2126590Z             >>> # Assuming optimizer uses lr = 0.05 for all groups
2025-07-17T07:05:47.2126660Z             >>> # lr = 0.005     if epoch == 0
2025-07-17T07:05:47.2126740Z             >>> # lr = 0.005     if epoch == 1
2025-07-17T07:05:47.2126820Z             >>> # lr = 0.005     if epoch == 2
2025-07-17T07:05:47.2126870Z             >>> # ...
2025-07-17T07:05:47.2126930Z             >>> # lr = 0.05      if epoch == 20
2025-07-17T07:05:47.2126990Z             >>> # lr = 0.045     if epoch == 21
2025-07-17T07:05:47.2127050Z             >>> # lr = 0.0405    if epoch == 22
2025-07-17T07:05:47.2127170Z             >>> scheduler1 = ConstantLR(optimizer, factor=0.1, total_iters=20)
2025-07-17T07:05:47.2127270Z             >>> scheduler2 = ExponentialLR(optimizer, gamma=0.9)
2025-07-17T07:05:47.2127330Z             >>> scheduler = SequentialLR(
2025-07-17T07:05:47.2127380Z             ...     optimizer,
2025-07-17T07:05:47.2127460Z             ...     schedulers=[scheduler1, scheduler2],
2025-07-17T07:05:47.2127510Z             ...     milestones=[20],
2025-07-17T07:05:47.2127560Z             ... )
2025-07-17T07:05:47.2127610Z             >>> for epoch in range(100):
2025-07-17T07:05:47.2127670Z             >>>     train(...)
2025-07-17T07:05:47.2127720Z             >>>     validate(...)
2025-07-17T07:05:47.2127780Z             >>>     scheduler.step()
2025-07-17T07:05:47.2127820Z     
2025-07-17T07:05:47.2127930Z         .. image:: ../scripts/lr_scheduler_images/SequentialLR.png
2025-07-17T07:05:47.2127970Z         
2025-07-17T07:05:47.2128120Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2128160Z     
2025-07-17T07:05:47.2128210Z       warnings.warn(msg)
2025-07-17T07:05:47.2128250Z     
2025-07-17T07:05:47.2128350Z --- Parse Warning: 100 / 136 ---
2025-07-17T07:05:47.2129020Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ReduceLROnPlateau in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1233.
2025-07-17T07:05:47.2129170Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:47.2129280Z     Reduce learning rate when a metric has stopped improving.
2025-07-17T07:05:47.2129320Z     
2025-07-17T07:05:47.2129440Z         Models often benefit from reducing the learning rate by a factor
2025-07-17T07:05:47.2129560Z         of 2-10 once learning stagnates. This scheduler reads a metrics
2025-07-17T07:05:47.2129670Z         quantity and if no improvement is seen for a 'patience' number
2025-07-17T07:05:47.2129750Z         of epochs, the learning rate is reduced.
2025-07-17T07:05:47.2129790Z     
2025-07-17T07:05:47.2129830Z         Args:
2025-07-17T07:05:47.2129910Z             optimizer (Optimizer): Wrapped optimizer.
2025-07-17T07:05:47.2130000Z             mode (str): One of `min`, `max`. In `min` mode, lr will
2025-07-17T07:05:47.2130100Z                 be reduced when the quantity monitored has stopped
2025-07-17T07:05:47.2130200Z                 decreasing; in `max` mode it will be reduced when the
2025-07-17T07:05:47.2130340Z                 quantity monitored has stopped increasing. Default: 'min'.
2025-07-17T07:05:47.2130450Z             factor (float): Factor by which the learning rate will be
2025-07-17T07:05:47.2130530Z                 reduced. new_lr = lr * factor. Default: 0.1.
2025-07-17T07:05:47.2130700Z             patience (int): The number of allowed epochs with no improvement after
2025-07-17T07:05:47.2130770Z                 which the learning rate will be reduced.
2025-07-17T07:05:47.2130910Z                 For example, consider the case of having no patience (`patience = 0`).
2025-07-17T07:05:47.2131130Z                 In the first epoch, a baseline is established and is always considered good as there's no previous baseline.
2025-07-17T07:05:47.2131260Z                 In the second epoch, if the performance is worse than the baseline,
2025-07-17T07:05:47.2131340Z                 we have what is considered an intolerable epoch.
2025-07-17T07:05:47.2131520Z                 Since the count of intolerable epochs (1) is greater than the patience level (0),
2025-07-17T07:05:47.2131640Z                 the learning rate is reduced at the end of this epoch.
2025-07-17T07:05:47.2131830Z                 From the third epoch onwards, the learning rate continues to be reduced at the end of each epoch
2025-07-17T07:05:47.2132020Z                 if the performance is worse than the baseline. If the performance improves or remains the same,
2025-07-17T07:05:47.2132100Z                 the learning rate is not adjusted.
2025-07-17T07:05:47.2132150Z                 Default: 10.
2025-07-17T07:05:47.2132260Z             threshold (float): Threshold for measuring the new optimum,
2025-07-17T07:05:47.2132360Z                 to only focus on significant changes. Default: 1e-4.
2025-07-17T07:05:47.2132470Z             threshold_mode (str): One of `rel`, `abs`. In `rel` mode,
2025-07-17T07:05:47.2132560Z                 dynamic_threshold = best * ( 1 + threshold ) in 'max'
2025-07-17T07:05:47.2132650Z                 mode or best * ( 1 - threshold ) in `min` mode.
2025-07-17T07:05:47.2132750Z                 In `abs` mode, dynamic_threshold = best + threshold in
2025-07-17T07:05:47.2132860Z                 `max` mode or best - threshold in `min` mode. Default: 'rel'.
2025-07-17T07:05:47.2132960Z             cooldown (int): Number of epochs to wait before resuming
2025-07-17T07:05:47.2133070Z                 normal operation after lr has been reduced. Default: 0.
2025-07-17T07:05:47.2133170Z             min_lr (float or list): A scalar or a list of scalars. A
2025-07-17T07:05:47.2133270Z                 lower bound on the learning rate of all param groups
2025-07-17T07:05:47.2133350Z                 or each group respectively. Default: 0.
2025-07-17T07:05:47.2133450Z             eps (float): Minimal decay applied to lr. If the difference
2025-07-17T07:05:47.2133560Z                 between new and old lr is smaller than eps, the update is
2025-07-17T07:05:47.2133620Z                 ignored. Default: 1e-8.
2025-07-17T07:05:47.2133660Z     
2025-07-17T07:05:47.2133710Z         Example:
2025-07-17T07:05:47.2133760Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2133900Z             >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)
2025-07-17T07:05:47.2134000Z             >>> scheduler = ReduceLROnPlateau(optimizer, "min")
2025-07-17T07:05:47.2134050Z             >>> for epoch in range(10):
2025-07-17T07:05:47.2134100Z             >>>     train(...)
2025-07-17T07:05:47.2134160Z             >>>     val_loss = validate(...)
2025-07-17T07:05:47.2134260Z             >>> # Note that step should be called after validate()
2025-07-17T07:05:47.2134320Z             >>>     scheduler.step(val_loss)
2025-07-17T07:05:47.2134360Z     
2025-07-17T07:05:47.2134480Z         .. image:: ../scripts/lr_scheduler_images/ReduceLROnPlateau.png
2025-07-17T07:05:47.2134520Z         
2025-07-17T07:05:47.2134760Z     Original Error: IndentationError('unexpected indent', ('<source_block>', 8, 4, '    scheduler.step(val_loss)\n', 8, -1))
2025-07-17T07:05:47.2134800Z     
2025-07-17T07:05:47.2134880Z         scheduler.step(val_loss)
2025-07-17T07:05:47.2134920Z        ^
2025-07-17T07:05:47.2134980Z       warnings.warn(msg)
2025-07-17T07:05:47.2135020Z     
2025-07-17T07:05:47.2135120Z --- Parse Warning: 101 / 136 ---
2025-07-17T07:05:47.2135790Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CyclicLR in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1430.
2025-07-17T07:05:47.2135940Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2136130Z     Sets the learning rate of each parameter group according to cyclical learning rate policy (CLR).
2025-07-17T07:05:47.2136170Z     
2025-07-17T07:05:47.2136370Z         The policy cycles the learning rate between two boundaries with a constant frequency,
2025-07-17T07:05:47.2136560Z         as detailed in the paper `Cyclical Learning Rates for Training Neural Networks`_.
2025-07-17T07:05:47.2136690Z         The distance between the two boundaries can be scaled on a per-iteration
2025-07-17T07:05:47.2136750Z         or per-cycle basis.
2025-07-17T07:05:47.2136790Z     
2025-07-17T07:05:47.2136930Z         Cyclical learning rate policy changes the learning rate after every batch.
2025-07-17T07:05:47.2137050Z         `step` should be called after a batch has been used for training.
2025-07-17T07:05:47.2137090Z     
2025-07-17T07:05:47.2137220Z         This class has three built-in policies, as put forth in the paper:
2025-07-17T07:05:47.2137260Z     
2025-07-17T07:05:47.2137390Z         * "triangular": A basic triangular cycle without amplitude scaling.
2025-07-17T07:05:47.2137560Z         * "triangular2": A basic triangular cycle that scales initial amplitude by half each cycle.
2025-07-17T07:05:47.2137760Z         * "exp_range": A cycle that scales initial amplitude by :math:`\text{gamma}^{\text{cycle iterations}}`
2025-07-17T07:05:47.2137820Z           at each cycle iteration.
2025-07-17T07:05:47.2137860Z     
2025-07-17T07:05:47.2138000Z         This implementation was adapted from the github repo: `bckenstler/CLR`_
2025-07-17T07:05:47.2138040Z     
2025-07-17T07:05:47.2138080Z         Args:
2025-07-17T07:05:47.2138170Z             optimizer (Optimizer): Wrapped optimizer.
2025-07-17T07:05:47.2138270Z             base_lr (float or list): Initial learning rate which is the
2025-07-17T07:05:47.2138380Z                 lower boundary in the cycle for each parameter group.
2025-07-17T07:05:47.2138500Z             max_lr (float or list): Upper learning rate boundaries in the cycle
2025-07-17T07:05:47.2138570Z                 for each parameter group. Functionally,
2025-07-17T07:05:47.2138670Z                 it defines the cycle amplitude (max_lr - base_lr).
2025-07-17T07:05:47.2138740Z                 The lr at any cycle is the sum of base_lr
2025-07-17T07:05:47.2138830Z                 and some scaling of the amplitude; therefore
2025-07-17T07:05:47.2138920Z                 max_lr may not actually be reached depending on
2025-07-17T07:05:47.2138980Z                 scaling function.
2025-07-17T07:05:47.2139080Z             step_size_up (int): Number of training iterations in the
2025-07-17T07:05:47.2139160Z                 increasing half of a cycle. Default: 2000
2025-07-17T07:05:47.2139270Z             step_size_down (int): Number of training iterations in the
2025-07-17T07:05:47.2139370Z                 decreasing half of a cycle. If step_size_down is None,
2025-07-17T07:05:47.2139450Z                 it is set to step_size_up. Default: None
2025-07-17T07:05:47.2139550Z             mode (str): One of {triangular, triangular2, exp_range}.
2025-07-17T07:05:47.2139640Z                 Values correspond to policies detailed above.
2025-07-17T07:05:47.2139730Z                 If scale_fn is not None, this argument is ignored.
2025-07-17T07:05:47.2139790Z                 Default: 'triangular'
2025-07-17T07:05:47.2139910Z             gamma (float): Constant in 'exp_range' scaling function:
2025-07-17T07:05:47.2139970Z                 gamma**(cycle iterations)
2025-07-17T07:05:47.2140020Z                 Default: 1.0
2025-07-17T07:05:47.2140130Z             scale_fn (function): Custom scaling policy defined by a single
2025-07-17T07:05:47.2140230Z                 argument lambda function, where
2025-07-17T07:05:47.2140300Z                 0 <= scale_fn(x) <= 1 for all x >= 0.
2025-07-17T07:05:47.2140370Z                 If specified, then 'mode' is ignored.
2025-07-17T07:05:47.2140420Z                 Default: None
2025-07-17T07:05:47.2140500Z             scale_mode (str): {'cycle', 'iterations'}.
2025-07-17T07:05:47.2140570Z                 Defines whether scale_fn is evaluated on
2025-07-17T07:05:47.2140650Z                 cycle number or cycle iterations (training
2025-07-17T07:05:47.2140720Z                 iterations since start of cycle).
2025-07-17T07:05:47.2140790Z                 Default: 'cycle'
2025-07-17T07:05:47.2140940Z             cycle_momentum (bool): If ``True``, momentum is cycled inversely
2025-07-17T07:05:47.2141050Z                 to learning rate between 'base_momentum' and 'max_momentum'.
2025-07-17T07:05:47.2141100Z                 Default: True
2025-07-17T07:05:47.2141230Z             base_momentum (float or list): Lower momentum boundaries in the cycle
2025-07-17T07:05:47.2141350Z                 for each parameter group. Note that momentum is cycled inversely
2025-07-17T07:05:47.2141450Z                 to learning rate; at the peak of a cycle, momentum is
2025-07-17T07:05:47.2141540Z                 'base_momentum' and learning rate is 'max_lr'.
2025-07-17T07:05:47.2141590Z                 Default: 0.8
2025-07-17T07:05:47.2141720Z             max_momentum (float or list): Upper momentum boundaries in the cycle
2025-07-17T07:05:47.2141800Z                 for each parameter group. Functionally,
2025-07-17T07:05:47.2141910Z                 it defines the cycle amplitude (max_momentum - base_momentum).
2025-07-17T07:05:47.2142030Z                 The momentum at any cycle is the difference of max_momentum
2025-07-17T07:05:47.2142110Z                 and some scaling of the amplitude; therefore
2025-07-17T07:05:47.2142210Z                 base_momentum may not actually be reached depending on
2025-07-17T07:05:47.2142320Z                 scaling function. Note that momentum is cycled inversely
2025-07-17T07:05:47.2142450Z                 to learning rate; at the start of a cycle, momentum is 'max_momentum'
2025-07-17T07:05:47.2142520Z                 and learning rate is 'base_lr'
2025-07-17T07:05:47.2142570Z                 Default: 0.9
2025-07-17T07:05:47.2142700Z             last_epoch (int): The index of the last batch. This parameter is used when
2025-07-17T07:05:47.2142830Z                 resuming a training job. Since `step()` should be invoked after each
2025-07-17T07:05:47.2142960Z                 batch instead of after each epoch, this number represents the total
2025-07-17T07:05:47.2143100Z                 number of *batches* computed, not the total number of epochs computed.
2025-07-17T07:05:47.2143220Z                 When last_epoch=-1, the schedule is started from the beginning.
2025-07-17T07:05:47.2143270Z                 Default: -1
2025-07-17T07:05:47.2143310Z     
2025-07-17T07:05:47.2143350Z         Example:
2025-07-17T07:05:47.2143410Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2143540Z             >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9)
2025-07-17T07:05:47.2143640Z             >>> scheduler = torch.optim.lr_scheduler.CyclicLR(
2025-07-17T07:05:47.2143690Z             ...     optimizer,
2025-07-17T07:05:47.2143740Z             ...     base_lr=0.01,
2025-07-17T07:05:47.2143790Z             ...     max_lr=0.1,
2025-07-17T07:05:47.2143850Z             ...     step_size_up=10,
2025-07-17T07:05:47.2143890Z             ... )
2025-07-17T07:05:47.2143980Z             >>> data_loader = torch.utils.data.DataLoader(...)
2025-07-17T07:05:47.2144040Z             >>> for epoch in range(10):
2025-07-17T07:05:47.2144130Z             >>>     for batch in data_loader:
2025-07-17T07:05:47.2144190Z             >>>         train_batch(...)
2025-07-17T07:05:47.2144250Z             >>>         scheduler.step()
2025-07-17T07:05:47.2144310Z     
2025-07-17T07:05:47.2144400Z         .. image:: ../scripts/lr_scheduler_images/CyclicLR.png
2025-07-17T07:05:47.2144440Z     
2025-07-17T07:05:47.2144650Z         .. _Cyclical Learning Rates for Training Neural Networks: https://arxiv.org/abs/1506.01186
2025-07-17T07:05:47.2144750Z         .. _bckenstler/CLR: https://github.com/bckenstler/CLR
2025-07-17T07:05:47.2144790Z         
2025-07-17T07:05:47.2144940Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2144980Z     
2025-07-17T07:05:47.2145030Z       warnings.warn(msg)
2025-07-17T07:05:47.2145070Z     
2025-07-17T07:05:47.2145200Z --- Parse Warning: 102 / 136 ---
2025-07-17T07:05:47.2145920Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CosineAnnealingWarmRestarts in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1713.
2025-07-17T07:05:47.2146080Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2146230Z     Set the learning rate of each parameter group using a cosine annealing schedule.
2025-07-17T07:05:47.2146270Z     
2025-07-17T07:05:47.2146380Z         The :math:`\eta_{max}` is set to the initial lr, :math:`T_{cur}`
2025-07-17T07:05:47.2146530Z         is the number of epochs since the last restart and :math:`T_{i}` is the number
2025-07-17T07:05:47.2146610Z         of epochs between two warm restarts in SGDR:
2025-07-17T07:05:47.2146650Z     
2025-07-17T07:05:47.2146690Z         .. math::
2025-07-17T07:05:47.2146810Z             \eta_t = \eta_{min} + \frac{1}{2}(\eta_{max} - \eta_{min})\left(1 +
2025-07-17T07:05:47.2146900Z             \cos\left(\frac{T_{cur}}{T_{i}}\pi\right)\right)
2025-07-17T07:05:47.2146940Z     
2025-07-17T07:05:47.2147040Z         When :math:`T_{cur}=T_{i}`, set :math:`\eta_t = \eta_{min}`.
2025-07-17T07:05:47.2147160Z         When :math:`T_{cur}=0` after restart, set :math:`\eta_t=\eta_{max}`.
2025-07-17T07:05:47.2147200Z     
2025-07-17T07:05:47.2147250Z         It has been proposed in
2025-07-17T07:05:47.2147360Z         `SGDR: Stochastic Gradient Descent with Warm Restarts`_.
2025-07-17T07:05:47.2147400Z     
2025-07-17T07:05:47.2147440Z         Args:
2025-07-17T07:05:47.2147520Z             optimizer (Optimizer): Wrapped optimizer.
2025-07-17T07:05:47.2147620Z             T_0 (int): Number of iterations until the first restart.
2025-07-17T07:05:47.2147790Z             T_mult (int, optional): A factor by which :math:`T_{i}` increases after a restart. Default: 1.
2025-07-17T07:05:47.2147900Z             eta_min (float, optional): Minimum learning rate. Default: 0.
2025-07-17T07:05:47.2148030Z             last_epoch (int, optional): The index of the last epoch. Default: -1.
2025-07-17T07:05:47.2148080Z     
2025-07-17T07:05:47.2148180Z         .. _SGDR\: Stochastic Gradient Descent with Warm Restarts:
2025-07-17T07:05:47.2148250Z             https://arxiv.org/abs/1608.03983
2025-07-17T07:05:47.2148290Z     
2025-07-17T07:05:47.2148330Z         Example:
2025-07-17T07:05:47.2148390Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2148500Z             >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.05)
2025-07-17T07:05:47.2148640Z             >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingWarmRestarts(
2025-07-17T07:05:47.2148690Z             ...     optimizer, T_0=20
2025-07-17T07:05:47.2148730Z             ... )
2025-07-17T07:05:47.2148790Z             >>> for epoch in range(100):
2025-07-17T07:05:47.2148840Z             >>>     train(...)
2025-07-17T07:05:47.2148900Z             >>>     validate(...)
2025-07-17T07:05:47.2148950Z             >>>     scheduler.step()
2025-07-17T07:05:47.2149040Z     
2025-07-17T07:05:47.2149180Z         .. image:: ../scripts/lr_scheduler_images/CosineAnnealingWarmRestarts.png
2025-07-17T07:05:47.2149220Z         
2025-07-17T07:05:47.2149370Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2149440Z     
2025-07-17T07:05:47.2149490Z       warnings.warn(msg)
2025-07-17T07:05:47.2149530Z     
2025-07-17T07:05:47.2149630Z --- Parse Warning: 103 / 136 ---
2025-07-17T07:05:47.2150280Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=OneCycleLR in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/lr_scheduler.py line=1863.
2025-07-17T07:05:47.2150440Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2150640Z     Sets the learning rate of each parameter group according to the 1cycle learning rate policy.
2025-07-17T07:05:47.2150700Z     
2025-07-17T07:05:47.2150870Z         The 1cycle policy anneals the learning rate from an initial learning rate to some maximum
2025-07-17T07:05:47.2151040Z         learning rate and then from that maximum learning rate to some minimum learning rate much
2025-07-17T07:05:47.2151110Z         lower than the initial learning rate.
2025-07-17T07:05:47.2151250Z         This policy was initially described in the paper `Super-Convergence:
2025-07-17T07:05:47.2151380Z         Very Fast Training of Neural Networks Using Large Learning Rates`_.
2025-07-17T07:05:47.2151420Z     
2025-07-17T07:05:47.2151560Z         The 1cycle learning rate policy changes the learning rate after every batch.
2025-07-17T07:05:47.2151680Z         `step` should be called after a batch has been used for training.
2025-07-17T07:05:47.2151720Z     
2025-07-17T07:05:47.2151780Z         This scheduler is not chainable.
2025-07-17T07:05:47.2155330Z     
2025-07-17T07:05:47.2155530Z         Note also that the total number of steps in the cycle can be determined in one
2025-07-17T07:05:47.2155610Z         of two ways (listed in order of precedence):
2025-07-17T07:05:47.2155660Z     
2025-07-17T07:05:47.2155750Z         #. A value for total_steps is explicitly provided.
2025-07-17T07:05:47.2155870Z         #. A number of epochs (epochs) and a number of steps per epoch
2025-07-17T07:05:47.2155930Z            (steps_per_epoch) are provided.
2025-07-17T07:05:47.2156030Z            In this case, the number of total steps is inferred by
2025-07-17T07:05:47.2156110Z            total_steps = epochs * steps_per_epoch
2025-07-17T07:05:47.2156150Z     
2025-07-17T07:05:47.2156290Z         You must either provide a value for total_steps or provide a value for both
2025-07-17T07:05:47.2156350Z         epochs and steps_per_epoch.
2025-07-17T07:05:47.2156390Z     
2025-07-17T07:05:47.2156570Z         The default behaviour of this scheduler follows the fastai implementation of 1cycle, which
2025-07-17T07:05:47.2156750Z         claims that "unpublished work has shown even better results by using only two phases". To
2025-07-17T07:05:47.2156890Z         mimic the behaviour of the original paper instead, set ``three_phase=True``.
2025-07-17T07:05:47.2156940Z     
2025-07-17T07:05:47.2156980Z         Args:
2025-07-17T07:05:47.2157060Z             optimizer (Optimizer): Wrapped optimizer.
2025-07-17T07:05:47.2157180Z             max_lr (float or list): Upper learning rate boundaries in the cycle
2025-07-17T07:05:47.2157250Z                 for each parameter group.
2025-07-17T07:05:47.2157370Z             total_steps (int): The total number of steps in the cycle. Note that
2025-07-17T07:05:47.2157500Z                 if a value is not provided here, then it must be inferred by providing
2025-07-17T07:05:47.2157570Z                 a value for epochs and steps_per_epoch.
2025-07-17T07:05:47.2157630Z                 Default: None
2025-07-17T07:05:47.2157840Z             epochs (int): The number of epochs to train for. This is used along
2025-07-17T07:05:47.2158000Z                 with steps_per_epoch in order to infer the total number of steps in the cycle
2025-07-17T07:05:47.2158080Z                 if a value for total_steps is not provided.
2025-07-17T07:05:47.2158150Z                 Default: None
2025-07-17T07:05:47.2158290Z             steps_per_epoch (int): The number of steps per epoch to train for. This is
2025-07-17T07:05:47.2158420Z                 used along with epochs in order to infer the total number of steps in the
2025-07-17T07:05:47.2158520Z                 cycle if a value for total_steps is not provided.
2025-07-17T07:05:47.2158570Z                 Default: None
2025-07-17T07:05:47.2158710Z             pct_start (float): The percentage of the cycle (in number of steps) spent
2025-07-17T07:05:47.2158770Z                 increasing the learning rate.
2025-07-17T07:05:47.2158830Z                 Default: 0.3
2025-07-17T07:05:47.2158930Z             anneal_strategy (str): {'cos', 'linear'}
2025-07-17T07:05:47.2159100Z                 Specifies the annealing strategy: "cos" for cosine annealing, "linear" for
2025-07-17T07:05:47.2159160Z                 linear annealing.
2025-07-17T07:05:47.2159210Z                 Default: 'cos'
2025-07-17T07:05:47.2159330Z             cycle_momentum (bool): If ``True``, momentum is cycled inversely
2025-07-17T07:05:47.2159450Z                 to learning rate between 'base_momentum' and 'max_momentum'.
2025-07-17T07:05:47.2159500Z                 Default: True
2025-07-17T07:05:47.2159630Z             base_momentum (float or list): Lower momentum boundaries in the cycle
2025-07-17T07:05:47.2159750Z                 for each parameter group. Note that momentum is cycled inversely
2025-07-17T07:05:47.2159850Z                 to learning rate; at the peak of a cycle, momentum is
2025-07-17T07:05:47.2159940Z                 'base_momentum' and learning rate is 'max_lr'.
2025-07-17T07:05:47.2159990Z                 Default: 0.85
2025-07-17T07:05:47.2160120Z             max_momentum (float or list): Upper momentum boundaries in the cycle
2025-07-17T07:05:47.2160200Z                 for each parameter group. Functionally,
2025-07-17T07:05:47.2160320Z                 it defines the cycle amplitude (max_momentum - base_momentum).
2025-07-17T07:05:47.2160390Z                 Note that momentum is cycled inversely
2025-07-17T07:05:47.2160520Z                 to learning rate; at the start of a cycle, momentum is 'max_momentum'
2025-07-17T07:05:47.2160590Z                 and learning rate is 'base_lr'
2025-07-17T07:05:47.2160640Z                 Default: 0.95
2025-07-17T07:05:47.2160750Z             div_factor (float): Determines the initial learning rate via
2025-07-17T07:05:47.2160820Z                 initial_lr = max_lr/div_factor
2025-07-17T07:05:47.2160860Z                 Default: 25
2025-07-17T07:05:47.2160990Z             final_div_factor (float): Determines the minimum learning rate via
2025-07-17T07:05:47.2161060Z                 min_lr = initial_lr/final_div_factor
2025-07-17T07:05:47.2161120Z                 Default: 1e4
2025-07-17T07:05:47.2161270Z             three_phase (bool): If ``True``, use a third phase of the schedule to annihilate the
2025-07-17T07:05:47.2161420Z                 learning rate according to 'final_div_factor' instead of modifying the second
2025-07-17T07:05:47.2161570Z                 phase (the first two phases will be symmetrical about the step indicated by
2025-07-17T07:05:47.2161620Z                 'pct_start').
2025-07-17T07:05:47.2161760Z             last_epoch (int): The index of the last batch. This parameter is used when
2025-07-17T07:05:47.2161890Z                 resuming a training job. Since `step()` should be invoked after each
2025-07-17T07:05:47.2162020Z                 batch instead of after each epoch, this number represents the total
2025-07-17T07:05:47.2162150Z                 number of *batches* computed, not the total number of epochs computed.
2025-07-17T07:05:47.2162290Z                 When last_epoch=-1, the schedule is started from the beginning.
2025-07-17T07:05:47.2162340Z                 Default: -1
2025-07-17T07:05:47.2162380Z     
2025-07-17T07:05:47.2162430Z         Example:
2025-07-17T07:05:47.2162480Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2162600Z             >>> data_loader = torch.utils.data.DataLoader(...)
2025-07-17T07:05:47.2162740Z             >>> optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9)
2025-07-17T07:05:47.2162840Z             >>> scheduler = torch.optim.lr_scheduler.OneCycleLR(
2025-07-17T07:05:47.2162970Z             ...     optimizer, max_lr=0.01, steps_per_epoch=len(data_loader), epochs=10
2025-07-17T07:05:47.2163010Z             ... )
2025-07-17T07:05:47.2163070Z             >>> for epoch in range(10):
2025-07-17T07:05:47.2163130Z             >>>     for batch in data_loader:
2025-07-17T07:05:47.2163190Z             >>>         train_batch(...)
2025-07-17T07:05:47.2163270Z             >>>         optimizer.step()
2025-07-17T07:05:47.2163350Z             >>>         scheduler.step()
2025-07-17T07:05:47.2163390Z     
2025-07-17T07:05:47.2163490Z         .. image:: ../scripts/lr_scheduler_images/OneCycleLR.png
2025-07-17T07:05:47.2163530Z     
2025-07-17T07:05:47.2163700Z         .. _Super-Convergence\: Very Fast Training of Neural Networks Using Large Learning Rates:
2025-07-17T07:05:47.2163770Z             https://arxiv.org/abs/1708.07120
2025-07-17T07:05:47.2163810Z         
2025-07-17T07:05:47.2163970Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2164010Z     
2025-07-17T07:05:47.2164060Z       warnings.warn(msg)
2025-07-17T07:05:47.2164100Z     
2025-07-17T07:05:47.2164220Z --- Parse Warning: 104 / 136 ---
2025-07-17T07:05:47.2164870Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=AveragedModel in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/swa_utils.py line=120.
2025-07-17T07:05:47.2165030Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2165240Z     Implements averaged model for Stochastic Weight Averaging (SWA) and Exponential Moving Average (EMA).
2025-07-17T07:05:47.2165280Z     
2025-07-17T07:05:47.2165430Z         Stochastic Weight Averaging was proposed in `Averaging Weights Leads to
2025-07-17T07:05:47.2165560Z         Wider Optima and Better Generalization`_ by Pavel Izmailov, Dmitrii
2025-07-17T07:05:47.2165690Z         Podoprikhin, Timur Garipov, Dmitry Vetrov and Andrew Gordon Wilson
2025-07-17T07:05:47.2165730Z         (UAI 2018).
2025-07-17T07:05:47.2165770Z     
2025-07-17T07:05:47.2165900Z         Exponential Moving Average is a variation of `Polyak averaging`_,
2025-07-17T07:05:47.2166050Z         but using exponential weights instead of equal weights across iterations.
2025-07-17T07:05:47.2166090Z     
2025-07-17T07:05:47.2166230Z         AveragedModel class creates a copy of the provided module :attr:`model`
2025-07-17T07:05:47.2166370Z         on the device :attr:`device` and allows to compute running averages of the
2025-07-17T07:05:47.2166430Z         parameters of the :attr:`model`.
2025-07-17T07:05:47.2166470Z     
2025-07-17T07:05:47.2166510Z         Args:
2025-07-17T07:05:47.2166610Z             model (torch.nn.Module): model to use with SWA/EMA
2025-07-17T07:05:47.2166750Z             device (torch.device, optional): if provided, the averaged model will be
2025-07-17T07:05:47.2166810Z                 stored on the :attr:`device`
2025-07-17T07:05:47.2166930Z             avg_fn (function, optional): the averaging function used to update
2025-07-17T07:05:47.2167060Z                 parameters; the function must take in the current value of the
2025-07-17T07:05:47.2167190Z                 :class:`AveragedModel` parameter, the current value of :attr:`model`
2025-07-17T07:05:47.2167310Z                 parameter, and the number of models already averaged; if None,
2025-07-17T07:05:47.2167460Z                 an equally weighted average is used (default: None)
2025-07-17T07:05:47.2167600Z             multi_avg_fn (function, optional): the averaging function used to update
2025-07-17T07:05:47.2167760Z                 parameters inplace; the function must take in the current values of the
2025-07-17T07:05:47.2167930Z                 :class:`AveragedModel` parameters as a list, the current values of :attr:`model`
2025-07-17T07:05:47.2168060Z                 parameters as a list, and the number of models already averaged; if None,
2025-07-17T07:05:47.2168160Z                 an equally weighted average is used (default: None)
2025-07-17T07:05:47.2168280Z             use_buffers (bool): if ``True``, it will compute running averages for
2025-07-17T07:05:47.2168420Z                 both the parameters and the buffers of the model. (default: ``False``)
2025-07-17T07:05:47.2168450Z     
2025-07-17T07:05:47.2168520Z         Example:
2025-07-17T07:05:47.2168620Z             >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:47.2168700Z             >>> loader, optimizer, model, loss_fn = ...
2025-07-17T07:05:47.2168800Z             >>> swa_model = torch.optim.swa_utils.AveragedModel(model)
2025-07-17T07:05:47.2168940Z             >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer,
2025-07-17T07:05:47.2169010Z             >>>                                     T_max=300)
2025-07-17T07:05:47.2169070Z             >>> swa_start = 160
2025-07-17T07:05:47.2169150Z             >>> swa_scheduler = SWALR(optimizer, swa_lr=0.05)
2025-07-17T07:05:47.2169210Z             >>> for i in range(300):
2025-07-17T07:05:47.2169280Z             >>>      for input, target in loader:
2025-07-17T07:05:47.2169340Z             >>>          optimizer.zero_grad()
2025-07-17T07:05:47.2169420Z             >>>          loss_fn(model(input), target).backward()
2025-07-17T07:05:47.2169480Z             >>>          optimizer.step()
2025-07-17T07:05:47.2169540Z             >>>      if i > swa_start:
2025-07-17T07:05:47.2169620Z             >>>          swa_model.update_parameters(model)
2025-07-17T07:05:47.2169690Z             >>>          swa_scheduler.step()
2025-07-17T07:05:47.2169730Z             >>>      else:
2025-07-17T07:05:47.2169790Z             >>>          scheduler.step()
2025-07-17T07:05:47.2169840Z             >>>
2025-07-17T07:05:47.2169930Z             >>> # Update bn statistics for the swa_model at the end
2025-07-17T07:05:47.2170030Z             >>> torch.optim.swa_utils.update_bn(loader, swa_model)
2025-07-17T07:05:47.2170070Z     
2025-07-17T07:05:47.2170250Z         You can also use custom averaging functions with the `avg_fn` or `multi_avg_fn` parameters.
2025-07-17T07:05:47.2170360Z         If no averaging function is provided, the default is to compute
2025-07-17T07:05:47.2170450Z         equally-weighted average of the weights (SWA).
2025-07-17T07:05:47.2170490Z     
2025-07-17T07:05:47.2170540Z         Example:
2025-07-17T07:05:47.2170620Z             >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:47.2170750Z             >>> # Compute exponential moving averages of the weights and buffers
2025-07-17T07:05:47.2170850Z             >>> ema_model = torch.optim.swa_utils.AveragedModel(model,
2025-07-17T07:05:47.2170980Z             >>>             torch.optim.swa_utils.get_ema_multi_avg_fn(0.9), use_buffers=True)
2025-07-17T07:05:47.2171020Z     
2025-07-17T07:05:47.2171070Z         .. note::
2025-07-17T07:05:47.2171200Z             When using SWA/EMA with models containing Batch Normalization you may
2025-07-17T07:05:47.2171320Z             need to update the activation statistics for Batch Normalization.
2025-07-17T07:05:47.2171460Z             This can be done either by using the :meth:`torch.optim.swa_utils.update_bn`
2025-07-17T07:05:47.2171600Z             or by setting :attr:`use_buffers` to `True`. The first approach updates the
2025-07-17T07:05:47.2171740Z             statistics in a post-training step by passing data through the model. The
2025-07-17T07:05:47.2171910Z             second does it during the parameter update phase by averaging all buffers.
2025-07-17T07:05:47.2172050Z             Empirical evidence has shown that updating the statistics in normalization
2025-07-17T07:05:47.2172220Z             layers increases accuracy, but you may wish to empirically test which
2025-07-17T07:05:47.2172320Z             approach yields the best results in your problem.
2025-07-17T07:05:47.2172350Z     
2025-07-17T07:05:47.2172400Z         .. note::
2025-07-17T07:05:47.2172550Z             :attr:`avg_fn` and `multi_avg_fn` are not saved in the :meth:`state_dict` of the model.
2025-07-17T07:05:47.2172590Z     
2025-07-17T07:05:47.2172640Z         .. note::
2025-07-17T07:05:47.2172760Z             When :meth:`update_parameters` is called for the first time (i.e.
2025-07-17T07:05:47.2172870Z             :attr:`n_averaged` is `0`) the parameters of `model` are copied
2025-07-17T07:05:47.2173010Z             to the parameters of :class:`AveragedModel`. For every subsequent
2025-07-17T07:05:47.2173140Z             call of :meth:`update_parameters` the function `avg_fn` is used
2025-07-17T07:05:47.2173200Z             to update the parameters.
2025-07-17T07:05:47.2173240Z     
2025-07-17T07:05:47.2173370Z         .. _Averaging Weights Leads to Wider Optima and Better Generalization:
2025-07-17T07:05:47.2173440Z             https://arxiv.org/abs/1803.05407
2025-07-17T07:05:47.2173590Z         .. _There Are Many Consistent Explanations of Unlabeled Data: Why You Should
2025-07-17T07:05:47.2173630Z             Average:
2025-07-17T07:05:47.2173700Z             https://arxiv.org/abs/1806.05594
2025-07-17T07:05:47.2173820Z         .. _SWALP: Stochastic Weight Averaging in Low-Precision Training:
2025-07-17T07:05:47.2173890Z             https://arxiv.org/abs/1904.11943
2025-07-17T07:05:47.2174020Z         .. _Stochastic Weight Averaging in Parallel: Large-Batch Training That
2025-07-17T07:05:47.2174080Z             Generalizes Well:
2025-07-17T07:05:47.2174150Z             https://arxiv.org/abs/2001.02312
2025-07-17T07:05:47.2174200Z         .. _Polyak averaging:
2025-07-17T07:05:47.2174300Z             https://paperswithcode.com/method/polyak-averaging
2025-07-17T07:05:47.2174340Z         
2025-07-17T07:05:47.2174490Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2174530Z     
2025-07-17T07:05:47.2174580Z       warnings.warn(msg)
2025-07-17T07:05:47.2174620Z     
2025-07-17T07:05:47.2174730Z --- Parse Warning: 105 / 136 ---
2025-07-17T07:05:47.2175350Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SWALR in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/swa_utils.py line=375.
2025-07-17T07:05:47.2175510Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2175640Z     Anneals the learning rate in each parameter group to a fixed value.
2025-07-17T07:05:47.2175680Z     
2025-07-17T07:05:47.2175820Z         This learning rate scheduler is meant to be used with Stochastic Weight
2025-07-17T07:05:47.2175950Z         Averaging (SWA) method (see `torch.optim.swa_utils.AveragedModel`).
2025-07-17T07:05:47.2175990Z     
2025-07-17T07:05:47.2176030Z         Args:
2025-07-17T07:05:47.2176140Z             optimizer (torch.optim.Optimizer): wrapped optimizer
2025-07-17T07:05:47.2176260Z             swa_lrs (float or list): the learning rate value for all param groups
2025-07-17T07:05:47.2176340Z                 together or separately for each group.
2025-07-17T07:05:47.2176460Z             annealing_epochs (int): number of epochs in the annealing phase
2025-07-17T07:05:47.2176520Z                 (default: 10)
2025-07-17T07:05:47.2176640Z             annealing_strategy (str): "cos" or "linear"; specifies the annealing
2025-07-17T07:05:47.2176770Z                 strategy: "cos" for cosine annealing, "linear" for linear annealing
2025-07-17T07:05:47.2176850Z                 (default: "cos")
2025-07-17T07:05:47.2176960Z             last_epoch (int): the index of the last epoch (default: -1)
2025-07-17T07:05:47.2177000Z     
2025-07-17T07:05:47.2177140Z         The :class:`SWALR` scheduler can be used together with other
2025-07-17T07:05:47.2177270Z         schedulers to switch to a constant learning rate late in the training
2025-07-17T07:05:47.2177320Z         as in the example below.
2025-07-17T07:05:47.2177360Z     
2025-07-17T07:05:47.2177400Z         Example:
2025-07-17T07:05:47.2177480Z             >>> # xdoctest: +SKIP("Undefined variables")
2025-07-17T07:05:47.2177550Z             >>> loader, optimizer, model = ...
2025-07-17T07:05:47.2177620Z             >>> lr_lambda = lambda epoch: 0.9
2025-07-17T07:05:47.2177750Z             >>> scheduler = torch.optim.lr_scheduler.MultiplicativeLR(optimizer,
2025-07-17T07:05:47.2177840Z             >>>        lr_lambda=lr_lambda)
2025-07-17T07:05:47.2177970Z             >>> swa_scheduler = torch.optim.swa_utils.SWALR(optimizer,
2025-07-17T07:05:47.2178090Z             >>>        anneal_strategy="linear", anneal_epochs=20, swa_lr=0.05)
2025-07-17T07:05:47.2178140Z             >>> swa_start = 160
2025-07-17T07:05:47.2178200Z             >>> for i in range(300):
2025-07-17T07:05:47.2178260Z             >>>      for input, target in loader:
2025-07-17T07:05:47.2178330Z             >>>          optimizer.zero_grad()
2025-07-17T07:05:47.2178410Z             >>>          loss_fn(model(input), target).backward()
2025-07-17T07:05:47.2178470Z             >>>          optimizer.step()
2025-07-17T07:05:47.2178530Z             >>>      if i > swa_start:
2025-07-17T07:05:47.2178590Z             >>>          swa_scheduler.step()
2025-07-17T07:05:47.2178640Z             >>>      else:
2025-07-17T07:05:47.2178700Z             >>>          scheduler.step()
2025-07-17T07:05:47.2178740Z     
2025-07-17T07:05:47.2178870Z         .. _Averaging Weights Leads to Wider Optima and Better Generalization:
2025-07-17T07:05:47.2178940Z             https://arxiv.org/abs/1803.05407
2025-07-17T07:05:47.2178980Z         
2025-07-17T07:05:47.2179130Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2179170Z     
2025-07-17T07:05:47.2179230Z       warnings.warn(msg)
2025-07-17T07:05:47.2179260Z     
2025-07-17T07:05:47.2179360Z --- Parse Warning: 106 / 136 ---
2025-07-17T07:05:47.2180040Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Optimizer.load_state_dict in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/optim/optimizer.py line=867.
2025-07-17T07:05:47.2180190Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2180250Z     Load the optimizer state.
2025-07-17T07:05:47.2180290Z     
2025-07-17T07:05:47.2180330Z             Args:
2025-07-17T07:05:47.2180450Z                 state_dict (dict): optimizer state. Should be an object returned
2025-07-17T07:05:47.2180520Z                     from a call to :meth:`state_dict`.
2025-07-17T07:05:47.2180560Z     
2025-07-17T07:05:47.2180620Z             .. warning::
2025-07-17T07:05:47.2180820Z                 Make sure this method is called after initializing :class:`torch.optim.lr_scheduler.LRScheduler`,
2025-07-17T07:05:47.2180950Z                 as calling it beforehand will overwrite the loaded learning rates.
2025-07-17T07:05:47.2180980Z     
2025-07-17T07:05:47.2181030Z             .. note::
2025-07-17T07:05:47.2181200Z                 The names of the parameters (if they exist under the "param_names" key of each param group
2025-07-17T07:05:47.2181310Z                 in :meth:`state_dict`) will not affect the loading process.
2025-07-17T07:05:47.2181500Z                 To use the parameters' names for custom cases (such as when the parameters in the loaded state dict
2025-07-17T07:05:47.2181650Z                 differ from those initialized in the optimizer),
2025-07-17T07:05:47.2181830Z                 a custom ``register_load_state_dict_pre_hook`` should be implemented to adapt the loaded dict
2025-07-17T07:05:47.2181890Z                 accordingly.
2025-07-17T07:05:47.2182120Z                 If ``param_names`` exist in loaded state dict ``param_groups`` they will be saved and override
2025-07-17T07:05:47.2182310Z                 the current names, if present, in the optimizer state. If they do not exist in loaded state dict,
2025-07-17T07:05:47.2182410Z                 the optimizer ``param_names`` will remain unchanged.
2025-07-17T07:05:47.2182440Z     
2025-07-17T07:05:47.2182490Z             Example:
2025-07-17T07:05:47.2182550Z                 >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2182620Z                 >>> model = torch.nn.Linear(10, 10)
2025-07-17T07:05:47.2182800Z                 >>> optim = torch.optim.SGD(model.parameters(), lr=3e-4)
2025-07-17T07:05:47.2182930Z                 >>> scheduler1 = torch.optim.lr_scheduler.LinearLR(
2025-07-17T07:05:47.2182980Z                 ...     optim,
2025-07-17T07:05:47.2183040Z                 ...     start_factor=0.1,
2025-07-17T07:05:47.2183090Z                 ...     end_factor=1,
2025-07-17T07:05:47.2183150Z                 ...     total_iters=20,
2025-07-17T07:05:47.2183190Z                 ... )
2025-07-17T07:05:47.2183310Z                 >>> scheduler2 = torch.optim.lr_scheduler.CosineAnnealingLR(
2025-07-17T07:05:47.2183360Z                 ...     optim,
2025-07-17T07:05:47.2183410Z                 ...     T_max=80,
2025-07-17T07:05:47.2183460Z                 ...     eta_min=3e-5,
2025-07-17T07:05:47.2183500Z                 ... )
2025-07-17T07:05:47.2183590Z                 >>> lr = torch.optim.lr_scheduler.SequentialLR(
2025-07-17T07:05:47.2183640Z                 ...     optim,
2025-07-17T07:05:47.2183720Z                 ...     schedulers=[scheduler1, scheduler2],
2025-07-17T07:05:47.2183780Z                 ...     milestones=[20],
2025-07-17T07:05:47.2183830Z                 ... )
2025-07-17T07:05:47.2183920Z                 >>> lr.load_state_dict(torch.load("./save_seq.pt"))
2025-07-17T07:05:47.2184040Z                 >>> # now load the optimizer checkpoint after loading the LRScheduler
2025-07-17T07:05:47.2184140Z                 >>> optim.load_state_dict(torch.load("./save_optim.pt"))
2025-07-17T07:05:47.2184190Z     
2025-07-17T07:05:47.2184230Z             
2025-07-17T07:05:47.2184380Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2184410Z     
2025-07-17T07:05:47.2184470Z       warnings.warn(msg)
2025-07-17T07:05:47.2184510Z     
2025-07-17T07:05:47.2184610Z --- Parse Warning: 107 / 136 ---
2025-07-17T07:05:47.2185310Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SelectiveCheckpointContext in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/checkpoint.py line=1218.
2025-07-17T07:05:47.2185470Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2185510Z     
2025-07-17T07:05:47.2185640Z     Context passed to policy function during selective checkpointing.
2025-07-17T07:05:47.2185680Z     
2025-07-17T07:05:47.2185810Z     This class is used to pass relevant metadata to the policy function during
2025-07-17T07:05:47.2185970Z     selective checkpointing. The metadata includes whether the current invocation
2025-07-17T07:05:47.2186070Z     of the policy function is during recomputation or not.
2025-07-17T07:05:47.2186110Z     
2025-07-17T07:05:47.2186150Z     Example:
2025-07-17T07:05:47.2186210Z         >>> # xdoctest: +SKIP(stub)
2025-07-17T07:05:47.2186250Z         >>>
2025-07-17T07:05:47.2186320Z         >>> def policy_fn(ctx, op, *args, **kwargs):
2025-07-17T07:05:47.2186380Z         >>>    print(ctx.is_recompute)
2025-07-17T07:05:47.2186430Z         >>>
2025-07-17T07:05:47.2186620Z         >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn)
2025-07-17T07:05:47.2186670Z         >>>
2025-07-17T07:05:47.2186750Z         >>> out = torch.utils.checkpoint.checkpoint(
2025-07-17T07:05:47.2186820Z         >>>     fn, x, y,
2025-07-17T07:05:47.2186880Z         >>>     use_reentrant=False,
2025-07-17T07:05:47.2186930Z         >>>     context_fn=context_fn,
2025-07-17T07:05:47.2186980Z         >>> )
2025-07-17T07:05:47.2187010Z     
2025-07-17T07:05:47.2187160Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2187200Z     
2025-07-17T07:05:47.2187250Z       warnings.warn(msg)
2025-07-17T07:05:47.2187290Z     
2025-07-17T07:05:47.2187390Z --- Parse Warning: 108 / 136 ---
2025-07-17T07:05:47.2188120Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=create_selective_checkpoint_contexts in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/checkpoint.py line=1358.
2025-07-17T07:05:47.2188300Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2188340Z     
2025-07-17T07:05:47.2188480Z     Helper to avoid recomputing certain ops during activation checkpointing.
2025-07-17T07:05:47.2188530Z     
2025-07-17T07:05:47.2188660Z     Use this with `torch.utils.checkpoint.checkpoint` to control which
2025-07-17T07:05:47.2188750Z     operations are recomputed during the backward pass.
2025-07-17T07:05:47.2188790Z     
2025-07-17T07:05:47.2188830Z     Args:
2025-07-17T07:05:47.2188900Z         policy_fn_or_list (Callable or List):
2025-07-17T07:05:47.2189000Z           - If a policy function is provided, it should accept a
2025-07-17T07:05:47.2189140Z             :class:`SelectiveCheckpointContext`, the :class:`OpOverload`, args and
2025-07-17T07:05:47.2189280Z             kwargs to the op, and return a :class:`CheckpointPolicy` enum value
2025-07-17T07:05:47.2189420Z             indicating whether the execution of the op should be recomputed or not.
2025-07-17T07:05:47.2189550Z           - If a list of operations is provided, it is equivalent to a policy
2025-07-17T07:05:47.2189660Z             returning `CheckpointPolicy.MUST_SAVE` for the specified
2025-07-17T07:05:47.2189790Z             operations and `CheckpointPolicy.PREFER_RECOMPUTE` for all other
2025-07-17T07:05:47.2189840Z             operations.
2025-07-17T07:05:47.2189970Z         allow_cache_entry_mutation (bool, optional): By default, an error is
2025-07-17T07:05:47.2190090Z             raised if any tensors cached by selective activation checkpoint are
2025-07-17T07:05:47.2190220Z             mutated in order to ensure correctness. If set to `True`, this check
2025-07-17T07:05:47.2190270Z             is disabled.
2025-07-17T07:05:47.2190310Z     Returns:
2025-07-17T07:05:47.2190370Z         A tuple of two context managers.
2025-07-17T07:05:47.2190410Z     
2025-07-17T07:05:47.2190460Z     Example:
2025-07-17T07:05:47.2190520Z         >>> # xdoctest: +REQUIRES(LINUX)
2025-07-17T07:05:47.2190570Z         >>> import functools
2025-07-17T07:05:47.2190610Z         >>>
2025-07-17T07:05:47.2190690Z         >>> x = torch.rand(10, 10, requires_grad=True)
2025-07-17T07:05:47.2190760Z         >>> y = torch.rand(10, 10, requires_grad=True)
2025-07-17T07:05:47.2190800Z         >>>
2025-07-17T07:05:47.2190850Z         >>> ops_to_save = [
2025-07-17T07:05:47.2190910Z         >>>    torch.ops.aten.mm.default,
2025-07-17T07:05:47.2190950Z         >>> ]
2025-07-17T07:05:47.2190990Z         >>>
2025-07-17T07:05:47.2191070Z         >>> def policy_fn(ctx, op, *args, **kwargs):
2025-07-17T07:05:47.2191120Z         >>>    if op in ops_to_save:
2025-07-17T07:05:47.2191200Z         >>>        return CheckpointPolicy.MUST_SAVE
2025-07-17T07:05:47.2191240Z         >>>    else:
2025-07-17T07:05:47.2191330Z         >>>        return CheckpointPolicy.PREFER_RECOMPUTE
2025-07-17T07:05:47.2191390Z         >>>
2025-07-17T07:05:47.2191560Z         >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn)
2025-07-17T07:05:47.2191600Z         >>>
2025-07-17T07:05:47.2191680Z         >>> # or equivalently
2025-07-17T07:05:47.2191850Z         >>> context_fn = functools.partial(create_selective_checkpoint_contexts, ops_to_save)
2025-07-17T07:05:47.2191890Z         >>>
2025-07-17T07:05:47.2191940Z         >>> def fn(x, y):
2025-07-17T07:05:47.2192060Z         >>>     return torch.sigmoid(torch.matmul(torch.matmul(x, y), y)) * y
2025-07-17T07:05:47.2192100Z         >>>
2025-07-17T07:05:47.2192190Z         >>> out = torch.utils.checkpoint.checkpoint(
2025-07-17T07:05:47.2192230Z         >>>     fn, x, y,
2025-07-17T07:05:47.2192290Z         >>>     use_reentrant=False,
2025-07-17T07:05:47.2192350Z         >>>     context_fn=context_fn,
2025-07-17T07:05:47.2192390Z         >>> )
2025-07-17T07:05:47.2192450Z     
2025-07-17T07:05:47.2192610Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2192650Z     
2025-07-17T07:05:47.2192710Z       warnings.warn(msg)
2025-07-17T07:05:47.2192740Z     
2025-07-17T07:05:47.2192850Z --- Parse Warning: 109 / 136 ---
2025-07-17T07:05:47.2193540Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ThroughputBenchmark in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/throughput_benchmark.py line=61.
2025-07-17T07:05:47.2193700Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2193740Z     
2025-07-17T07:05:47.2193920Z     This class is a wrapper around a c++ component throughput_benchmark::ThroughputBenchmark.
2025-07-17T07:05:47.2193960Z     
2025-07-17T07:05:47.2194130Z     This wrapper on the throughput_benchmark::ThroughputBenchmark component is responsible
2025-07-17T07:05:47.2194280Z     for executing a PyTorch module (nn.Module or ScriptModule) under an inference
2025-07-17T07:05:47.2194420Z     server like load. It can emulate multiple calling threads to a single module
2025-07-17T07:05:47.2194560Z     provided. In the future we plan to enhance this component to support inter and
2025-07-17T07:05:47.2194700Z     intra-op parallelism as well as multiple models running in a single process.
2025-07-17T07:05:47.2194740Z     
2025-07-17T07:05:47.2194890Z     Please note that even though nn.Module is supported, it might incur an overhead
2025-07-17T07:05:47.2195030Z     from the need to hold GIL every time we execute Python code or pass around
2025-07-17T07:05:47.2195170Z     inputs as Python objects. As soon as you have a ScriptModule version of your
2025-07-17T07:05:47.2195310Z     model for inference deployment it is better to switch to using it in this
2025-07-17T07:05:47.2195360Z     benchmark.
2025-07-17T07:05:47.2195400Z     
2025-07-17T07:05:47.2195440Z     Example::
2025-07-17T07:05:47.2195490Z     
2025-07-17T07:05:47.2195560Z         >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:47.2195640Z         >>> from torch.utils import ThroughputBenchmark
2025-07-17T07:05:47.2195720Z         >>> bench = ThroughputBenchmark(my_module)
2025-07-17T07:05:47.2195810Z         >>> # Pre-populate benchmark's data set with the inputs
2025-07-17T07:05:47.2195870Z         >>> for input in inputs:
2025-07-17T07:05:47.2196000Z         ...     # Both args and kwargs work, same as any PyTorch Module / ScriptModule
2025-07-17T07:05:47.2196080Z         ...     bench.add_input(input[0], x2=input[1])
2025-07-17T07:05:47.2196200Z         >>> # Inputs supplied above are randomly used during the execution
2025-07-17T07:05:47.2196260Z         >>> stats = bench.benchmark(
2025-07-17T07:05:47.2196310Z         ...     num_calling_threads=4,
2025-07-17T07:05:47.2196370Z         ...     num_warmup_iters = 100,
2025-07-17T07:05:47.2196420Z         ...     num_iters = 1000,
2025-07-17T07:05:47.2196500Z         ... )
2025-07-17T07:05:47.2196610Z         >>> print("Avg latency (ms): {}".format(stats.latency_avg_ms))
2025-07-17T07:05:47.2196720Z         >>> print("Number of iterations: {}".format(stats.num_iters))
2025-07-17T07:05:47.2196780Z     
2025-07-17T07:05:47.2196930Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2196970Z     
2025-07-17T07:05:47.2197030Z       warnings.warn(msg)
2025-07-17T07:05:47.2197070Z     
2025-07-17T07:05:47.2197170Z --- Parse Warning: 110 / 136 ---
2025-07-17T07:05:47.2197830Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_pytree_node in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/_cxx_pytree.py line=134.
2025-07-17T07:05:47.2198010Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2198130Z     Register a container-like type as pytree node.
2025-07-17T07:05:47.2198170Z     
2025-07-17T07:05:47.2198210Z         Args:
2025-07-17T07:05:47.2198320Z             cls (type): A Python type to treat as an internal pytree node.
2025-07-17T07:05:47.2198490Z             flatten_fn (callable): A function to be used during flattening, taking an instance of
2025-07-17T07:05:47.2198640Z                 ``cls`` and returning a pair, with (1) an iterable for the children to be flattened
2025-07-17T07:05:47.2198820Z                 recursively, and (2) some hashable auxiliary data to be stored in the treespec and to be
2025-07-17T07:05:47.2198890Z                 passed to the ``unflatten_fn``.
2025-07-17T07:05:47.2199050Z             unflatten_fn (callable): A function taking two arguments: the auxiliary data that was
2025-07-17T07:05:47.2199210Z                 returned by ``flatten_fn`` and stored in the treespec, and the unflattened children.
2025-07-17T07:05:47.2199310Z                 The function should return an instance of ``cls``.
2025-07-17T07:05:47.2199470Z             serialized_type_name (str, optional): A keyword argument used to specify the fully
2025-07-17T07:05:47.2199570Z                 qualified name used when serializing the tree spec.
2025-07-17T07:05:47.2199750Z             to_dumpable_context (callable, optional): An optional keyword argument to custom specify how
2025-07-17T07:05:47.2199920Z                 to convert the context of the pytree to a custom json dumpable representation. This is
2025-07-17T07:05:47.2200080Z                 used for json serialization, which is being used in :mod:`torch.export` right now.
2025-07-17T07:05:47.2200260Z             from_dumpable_context (callable, optional): An optional keyword argument to custom specify
2025-07-17T07:05:47.2200420Z                 how to convert the custom json dumpable representation of the context back to the
2025-07-17T07:05:47.2200570Z                 original context. This is used for json deserialization, which is being used in
2025-07-17T07:05:47.2200650Z                 :mod:`torch.export` right now.
2025-07-17T07:05:47.2200690Z     
2025-07-17T07:05:47.2200730Z         Example::
2025-07-17T07:05:47.2200770Z     
2025-07-17T07:05:47.2200830Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2200920Z             >>> # Registry a Python type with lambda functions
2025-07-17T07:05:47.2200980Z             >>> register_pytree_node(
2025-07-17T07:05:47.2201020Z             ...     set,
2025-07-17T07:05:47.2201100Z             ...     lambda s: (sorted(s), None, None),
2025-07-17T07:05:47.2201170Z             ...     lambda children, _: set(children),
2025-07-17T07:05:47.2201210Z             ... )
2025-07-17T07:05:47.2201250Z         
2025-07-17T07:05:47.2201400Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2201440Z     
2025-07-17T07:05:47.2201490Z       warnings.warn(msg)
2025-07-17T07:05:47.2201530Z     
2025-07-17T07:05:47.2201650Z --- Parse Warning: 111 / 136 ---
2025-07-17T07:05:47.2202310Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CppExtension in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1147.
2025-07-17T07:05:47.2202490Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2202530Z     
2025-07-17T07:05:47.2202620Z     Create a :class:`setuptools.Extension` for C++.
2025-07-17T07:05:47.2202660Z     
2025-07-17T07:05:47.2202800Z     Convenience method that creates a :class:`setuptools.Extension` with the
2025-07-17T07:05:47.2202940Z     bare minimum (but often sufficient) arguments to build a C++ extension.
2025-07-17T07:05:47.2202980Z     
2025-07-17T07:05:47.2203100Z     All arguments are forwarded to the :class:`setuptools.Extension`
2025-07-17T07:05:47.2203210Z     constructor. Full list arguments can be found at
2025-07-17T07:05:47.2203430Z     https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference
2025-07-17T07:05:47.2203470Z     
2025-07-17T07:05:47.2203510Z     .. warning::
2025-07-17T07:05:47.2203650Z         The PyTorch python API (as provided in libtorch_python) cannot be built
2025-07-17T07:05:47.2203780Z         with the flag ``py_limited_api=True``.  When this flag is passed, it is
2025-07-17T07:05:47.2203900Z         the user's responsibility in their library to not use APIs from
2025-07-17T07:05:47.2204040Z         libtorch_python (in particular pytorch/python bindings) and to only use
2025-07-17T07:05:47.2204170Z         APIs from libtorch (aten objects, operators and the dispatcher). For
2025-07-17T07:05:47.2204300Z         example, to give access to custom ops from python, the library should
2025-07-17T07:05:47.2204370Z         register the ops through the dispatcher.
2025-07-17T07:05:47.2204410Z     
2025-07-17T07:05:47.2204550Z         Contrary to CPython setuptools, who does not define -DPy_LIMITED_API
2025-07-17T07:05:47.2204670Z         as a compile flag when py_limited_api is specified as an option for
2025-07-17T07:05:47.2204800Z         the "bdist_wheel" command in ``setup``, PyTorch does! We will specify
2025-07-17T07:05:47.2204930Z         -DPy_LIMITED_API=min_supported_cpython to best enforce consistency,
2025-07-17T07:05:47.2205060Z         safety, and sanity in order to encourage best practices. To target a
2025-07-17T07:05:47.2205190Z         different version, set min_supported_cpython to the hexcode of the
2025-07-17T07:05:47.2205240Z         CPython version of choice.
2025-07-17T07:05:47.2205280Z     
2025-07-17T07:05:47.2205330Z     Example:
2025-07-17T07:05:47.2205380Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2205470Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-07-17T07:05:47.2205530Z         >>> from setuptools import setup
2025-07-17T07:05:47.2205670Z         >>> from torch.utils.cpp_extension import BuildExtension, CppExtension
2025-07-17T07:05:47.2205710Z         >>> setup(
2025-07-17T07:05:47.2205770Z         ...     name='extension',
2025-07-17T07:05:47.2205820Z         ...     ext_modules=[
2025-07-17T07:05:47.2205870Z         ...         CppExtension(
2025-07-17T07:05:47.2205930Z         ...             name='extension',
2025-07-17T07:05:47.2206000Z         ...             sources=['extension.cpp'],
2025-07-17T07:05:47.2206070Z         ...             extra_compile_args=['-g'],
2025-07-17T07:05:47.2206160Z         ...             extra_link_args=['-Wl,--no-as-needed', '-lm'])
2025-07-17T07:05:47.2206210Z         ...     ],
2025-07-17T07:05:47.2206260Z         ...     cmdclass={
2025-07-17T07:05:47.2206320Z         ...         'build_ext': BuildExtension
2025-07-17T07:05:47.2206360Z         ...     })
2025-07-17T07:05:47.2206400Z     
2025-07-17T07:05:47.2206550Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2206590Z     
2025-07-17T07:05:47.2206650Z       warnings.warn(msg)
2025-07-17T07:05:47.2206710Z     
2025-07-17T07:05:47.2206820Z --- Parse Warning: 112 / 136 ---
2025-07-17T07:05:47.2210930Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CUDAExtension in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1217.
2025-07-17T07:05:47.2211180Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2211220Z     
2025-07-17T07:05:47.2211310Z     Create a :class:`setuptools.Extension` for CUDA/C++.
2025-07-17T07:05:47.2211360Z     
2025-07-17T07:05:47.2211500Z     Convenience method that creates a :class:`setuptools.Extension` with the
2025-07-17T07:05:47.2211620Z     bare minimum (but often sufficient) arguments to build a CUDA/C++
2025-07-17T07:05:47.2211790Z     extension. This includes the CUDA include path, library path and runtime
2025-07-17T07:05:47.2211860Z     library.
2025-07-17T07:05:47.2211900Z     
2025-07-17T07:05:47.2212020Z     All arguments are forwarded to the :class:`setuptools.Extension`
2025-07-17T07:05:47.2212110Z     constructor. Full list arguments can be found at
2025-07-17T07:05:47.2212310Z     https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference
2025-07-17T07:05:47.2212350Z     
2025-07-17T07:05:47.2212400Z     .. warning::
2025-07-17T07:05:47.2212540Z         The PyTorch python API (as provided in libtorch_python) cannot be built
2025-07-17T07:05:47.2212660Z         with the flag ``py_limited_api=True``.  When this flag is passed, it is
2025-07-17T07:05:47.2212780Z         the user's responsibility in their library to not use APIs from
2025-07-17T07:05:47.2212920Z         libtorch_python (in particular pytorch/python bindings) and to only use
2025-07-17T07:05:47.2213050Z         APIs from libtorch (aten objects, operators and the dispatcher). For
2025-07-17T07:05:47.2213180Z         example, to give access to custom ops from python, the library should
2025-07-17T07:05:47.2213260Z         register the ops through the dispatcher.
2025-07-17T07:05:47.2213300Z     
2025-07-17T07:05:47.2213430Z         Contrary to CPython setuptools, who does not define -DPy_LIMITED_API
2025-07-17T07:05:47.2213560Z         as a compile flag when py_limited_api is specified as an option for
2025-07-17T07:05:47.2213680Z         the "bdist_wheel" command in ``setup``, PyTorch does! We will specify
2025-07-17T07:05:47.2213810Z         -DPy_LIMITED_API=min_supported_cpython to best enforce consistency,
2025-07-17T07:05:47.2213940Z         safety, and sanity in order to encourage best practices. To target a
2025-07-17T07:05:47.2214070Z         different version, set min_supported_cpython to the hexcode of the
2025-07-17T07:05:47.2214120Z         CPython version of choice.
2025-07-17T07:05:47.2214160Z     
2025-07-17T07:05:47.2214210Z     Example:
2025-07-17T07:05:47.2214260Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2214350Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-07-17T07:05:47.2214420Z         >>> from setuptools import setup
2025-07-17T07:05:47.2214550Z         >>> from torch.utils.cpp_extension import BuildExtension, CUDAExtension
2025-07-17T07:05:47.2214600Z         >>> setup(
2025-07-17T07:05:47.2214660Z         ...     name='cuda_extension',
2025-07-17T07:05:47.2214710Z         ...     ext_modules=[
2025-07-17T07:05:47.2214760Z         ...         CUDAExtension(
2025-07-17T07:05:47.2214830Z         ...                 name='cuda_extension',
2025-07-17T07:05:47.2214930Z         ...                 sources=['extension.cpp', 'extension_kernel.cu'],
2025-07-17T07:05:47.2215010Z         ...                 extra_compile_args={'cxx': ['-g'],
2025-07-17T07:05:47.2215090Z         ...                                     'nvcc': ['-O2']},
2025-07-17T07:05:47.2215180Z         ...                 extra_link_args=['-Wl,--no-as-needed', '-lcuda'])
2025-07-17T07:05:47.2215230Z         ...     ],
2025-07-17T07:05:47.2215300Z         ...     cmdclass={
2025-07-17T07:05:47.2215370Z         ...         'build_ext': BuildExtension
2025-07-17T07:05:47.2215420Z         ...     })
2025-07-17T07:05:47.2215490Z     
2025-07-17T07:05:47.2215540Z     Compute capabilities:
2025-07-17T07:05:47.2215580Z     
2025-07-17T07:05:47.2215760Z     By default the extension will be compiled to run on all archs of the cards visible during the
2025-07-17T07:05:47.2215930Z     building process of the extension, plus PTX. If down the road a new card is installed the
2025-07-17T07:05:47.2216110Z     extension may need to be recompiled. If a visible card has a compute capability (CC) that's
2025-07-17T07:05:47.2216290Z     newer than the newest version for which your nvcc can build fully-compiled binaries, PyTorch
2025-07-17T07:05:47.2216450Z     will make nvcc fall back to building kernels with the newest version of PTX your nvcc does
2025-07-17T07:05:47.2216540Z     support (see below for details on PTX).
2025-07-17T07:05:47.2216600Z     
2025-07-17T07:05:47.2216780Z     You can override the default behavior using `TORCH_CUDA_ARCH_LIST` to explicitly specify which
2025-07-17T07:05:47.2216850Z     CCs you want the extension to support:
2025-07-17T07:05:47.2216890Z     
2025-07-17T07:05:47.2217010Z     ``TORCH_CUDA_ARCH_LIST="6.1 8.6" python build_my_extension.py``
2025-07-17T07:05:47.2217150Z     ``TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" python build_my_extension.py``
2025-07-17T07:05:47.2217190Z     
2025-07-17T07:05:47.2217380Z     The +PTX option causes extension kernel binaries to include PTX instructions for the specified
2025-07-17T07:05:47.2217570Z     CC. PTX is an intermediate representation that allows kernels to runtime-compile for any CC >=
2025-07-17T07:05:47.2217740Z     the specified CC (for example, 8.6+PTX generates PTX that can runtime-compile for any GPU with
2025-07-17T07:05:47.2217920Z     CC >= 8.6). This improves your binary's forward compatibility. However, relying on older PTX to
2025-07-17T07:05:47.2218110Z     provide forward compat by runtime-compiling for newer CCs can modestly reduce performance on
2025-07-17T07:05:47.2218270Z     those newer CCs. If you know exact CC(s) of the GPUs you want to target, you're always better
2025-07-17T07:05:47.2218470Z     off specifying them individually. For example, if you want your extension to run on 8.0 and 8.6,
2025-07-17T07:05:47.2218650Z     "8.0+PTX" would work functionally because it includes PTX that can runtime-compile for 8.6, but
2025-07-17T07:05:47.2218710Z     "8.0 8.6" would be better.
2025-07-17T07:05:47.2218750Z     
2025-07-17T07:05:47.2218920Z     Note that while it's possible to include all supported archs, the more archs get included the
2025-07-17T07:05:47.2219090Z     slower the building process will be, as it will build a separate kernel image for each arch.
2025-07-17T07:05:47.2219130Z     
2025-07-17T07:05:47.2219330Z     Note that CUDA-11.5 nvcc will hit internal compiler error while parsing torch/extension.h on Windows.
2025-07-17T07:05:47.2219460Z     To workaround the issue, move python binding logic to pure C++ file.
2025-07-17T07:05:47.2219500Z     
2025-07-17T07:05:47.2219550Z     Example use:
2025-07-17T07:05:47.2219600Z         #include <ATen/ATen.h>
2025-07-17T07:05:47.2219690Z         at::Tensor SigmoidAlphaBlendForwardCuda(....)
2025-07-17T07:05:47.2219730Z     
2025-07-17T07:05:47.2219770Z     Instead of:
2025-07-17T07:05:47.2219830Z         #include <torch/extension.h>
2025-07-17T07:05:47.2219930Z         torch::Tensor SigmoidAlphaBlendForwardCuda(...)
2025-07-17T07:05:47.2219970Z     
2025-07-17T07:05:47.2220130Z     Currently open issue for nvcc bug: https://github.com/pytorch/pytorch/issues/69460
2025-07-17T07:05:47.2220430Z     Complete workaround code example: https://github.com/facebookresearch/pytorch3d/commit/cb170ac024a949f1f9614ffe6af1c38d972f7d48
2025-07-17T07:05:47.2220470Z     
2025-07-17T07:05:47.2220530Z     Relocatable device code linking:
2025-07-17T07:05:47.2220570Z     
2025-07-17T07:05:47.2220750Z     If you want to reference device symbols across compilation units (across object files),
2025-07-17T07:05:47.2220910Z     the object files need to be built with `relocatable device code` (-rdc=true or -dc).
2025-07-17T07:05:47.2221150Z     An exception to this rule is "dynamic parallelism" (nested kernel launches)  which is not used a lot anymore.
2025-07-17T07:05:47.2221350Z     `Relocatable device code` is less optimized so it needs to be used only on object files that need it.
2025-07-17T07:05:47.2221540Z     Using `-dlto` (Device Link Time Optimization) at the device code compilation step and `dlink` step
2025-07-17T07:05:47.2221650Z     helps reduce the protentional perf degradation of `-rdc`.
2025-07-17T07:05:47.2221750Z     Note that it needs to be used at both steps to be useful.
2025-07-17T07:05:47.2221790Z     
2025-07-17T07:05:47.2222040Z     If you have `rdc` objects you need to have an extra `-dlink` (device linking) step before the CPU symbol linking step.
2025-07-17T07:05:47.2222170Z     There is also a case where `-dlink` is used without `-rdc`:
2025-07-17T07:05:47.2222330Z     when an extension is linked against a static lib containing rdc-compiled objects
2025-07-17T07:05:47.2222450Z     like the [NVSHMEM library](https://developer.nvidia.com/nvshmem).
2025-07-17T07:05:47.2222500Z     
2025-07-17T07:05:47.2222620Z     Note: Ninja is required to build a CUDA Extension with RDC linking.
2025-07-17T07:05:47.2222660Z     
2025-07-17T07:05:47.2222700Z     Example:
2025-07-17T07:05:47.2222750Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2222850Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-07-17T07:05:47.2222900Z         >>> CUDAExtension(
2025-07-17T07:05:47.2222960Z         ...        name='cuda_extension',
2025-07-17T07:05:47.2223060Z         ...        sources=['extension.cpp', 'extension_kernel.cu'],
2025-07-17T07:05:47.2223110Z         ...        dlink=True,
2025-07-17T07:05:47.2223180Z         ...        dlink_libraries=["dlink_lib"],
2025-07-17T07:05:47.2223260Z         ...        extra_compile_args={'cxx': ['-g'],
2025-07-17T07:05:47.2223330Z         ...                            'nvcc': ['-O2', '-rdc=true']})
2025-07-17T07:05:47.2223370Z     
2025-07-17T07:05:47.2223520Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2223560Z     
2025-07-17T07:05:47.2223620Z       warnings.warn(msg)
2025-07-17T07:05:47.2223650Z     
2025-07-17T07:05:47.2223780Z --- Parse Warning: 113 / 136 ---
2025-07-17T07:05:47.2224450Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyclExtension in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1408.
2025-07-17T07:05:47.2224600Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2224640Z     
2025-07-17T07:05:47.2224740Z     Creates a :class:`setuptools.Extension` for SYCL/C++.
2025-07-17T07:05:47.2224780Z     
2025-07-17T07:05:47.2224930Z     Convenience method that creates a :class:`setuptools.Extension` with the
2025-07-17T07:05:47.2225040Z     bare minimum (but often sufficient) arguments to build a SYCL/C++
2025-07-17T07:05:47.2225090Z     extension.
2025-07-17T07:05:47.2225130Z     
2025-07-17T07:05:47.2225250Z     All arguments are forwarded to the :class:`setuptools.Extension`
2025-07-17T07:05:47.2225300Z     constructor.
2025-07-17T07:05:47.2225330Z     
2025-07-17T07:05:47.2225380Z     .. warning::
2025-07-17T07:05:47.2225520Z         The PyTorch python API (as provided in libtorch_python) cannot be built
2025-07-17T07:05:47.2225650Z         with the flag ``py_limited_api=True``.  When this flag is passed, it is
2025-07-17T07:05:47.2225770Z         the user's responsibility in their library to not use APIs from
2025-07-17T07:05:47.2225910Z         libtorch_python (in particular pytorch/python bindings) and to only use
2025-07-17T07:05:47.2226090Z         APIs from libtorch (aten objects, operators and the dispatcher). For
2025-07-17T07:05:47.2226220Z         example, to give access to custom ops from python, the library should
2025-07-17T07:05:47.2226320Z         register the ops through the dispatcher.
2025-07-17T07:05:47.2226360Z     
2025-07-17T07:05:47.2226490Z         Contrary to CPython setuptools, who does not define -DPy_LIMITED_API
2025-07-17T07:05:47.2226610Z         as a compile flag when py_limited_api is specified as an option for
2025-07-17T07:05:47.2226740Z         the "bdist_wheel" command in ``setup``, PyTorch does! We will specify
2025-07-17T07:05:47.2226870Z         -DPy_LIMITED_API=min_supported_cpython to best enforce consistency,
2025-07-17T07:05:47.2226990Z         safety, and sanity in order to encourage best practices. To target a
2025-07-17T07:05:47.2227120Z         different version, set min_supported_cpython to the hexcode of the
2025-07-17T07:05:47.2227200Z         CPython version of choice.
2025-07-17T07:05:47.2227260Z     
2025-07-17T07:05:47.2227310Z     Example:
2025-07-17T07:05:47.2227360Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2227450Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-07-17T07:05:47.2227590Z         >>> from torch.utils.cpp_extension import BuildExtension, SyclExtension
2025-07-17T07:05:47.2227630Z         >>> setup(
2025-07-17T07:05:47.2227690Z         ...     name='xpu_extension',
2025-07-17T07:05:47.2227740Z         ...     ext_modules=[
2025-07-17T07:05:47.2227790Z         ...     SyclExtension(
2025-07-17T07:05:47.2227860Z         ...                 name='xpu_extension',
2025-07-17T07:05:47.2227960Z         ...                 sources=['extension.cpp', 'extension_kernel.cpp'],
2025-07-17T07:05:47.2228080Z         ...                 extra_compile_args={'cxx': ['-g', '-std=c++20', '-fPIC']})
2025-07-17T07:05:47.2228120Z         ...     ],
2025-07-17T07:05:47.2228170Z         ...     cmdclass={
2025-07-17T07:05:47.2228240Z         ...         'build_ext': BuildExtension
2025-07-17T07:05:47.2228280Z         ...     })
2025-07-17T07:05:47.2228320Z     
2025-07-17T07:05:47.2228500Z     By default the extension will be compiled to run on all archs of the cards visible during the
2025-07-17T07:05:47.2228660Z     building process of the extension. If down the road a new card is installed the
2025-07-17T07:05:47.2228800Z     extension may need to be recompiled. You can override the default behavior using
2025-07-17T07:05:47.2228990Z     `TORCH_XPU_ARCH_LIST` to explicitly specify which device architectures you want the extension
2025-07-17T07:05:47.2229030Z     to support:
2025-07-17T07:05:47.2229080Z     
2025-07-17T07:05:47.2229200Z     ``TORCH_XPU_ARCH_LIST="pvc,xe-lpg" python build_my_extension.py``
2025-07-17T07:05:47.2229240Z     
2025-07-17T07:05:47.2229410Z     Note that while it's possible to include all supported archs, the more archs get included the
2025-07-17T07:05:47.2229590Z     slower the building process will be, as it will build a separate kernel image for each arch.
2025-07-17T07:05:47.2229630Z     
2025-07-17T07:05:47.2229720Z     Note: Ninja is required to build SyclExtension.
2025-07-17T07:05:47.2229750Z     
2025-07-17T07:05:47.2229900Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2229940Z     
2025-07-17T07:05:47.2229990Z       warnings.warn(msg)
2025-07-17T07:05:47.2230040Z     
2025-07-17T07:05:47.2230130Z --- Parse Warning: 114 / 136 ---
2025-07-17T07:05:47.2230770Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1585.
2025-07-17T07:05:47.2230930Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2230970Z     
2025-07-17T07:05:47.2231050Z     Load a PyTorch C++ extension just-in-time (JIT).
2025-07-17T07:05:47.2231120Z     
2025-07-17T07:05:47.2231250Z     To load an extension, a Ninja build file is emitted, which is used to
2025-07-17T07:05:47.2231370Z     compile the given sources into a dynamic library. This library is
2025-07-17T07:05:47.2231520Z     subsequently loaded into the current Python process as a module and
2025-07-17T07:05:47.2231600Z     returned from this function, ready for use.
2025-07-17T07:05:47.2231640Z     
2025-07-17T07:05:47.2231760Z     By default, the directory to which the build file is emitted and the
2025-07-17T07:05:47.2231900Z     resulting library compiled to is ``<tmp>/torch_extensions/<name>``, where
2025-07-17T07:05:47.2232030Z     ``<tmp>`` is the temporary folder on the current platform and ``<name>``
2025-07-17T07:05:47.2232150Z     the name of the extension. This location can be overridden in two ways.
2025-07-17T07:05:47.2232300Z     First, if the ``TORCH_EXTENSIONS_DIR`` environment variable is set, it
2025-07-17T07:05:47.2232450Z     replaces ``<tmp>/torch_extensions`` and all extensions will be compiled
2025-07-17T07:05:47.2232580Z     into subfolders of this directory. Second, if the ``build_directory``
2025-07-17T07:05:47.2232720Z     argument to this function is supplied, it overrides the entire path, i.e.
2025-07-17T07:05:47.2232820Z     the library will be compiled into that folder directly.
2025-07-17T07:05:47.2232860Z     
2025-07-17T07:05:47.2232980Z     To compile the sources, the default system compiler (``c++``) is used,
2025-07-17T07:05:47.2233120Z     which can be overridden by setting the ``CXX`` environment variable. To pass
2025-07-17T07:05:47.2233260Z     additional arguments to the compilation process, ``extra_cflags`` or
2025-07-17T07:05:47.2233390Z     ``extra_ldflags`` can be provided. For example, to compile your extension
2025-07-17T07:05:47.2233510Z     with optimizations, pass ``extra_cflags=['-O3']``. You can also use
2025-07-17T07:05:47.2233610Z     ``extra_cflags`` to pass further include directories.
2025-07-17T07:05:47.2233650Z     
2025-07-17T07:05:47.2233790Z     CUDA support with mixed compilation is provided. Simply pass CUDA source
2025-07-17T07:05:47.2233900Z     files (``.cu`` or ``.cuh``) along with other sources. Such files will be
2025-07-17T07:05:47.2234050Z     detected and compiled with nvcc rather than the C++ compiler. This includes
2025-07-17T07:05:47.2234180Z     passing the CUDA lib64 directory as a library directory, and linking
2025-07-17T07:05:47.2234270Z     ``cudart``. You can pass additional flags to nvcc via
2025-07-17T07:05:47.2234390Z     ``extra_cuda_cflags``, just like with ``extra_cflags`` for C++. Various
2025-07-17T07:05:47.2234530Z     heuristics for finding the CUDA install directory are used, which usually
2025-07-17T07:05:47.2234650Z     work fine. If not, setting the ``CUDA_HOME`` environment variable is the
2025-07-17T07:05:47.2234700Z     safest option.
2025-07-17T07:05:47.2234740Z     
2025-07-17T07:05:47.2234880Z     SYCL support with mixed compilation is provided. Simply pass SYCL source
2025-07-17T07:05:47.2235000Z     files (``.sycl``) along with other sources. Such files will be detected
2025-07-17T07:05:47.2235130Z     and compiled with SYCL compiler (such as Intel DPC++ Compiler) rather
2025-07-17T07:05:47.2235260Z     than the C++ compiler. You can pass additional flags to SYCL compiler
2025-07-17T07:05:47.2235370Z     via ``extra_sycl_cflags``, just like with ``extra_cflags`` for C++.
2025-07-17T07:05:47.2235500Z     SYCL compiler is expected to be found via system PATH environment
2025-07-17T07:05:47.2235540Z     variable.
2025-07-17T07:05:47.2235580Z     
2025-07-17T07:05:47.2235620Z     Args:
2025-07-17T07:05:47.2235750Z         name: The name of the extension to build. This MUST be the same as the
2025-07-17T07:05:47.2235810Z             name of the pybind11 module!
2025-07-17T07:05:47.2235930Z         sources: A list of relative or absolute paths to C++ source files.
2025-07-17T07:05:47.2236070Z         extra_cflags: optional list of compiler flags to forward to the build.
2025-07-17T07:05:47.2236220Z         extra_cuda_cflags: optional list of compiler flags to forward to nvcc
2025-07-17T07:05:47.2236280Z             when building CUDA sources.
2025-07-17T07:05:47.2236410Z         extra_sycl_cflags: optional list of compiler flags to forward to SYCL
2025-07-17T07:05:47.2236510Z             compiler when building SYCL sources.
2025-07-17T07:05:47.2236640Z         extra_ldflags: optional list of linker flags to forward to the build.
2025-07-17T07:05:47.2236770Z         extra_include_paths: optional list of include directories to forward
2025-07-17T07:05:47.2236820Z             to the build.
2025-07-17T07:05:47.2236930Z         build_directory: optional path to use as build workspace.
2025-07-17T07:05:47.2237030Z         verbose: If ``True``, turns on verbose logging of load steps.
2025-07-17T07:05:47.2237170Z         with_cuda: Determines whether CUDA headers and libraries are added to
2025-07-17T07:05:47.2237280Z             the build. If set to ``None`` (default), this value is
2025-07-17T07:05:47.2237420Z             automatically determined based on the existence of ``.cu`` or
2025-07-17T07:05:47.2237530Z             ``.cuh`` in ``sources``. Set it to `True`` to force CUDA headers
2025-07-17T07:05:47.2237590Z             and libraries to be included.
2025-07-17T07:05:47.2237720Z         with_sycl: Determines whether SYCL headers and libraries are added to
2025-07-17T07:05:47.2237820Z             the build. If set to ``None`` (default), this value is
2025-07-17T07:05:47.2237940Z             automatically determined based on the existence of ``.sycl`` in
2025-07-17T07:05:47.2238040Z             ``sources``. Set it to `True`` to force SYCL headers and
2025-07-17T07:05:47.2238100Z             libraries to be included.
2025-07-17T07:05:47.2238220Z         is_python_module: If ``True`` (default), imports the produced shared
2025-07-17T07:05:47.2238340Z             library as a Python module. If ``False``, behavior depends on
2025-07-17T07:05:47.2238390Z             ``is_standalone``.
2025-07-17T07:05:47.2238520Z         is_standalone: If ``False`` (default) loads the constructed extension
2025-07-17T07:05:47.2238640Z             into the process as a plain dynamic library. If ``True``, build a
2025-07-17T07:05:47.2238700Z             standalone executable.
2025-07-17T07:05:47.2238740Z     
2025-07-17T07:05:47.2238780Z     Returns:
2025-07-17T07:05:47.2238840Z         If ``is_python_module`` is ``True``:
2025-07-17T07:05:47.2238950Z             Returns the loaded PyTorch extension as a Python module.
2025-07-17T07:05:47.2238990Z     
2025-07-17T07:05:47.2239110Z         If ``is_python_module`` is ``False`` and ``is_standalone`` is ``False``:
2025-07-17T07:05:47.2239240Z             Returns nothing. (The shared library is loaded into the process as
2025-07-17T07:05:47.2239290Z             a side effect.)
2025-07-17T07:05:47.2239330Z     
2025-07-17T07:05:47.2239390Z         If ``is_standalone`` is ``True``.
2025-07-17T07:05:47.2239510Z             Return the path to the executable. (On Windows, TORCH_LIB_PATH is
2025-07-17T07:05:47.2239620Z             added to the PATH environment variable as a side effect.)
2025-07-17T07:05:47.2239660Z     
2025-07-17T07:05:47.2239700Z     Example:
2025-07-17T07:05:47.2239750Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2239840Z         >>> from torch.utils.cpp_extension import load
2025-07-17T07:05:47.2239890Z         >>> module = load(
2025-07-17T07:05:47.2239940Z         ...     name='extension',
2025-07-17T07:05:47.2240040Z         ...     sources=['extension.cpp', 'extension_kernel.cu'],
2025-07-17T07:05:47.2240090Z         ...     extra_cflags=['-O2'],
2025-07-17T07:05:47.2240140Z         ...     verbose=True)
2025-07-17T07:05:47.2240180Z     
2025-07-17T07:05:47.2240330Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2240370Z     
2025-07-17T07:05:47.2240420Z       warnings.warn(msg)
2025-07-17T07:05:47.2240460Z     
2025-07-17T07:05:47.2240560Z --- Parse Warning: 115 / 136 ---
2025-07-17T07:05:47.2241240Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_inline in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/cpp_extension.py line=1890.
2025-07-17T07:05:47.2241420Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2241460Z     
2025-07-17T07:05:47.2241580Z     Load a PyTorch C++ extension just-in-time (JIT) from string sources.
2025-07-17T07:05:47.2241620Z     
2025-07-17T07:05:47.2241760Z     This function behaves exactly like :func:`load`, but takes its sources as
2025-07-17T07:05:47.2241900Z     strings rather than filenames. These strings are stored to files in the
2025-07-17T07:05:47.2242020Z     build directory, after which the behavior of :func:`load_inline` is
2025-07-17T07:05:47.2242110Z     identical to :func:`load`.
2025-07-17T07:05:47.2242180Z     
2025-07-17T07:05:47.2242220Z     See `the
2025-07-17T07:05:47.2242410Z     tests <https://github.com/pytorch/pytorch/blob/master/test/test_cpp_extensions_jit.py>`_
2025-07-17T07:05:47.2242490Z     for good examples of using this function.
2025-07-17T07:05:47.2242530Z     
2025-07-17T07:05:47.2242670Z     Sources may omit two required parts of a typical non-inline C++ extension:
2025-07-17T07:05:47.2242810Z     the necessary header includes, as well as the (pybind11) binding code. More
2025-07-17T07:05:47.2242950Z     precisely, strings passed to ``cpp_sources`` are first concatenated into a
2025-07-17T07:05:47.2243070Z     single ``.cpp`` file. This file is then prepended with ``#include
2025-07-17T07:05:47.2243120Z     <torch/extension.h>``
2025-07-17T07:05:47.2243160Z     
2025-07-17T07:05:47.2243300Z     Furthermore, if the ``functions`` argument is supplied, bindings will be
2025-07-17T07:05:47.2243440Z     automatically generated for each function specified. ``functions`` can
2025-07-17T07:05:47.2243570Z     either be a list of function names, or a dictionary mapping from function
2025-07-17T07:05:47.2243700Z     names to docstrings. If a list is given, the name of each function is used
2025-07-17T07:05:47.2243750Z     as its docstring.
2025-07-17T07:05:47.2243790Z     
2025-07-17T07:05:47.2243920Z     The sources in ``cuda_sources`` are concatenated into a separate ``.cu``
2025-07-17T07:05:47.2244020Z     file and  prepended with ``torch/types.h``, ``cuda.h`` and
2025-07-17T07:05:47.2244150Z     ``cuda_runtime.h`` includes. The ``.cpp`` and ``.cu`` files are compiled
2025-07-17T07:05:47.2244280Z     separately, but ultimately linked into a single library. Note that no
2025-07-17T07:05:47.2244410Z     bindings are generated for functions in ``cuda_sources`` per se. To bind
2025-07-17T07:05:47.2244550Z     to a CUDA kernel, you must create a C++ function that calls it, and either
2025-07-17T07:05:47.2244670Z     declare or define this C++ function in one of the ``cpp_sources`` (and
2025-07-17T07:05:47.2244740Z     include its name in ``functions``).
2025-07-17T07:05:47.2244780Z     
2025-07-17T07:05:47.2244910Z     The sources in ``sycl_sources`` are concatenated into a separate ``.sycl``
2025-07-17T07:05:47.2245040Z     file and  prepended with ``torch/types.h``, ``sycl/sycl.hpp`` includes.
2025-07-17T07:05:47.2245160Z     The ``.cpp`` and ``.sycl`` files are compiled separately, but ultimately
2025-07-17T07:05:47.2245290Z     linked into a single library. Note that no bindings are generated for
2025-07-17T07:05:47.2245410Z     functions in ``sycl_sources`` per se. To bind to a SYCL kernel, you must
2025-07-17T07:05:47.2245540Z     create a C++ function that calls it, and either declare or define this
2025-07-17T07:05:47.2245650Z     C++ function in one of the ``cpp_sources`` (and include its name
2025-07-17T07:05:47.2245700Z     in ``functions``).
2025-07-17T07:05:47.2245740Z     
2025-07-17T07:05:47.2245780Z     
2025-07-17T07:05:47.2245820Z     
2025-07-17T07:05:47.2245930Z     See :func:`load` for a description of arguments omitted below.
2025-07-17T07:05:47.2245990Z     
2025-07-17T07:05:47.2246030Z     Args:
2025-07-17T07:05:47.2246160Z         cpp_sources: A string, or list of strings, containing C++ source code.
2025-07-17T07:05:47.2246300Z         cuda_sources: A string, or list of strings, containing CUDA source code.
2025-07-17T07:05:47.2246450Z         sycl_sources: A string, or list of strings, containing SYCL source code.
2025-07-17T07:05:47.2246570Z         functions: A list of function names for which to generate function
2025-07-17T07:05:47.2246700Z             bindings. If a dictionary is given, it should map function names to
2025-07-17T07:05:47.2246810Z             docstrings (which are otherwise just the function names).
2025-07-17T07:05:47.2246940Z         with_cuda: Determines whether CUDA headers and libraries are added to
2025-07-17T07:05:47.2247040Z             the build. If set to ``None`` (default), this value is
2025-07-17T07:05:47.2247180Z             automatically determined based on whether ``cuda_sources`` is
2025-07-17T07:05:47.2247290Z             provided. Set it to ``True`` to force CUDA headers
2025-07-17T07:05:47.2247360Z             and libraries to be included.
2025-07-17T07:05:47.2247490Z         with_sycl: Determines whether SYCL headers and libraries are added to
2025-07-17T07:05:47.2247580Z             the build. If set to ``None`` (default), this value is
2025-07-17T07:05:47.2247700Z             automatically determined based on whether ``sycl_sources`` is
2025-07-17T07:05:47.2247790Z             provided. Set it to ``True`` to force SYCL headers
2025-07-17T07:05:47.2247850Z             and libraries to be included.
2025-07-17T07:05:47.2247980Z         with_pytorch_error_handling: Determines whether pytorch error and
2025-07-17T07:05:47.2248090Z             warning macros are handled by pytorch instead of pybind. To do
2025-07-17T07:05:47.2248230Z             this, each function ``foo`` is called via an intermediary ``_safe_foo``
2025-07-17T07:05:47.2248350Z             function. This redirection might cause issues in obscure cases
2025-07-17T07:05:47.2248460Z             of cpp. This flag should be set to ``False`` when this redirect
2025-07-17T07:05:47.2248510Z             causes issues.
2025-07-17T07:05:47.2248660Z         no_implicit_headers: If ``True``, skips automatically adding headers, most notably
2025-07-17T07:05:47.2248800Z             ``#include <torch/extension.h>`` and ``#include <torch/types.h>`` lines.
2025-07-17T07:05:47.2248900Z             Use this option to improve cold start times when you
2025-07-17T07:05:47.2249050Z             already include the necessary headers in your source code. Default: ``False``.
2025-07-17T07:05:47.2249090Z     
2025-07-17T07:05:47.2249130Z     Example:
2025-07-17T07:05:47.2249220Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT)
2025-07-17T07:05:47.2249320Z         >>> from torch.utils.cpp_extension import load_inline
2025-07-17T07:05:47.2249360Z         >>> source = """
2025-07-17T07:05:47.2249450Z         at::Tensor sin_add(at::Tensor x, at::Tensor y) {
2025-07-17T07:05:47.2249510Z           return x.sin() + y.sin();
2025-07-17T07:05:47.2249550Z         }
2025-07-17T07:05:47.2249590Z         """
2025-07-17T07:05:47.2249670Z         >>> module = load_inline(name='inline_extension',
2025-07-17T07:05:47.2249750Z         ...                      cpp_sources=[source],
2025-07-17T07:05:47.2249820Z         ...                      functions=['sin_add'])
2025-07-17T07:05:47.2249860Z     
2025-07-17T07:05:47.2249900Z     .. note::
2025-07-17T07:05:47.2250040Z         Since load_inline will just-in-time compile the source code, please ensure
2025-07-17T07:05:47.2250180Z         that you have the right toolchains installed in the runtime. For example,
2025-07-17T07:05:47.2250310Z         when loading C++, make sure a C++ compiler is available. If you're loading
2025-07-17T07:05:47.2250460Z         a CUDA extension, you will need to additionally install the corresponding CUDA
2025-07-17T07:05:47.2250630Z         toolkit (nvcc and any other dependencies your code has). Compiling toolchains
2025-07-17T07:05:47.2250780Z         are not included when you install torch and must be additionally installed.
2025-07-17T07:05:47.2250820Z     
2025-07-17T07:05:47.2250970Z         During compiling, by default, the Ninja backend uses #CPUS + 2 workers to build
2025-07-17T07:05:47.2251120Z         the extension. This may use up too many resources on some systems. One
2025-07-17T07:05:47.2251250Z         can control the number of workers by setting the `MAX_JOBS` environment
2025-07-17T07:05:47.2251320Z         variable to a non-negative number.
2025-07-17T07:05:47.2251360Z     
2025-07-17T07:05:47.2251510Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2251550Z     
2025-07-17T07:05:47.2251600Z       warnings.warn(msg)
2025-07-17T07:05:47.2251640Z     
2025-07-17T07:05:47.2251740Z --- Parse Warning: 116 / 136 ---
2025-07-17T07:05:47.2252450Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedSampler in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/utils/data/distributed.py line=18.
2025-07-17T07:05:47.2252620Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2252740Z     Sampler that restricts data loading to a subset of the dataset.
2025-07-17T07:05:47.2252780Z     
2025-07-17T07:05:47.2252860Z         It is especially useful in conjunction with
2025-07-17T07:05:47.2253010Z         :class:`torch.nn.parallel.DistributedDataParallel`. In such a case, each
2025-07-17T07:05:47.2253170Z         process can pass a :class:`~torch.utils.data.DistributedSampler` instance as a
2025-07-17T07:05:47.2253300Z         :class:`~torch.utils.data.DataLoader` sampler, and load a subset of the
2025-07-17T07:05:47.2253380Z         original dataset that is exclusive to it.
2025-07-17T07:05:47.2253420Z     
2025-07-17T07:05:47.2253470Z         .. note::
2025-07-17T07:05:47.2253610Z             Dataset is assumed to be of constant size and that any instance of it always
2025-07-17T07:05:47.2253690Z             returns the same elements in the same order.
2025-07-17T07:05:47.2253730Z     
2025-07-17T07:05:47.2253780Z         Args:
2025-07-17T07:05:47.2253850Z             dataset: Dataset used for sampling.
2025-07-17T07:05:47.2253980Z             num_replicas (int, optional): Number of processes participating in
2025-07-17T07:05:47.2254120Z                 distributed training. By default, :attr:`world_size` is retrieved from the
2025-07-17T07:05:47.2254190Z                 current distributed group.
2025-07-17T07:05:47.2254330Z             rank (int, optional): Rank of the current process within :attr:`num_replicas`.
2025-07-17T07:05:47.2254450Z                 By default, :attr:`rank` is retrieved from the current distributed
2025-07-17T07:05:47.2254500Z                 group.
2025-07-17T07:05:47.2254630Z             shuffle (bool, optional): If ``True`` (default), sampler will shuffle the
2025-07-17T07:05:47.2254680Z                 indices.
2025-07-17T07:05:47.2254790Z             seed (int, optional): random seed used to shuffle the sampler if
2025-07-17T07:05:47.2254910Z                 :attr:`shuffle=True`. This number should be identical across all
2025-07-17T07:05:47.2255010Z                 processes in the distributed group. Default: ``0``.
2025-07-17T07:05:47.2255150Z             drop_last (bool, optional): if ``True``, then the sampler will drop the
2025-07-17T07:05:47.2255270Z                 tail of the data to make it evenly divisible across the number of
2025-07-17T07:05:47.2255390Z                 replicas. If ``False``, the sampler will add extra indices to make
2025-07-17T07:05:47.2255510Z                 the data evenly divisible across the replicas. Default: ``False``.
2025-07-17T07:05:47.2255550Z     
2025-07-17T07:05:47.2255600Z         .. warning::
2025-07-17T07:05:47.2255730Z             In distributed mode, calling the :meth:`set_epoch` method at
2025-07-17T07:05:47.2255890Z             the beginning of each epoch **before** creating the :class:`DataLoader` iterator
2025-07-17T07:05:47.2256040Z             is necessary to make shuffling work properly across multiple epochs. Otherwise,
2025-07-17T07:05:47.2256150Z             the same ordering will be always used.
2025-07-17T07:05:47.2256190Z     
2025-07-17T07:05:47.2256230Z         Example::
2025-07-17T07:05:47.2256270Z     
2025-07-17T07:05:47.2256320Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2256450Z             >>> sampler = DistributedSampler(dataset) if is_distributed else None
2025-07-17T07:05:47.2256560Z             >>> loader = DataLoader(dataset, shuffle=(sampler is None),
2025-07-17T07:05:47.2256630Z             ...                     sampler=sampler)
2025-07-17T07:05:47.2256710Z             >>> for epoch in range(start_epoch, n_epochs):
2025-07-17T07:05:47.2256790Z             ...     if is_distributed:
2025-07-17T07:05:47.2256870Z             ...         sampler.set_epoch(epoch)
2025-07-17T07:05:47.2256930Z             ...     train(loader)
2025-07-17T07:05:47.2256970Z         
2025-07-17T07:05:47.2257110Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2257160Z     
2025-07-17T07:05:47.2257210Z       warnings.warn(msg)
2025-07-17T07:05:47.2257250Z     
2025-07-17T07:05:47.2257350Z --- Parse Warning: 117 / 136 ---
2025-07-17T07:05:47.2258000Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_close in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/testing/_comparison.py line=1331.
2025-07-17T07:05:47.2258160Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2258240Z     Asserts that ``actual`` and ``expected`` are close.
2025-07-17T07:05:47.2258290Z     
2025-07-17T07:05:47.2258510Z         If ``actual`` and ``expected`` are strided, non-quantized, real-valued, and finite, they are considered close if
2025-07-17T07:05:47.2258550Z     
2025-07-17T07:05:47.2258590Z         .. math::
2025-07-17T07:05:47.2258640Z     
2025-07-17T07:05:47.2258850Z             \lvert \text{actual} - \text{expected} \rvert \le \texttt{atol} + \texttt{rtol} \cdot \lvert \text{expected} \rvert
2025-07-17T07:05:47.2258900Z     
2025-07-17T07:05:47.2259100Z         Non-finite values (``-inf`` and ``inf``) are only considered close if and only if they are equal. ``NaN``'s are
2025-07-17T07:05:47.2259230Z         only considered equal to each other if ``equal_nan`` is ``True``.
2025-07-17T07:05:47.2259270Z     
2025-07-17T07:05:47.2259390Z         In addition, they are only considered close if they have the same
2025-07-17T07:05:47.2259430Z     
2025-07-17T07:05:47.2259540Z         - :attr:`~torch.Tensor.device` (if ``check_device`` is ``True``),
2025-07-17T07:05:47.2259630Z         - ``dtype`` (if ``check_dtype`` is ``True``),
2025-07-17T07:05:47.2259710Z         - ``layout`` (if ``check_layout`` is ``True``), and
2025-07-17T07:05:47.2259780Z         - stride (if ``check_stride`` is ``True``).
2025-07-17T07:05:47.2259830Z     
2025-07-17T07:05:47.2260010Z         If either ``actual`` or ``expected`` is a meta tensor, only the attribute checks will be performed.
2025-07-17T07:05:47.2260050Z     
2025-07-17T07:05:47.2260260Z         If ``actual`` and ``expected`` are sparse (either having COO, CSR, CSC, BSR, or BSC layout), their strided members are
2025-07-17T07:05:47.2260480Z         checked individually. Indices, namely ``indices`` for COO, ``crow_indices`` and ``col_indices`` for CSR and BSR,
2025-07-17T07:05:47.2260620Z         or ``ccol_indices``  and ``row_indices`` for CSC and BSC layouts, respectively,
2025-07-17T07:05:47.2260850Z         are always checked for equality whereas the values are checked for closeness according to the definition above.
2025-07-17T07:05:47.2260890Z     
2025-07-17T07:05:47.2261080Z         If ``actual`` and ``expected`` are quantized, they are considered close if they have the same
2025-07-17T07:05:47.2261300Z         :meth:`~torch.Tensor.qscheme` and the result of :meth:`~torch.Tensor.dequantize` is close according to the
2025-07-17T07:05:47.2261380Z         definition above.
2025-07-17T07:05:47.2261420Z     
2025-07-17T07:05:47.2261600Z         ``actual`` and ``expected`` can be :class:`~torch.Tensor`'s or any tensor-or-scalar-likes from which
2025-07-17T07:05:47.2261820Z         :class:`torch.Tensor`'s can be constructed with :func:`torch.as_tensor`. Except for Python scalars the input types
2025-07-17T07:05:47.2262040Z         have to be directly related. In addition, ``actual`` and ``expected`` can be :class:`~collections.abc.Sequence`'s
2025-07-17T07:05:47.2262260Z         or :class:`~collections.abc.Mapping`'s in which case they are considered close if their structure matches and all
2025-07-17T07:05:47.2262450Z         their elements are considered close according to the above definition.
2025-07-17T07:05:47.2262520Z     
2025-07-17T07:05:47.2262560Z         .. note::
2025-07-17T07:05:47.2262600Z     
2025-07-17T07:05:47.2262800Z             Python scalars are an exception to the type relation requirement, because their :func:`type`, i.e.
2025-07-17T07:05:47.2263000Z             :class:`int`, :class:`float`, and :class:`complex`, is equivalent to the ``dtype`` of a tensor-like. Thus,
2025-07-17T07:05:47.2263160Z             Python scalars of different types can be checked, but require ``check_dtype=False``.
2025-07-17T07:05:47.2263200Z     
2025-07-17T07:05:47.2263250Z         Args:
2025-07-17T07:05:47.2263300Z             actual (Any): Actual input.
2025-07-17T07:05:47.2263370Z             expected (Any): Expected input.
2025-07-17T07:05:47.2263580Z             allow_subclasses (bool): If ``True`` (default) and except for Python scalars, inputs of directly related types
2025-07-17T07:05:47.2263680Z                 are allowed. Otherwise type equality is required.
2025-07-17T07:05:47.2263900Z             rtol (Optional[float]): Relative tolerance. If specified ``atol`` must also be specified. If omitted, default
2025-07-17T07:05:47.2264060Z                 values based on the :attr:`~torch.Tensor.dtype` are selected with the below table.
2025-07-17T07:05:47.2264270Z             atol (Optional[float]): Absolute tolerance. If specified ``rtol`` must also be specified. If omitted, default
2025-07-17T07:05:47.2264430Z                 values based on the :attr:`~torch.Tensor.dtype` are selected with the below table.
2025-07-17T07:05:47.2264580Z             equal_nan (Union[bool, str]): If ``True``, two ``NaN`` values will be considered equal.
2025-07-17T07:05:47.2264750Z             check_device (bool): If ``True`` (default), asserts that corresponding tensors are on the same
2025-07-17T07:05:47.2264900Z                 :attr:`~torch.Tensor.device`. If this check is disabled, tensors on different
2025-07-17T07:05:47.2265040Z                 :attr:`~torch.Tensor.device`'s are moved to the CPU before being compared.
2025-07-17T07:05:47.2265250Z             check_dtype (bool): If ``True`` (default), asserts that corresponding tensors have the same ``dtype``. If this
2025-07-17T07:05:47.2265460Z                 check is disabled, tensors with different ``dtype``'s are promoted  to a common ``dtype`` (according to
2025-07-17T07:05:47.2265560Z                 :func:`torch.promote_types`) before being compared.
2025-07-17T07:05:47.2265770Z             check_layout (bool): If ``True`` (default), asserts that corresponding tensors have the same ``layout``. If this
2025-07-17T07:05:47.2265970Z                 check is disabled, tensors with different ``layout``'s are converted to strided tensors before being
2025-07-17T07:05:47.2266020Z                 compared.
2025-07-17T07:05:47.2266230Z             check_stride (bool): If ``True`` and corresponding tensors are strided, asserts that they have the same stride.
2025-07-17T07:05:47.2266460Z             msg (Optional[Union[str, Callable[[str], str]]]): Optional error message to use in case a failure occurs during
2025-07-17T07:05:47.2266670Z                 the comparison. Can also passed as callable in which case it will be called with the generated message and
2025-07-17T07:05:47.2266760Z                 should return the new message.
2025-07-17T07:05:47.2266800Z     
2025-07-17T07:05:47.2266840Z         Raises:
2025-07-17T07:05:47.2266990Z             ValueError: If no :class:`torch.Tensor` can be constructed from an input.
2025-07-17T07:05:47.2267090Z             ValueError: If only ``rtol`` or ``atol`` is specified.
2025-07-17T07:05:47.2270720Z             AssertionError: If corresponding inputs are not Python scalars and are not directly related.
2025-07-17T07:05:47.2270950Z             AssertionError: If ``allow_subclasses`` is ``False``, but corresponding inputs are not Python scalars and have
2025-07-17T07:05:47.2271010Z                 different types.
2025-07-17T07:05:47.2271300Z             AssertionError: If the inputs are :class:`~collections.abc.Sequence`'s, but their length does not match.
2025-07-17T07:05:47.2271540Z             AssertionError: If the inputs are :class:`~collections.abc.Mapping`'s, but their set of keys do not match.
2025-07-17T07:05:47.2271740Z             AssertionError: If corresponding tensors do not have the same :attr:`~torch.Tensor.shape`.
2025-07-17T07:05:47.2271920Z             AssertionError: If ``check_layout`` is ``True``, but corresponding tensors do not have the same
2025-07-17T07:05:47.2271990Z                 :attr:`~torch.Tensor.layout`.
2025-07-17T07:05:47.2272120Z             AssertionError: If only one of corresponding tensors is quantized.
2025-07-17T07:05:47.2272350Z             AssertionError: If corresponding tensors are quantized, but have different :meth:`~torch.Tensor.qscheme`'s.
2025-07-17T07:05:47.2272520Z             AssertionError: If ``check_device`` is ``True``, but corresponding tensors are not on the same
2025-07-17T07:05:47.2272590Z                 :attr:`~torch.Tensor.device`.
2025-07-17T07:05:47.2272790Z             AssertionError: If ``check_dtype`` is ``True``, but corresponding tensors do not have the same ``dtype``.
2025-07-17T07:05:47.2272990Z             AssertionError: If ``check_stride`` is ``True``, but corresponding strided tensors do not have the same stride.
2025-07-17T07:05:47.2273210Z             AssertionError: If the values of corresponding tensors are not close according to the definition above.
2025-07-17T07:05:47.2273250Z     
2025-07-17T07:05:47.2273460Z         The following table displays the default ``rtol`` and ``atol`` for different ``dtype``'s. In case of mismatching
2025-07-17T07:05:47.2273550Z         ``dtype``'s, the maximum of both tolerances is used.
2025-07-17T07:05:47.2273600Z     
2025-07-17T07:05:47.2273680Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2273760Z         | ``dtype``                 | ``rtol``   | ``atol`` |
2025-07-17T07:05:47.2273820Z         +===========================+============+==========+
2025-07-17T07:05:47.2273910Z         | :attr:`~torch.float16`    | ``1e-3``   | ``1e-5`` |
2025-07-17T07:05:47.2273990Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2274070Z         | :attr:`~torch.bfloat16`   | ``1.6e-2`` | ``1e-5`` |
2025-07-17T07:05:47.2274140Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2274220Z         | :attr:`~torch.float32`    | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:47.2274300Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2274380Z         | :attr:`~torch.float64`    | ``1e-7``   | ``1e-7`` |
2025-07-17T07:05:47.2274450Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2274540Z         | :attr:`~torch.complex32`  | ``1e-3``   | ``1e-5`` |
2025-07-17T07:05:47.2274620Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2274700Z         | :attr:`~torch.complex64`  | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:47.2274820Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2274910Z         | :attr:`~torch.complex128` | ``1e-7``   | ``1e-7`` |
2025-07-17T07:05:47.2274980Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2275090Z         | :attr:`~torch.quint8`     | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:47.2275170Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2275250Z         | :attr:`~torch.quint2x4`   | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:47.2275330Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2275600Z         | :attr:`~torch.quint4x2`   | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:47.2275840Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2276080Z         | :attr:`~torch.qint8`      | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:47.2276340Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2276600Z         | :attr:`~torch.qint32`     | ``1.3e-6`` | ``1e-5`` |
2025-07-17T07:05:47.2276840Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2277070Z         | other                     | ``0.0``    | ``0.0``  |
2025-07-17T07:05:47.2277290Z         +---------------------------+------------+----------+
2025-07-17T07:05:47.2277490Z     
2025-07-17T07:05:47.2277600Z         .. note::
2025-07-17T07:05:47.2277730Z     
2025-07-17T07:05:47.2278040Z             :func:`~torch.testing.assert_close` is highly configurable with strict default settings. Users are encouraged
2025-07-17T07:05:47.2278570Z             to :func:`~functools.partial` it to fit their use case. For example, if an equality check is needed, one might
2025-07-17T07:05:47.2279020Z             define an ``assert_equal`` that uses zero tolerances for every ``dtype`` by default:
2025-07-17T07:05:47.2279300Z     
2025-07-17T07:05:47.2279420Z             >>> import functools
2025-07-17T07:05:47.2279710Z             >>> assert_equal = functools.partial(torch.testing.assert_close, rtol=0, atol=0)
2025-07-17T07:05:47.2280010Z             >>> assert_equal(1e-9, 1e-10)
2025-07-17T07:05:47.2280230Z             Traceback (most recent call last):
2025-07-17T07:05:47.2280420Z             ...
2025-07-17T07:05:47.2280580Z             AssertionError: Scalars are not equal!
2025-07-17T07:05:47.2280790Z             <BLANKLINE>
2025-07-17T07:05:47.2280960Z             Expected 1e-10 but got 1e-09.
2025-07-17T07:05:47.2281180Z             Absolute difference: 9.000000000000001e-10
2025-07-17T07:05:47.2281390Z             Relative difference: 9.0
2025-07-17T07:05:47.2281560Z     
2025-07-17T07:05:47.2281670Z         Examples:
2025-07-17T07:05:47.2281820Z             >>> # tensor to tensor comparison
2025-07-17T07:05:47.2282050Z             >>> expected = torch.tensor([1e0, 1e-1, 1e-2])
2025-07-17T07:05:47.2282290Z             >>> actual = torch.acos(torch.cos(expected))
2025-07-17T07:05:47.2282540Z             >>> torch.testing.assert_close(actual, expected)
2025-07-17T07:05:47.2282770Z     
2025-07-17T07:05:47.2282900Z             >>> # scalar to scalar comparison
2025-07-17T07:05:47.2283090Z             >>> import math
2025-07-17T07:05:47.2283270Z             >>> expected = math.sqrt(2.0)
2025-07-17T07:05:47.2283500Z             >>> actual = 2.0 / math.sqrt(2.0)
2025-07-17T07:05:47.2283740Z             >>> torch.testing.assert_close(actual, expected)
2025-07-17T07:05:47.2283940Z     
2025-07-17T07:05:47.2284090Z             >>> # numpy array to numpy array comparison
2025-07-17T07:05:47.2284290Z             >>> import numpy as np
2025-07-17T07:05:47.2284500Z             >>> expected = np.array([1e0, 1e-1, 1e-2])
2025-07-17T07:05:47.2284720Z             >>> actual = np.arccos(np.cos(expected))
2025-07-17T07:05:47.2284960Z             >>> torch.testing.assert_close(actual, expected)
2025-07-17T07:05:47.2285160Z     
2025-07-17T07:05:47.2285300Z             >>> # sequence to sequence comparison
2025-07-17T07:05:47.2285510Z             >>> import numpy as np
2025-07-17T07:05:47.2285840Z             >>> # The types of the sequences do not have to match. They only have to have the same
2025-07-17T07:05:47.2286150Z             >>> # length and their elements have to match.
2025-07-17T07:05:47.2286440Z             >>> expected = [torch.tensor([1.0]), 2.0, np.array(3.0)]
2025-07-17T07:05:47.2286670Z             >>> actual = tuple(expected)
2025-07-17T07:05:47.2286890Z             >>> torch.testing.assert_close(actual, expected)
2025-07-17T07:05:47.2287090Z     
2025-07-17T07:05:47.2287220Z             >>> # mapping to mapping comparison
2025-07-17T07:05:47.2287430Z             >>> from collections import OrderedDict
2025-07-17T07:05:47.2287630Z             >>> import numpy as np
2025-07-17T07:05:47.2287810Z             >>> foo = torch.tensor(1.0)
2025-07-17T07:05:47.2287990Z             >>> bar = 2.0
2025-07-17T07:05:47.2288150Z             >>> baz = np.array(3.0)
2025-07-17T07:05:47.2288450Z             >>> # The types and a possible ordering of mappings do not have to match. They only
2025-07-17T07:05:47.2288820Z             >>> # have to have the same set of keys and their elements have to match.
2025-07-17T07:05:47.2289140Z             >>> expected = OrderedDict([("foo", foo), ("bar", bar), ("baz", baz)])
2025-07-17T07:05:47.2289430Z             >>> actual = {"baz": baz, "bar": bar, "foo": foo}
2025-07-17T07:05:47.2289680Z             >>> torch.testing.assert_close(actual, expected)
2025-07-17T07:05:47.2289880Z     
2025-07-17T07:05:47.2290020Z             >>> expected = torch.tensor([1.0, 2.0, 3.0])
2025-07-17T07:05:47.2290240Z             >>> actual = expected.clone()
2025-07-17T07:05:47.2290480Z             >>> # By default, directly related instances can be compared
2025-07-17T07:05:47.2290820Z             >>> torch.testing.assert_close(torch.nn.Parameter(actual), expected)
2025-07-17T07:05:47.2291150Z             >>> # This check can be made more strict with allow_subclasses=False
2025-07-17T07:05:47.2291410Z             >>> torch.testing.assert_close(
2025-07-17T07:05:47.2291680Z             ...     torch.nn.Parameter(actual), expected, allow_subclasses=False
2025-07-17T07:05:47.2291920Z             ... )
2025-07-17T07:05:47.2292080Z             Traceback (most recent call last):
2025-07-17T07:05:47.2292270Z             ...
2025-07-17T07:05:47.2292500Z             TypeError: No comparison pair was able to handle inputs of type
2025-07-17T07:05:47.2292840Z             <class 'torch.nn.parameter.Parameter'> and <class 'torch.Tensor'>.
2025-07-17T07:05:47.2293190Z             >>> # If the inputs are not directly related, they are never considered close
2025-07-17T07:05:47.2293520Z             >>> torch.testing.assert_close(actual.numpy(), expected)
2025-07-17T07:05:47.2293780Z             Traceback (most recent call last):
2025-07-17T07:05:47.2293960Z             ...
2025-07-17T07:05:47.2294230Z             TypeError: No comparison pair was able to handle inputs of type <class 'numpy.ndarray'>
2025-07-17T07:05:47.2294550Z             and <class 'torch.Tensor'>.
2025-07-17T07:05:47.2294870Z             >>> # Exceptions to these rules are Python scalars. They can be checked regardless of
2025-07-17T07:05:47.2295190Z             >>> # their type if check_dtype=False.
2025-07-17T07:05:47.2295450Z             >>> torch.testing.assert_close(1.0, 1, check_dtype=False)
2025-07-17T07:05:47.2295670Z     
2025-07-17T07:05:47.2295790Z             >>> # NaN != NaN by default.
2025-07-17T07:05:47.2296010Z             >>> expected = torch.tensor(float("Nan"))
2025-07-17T07:05:47.2296220Z             >>> actual = expected.clone()
2025-07-17T07:05:47.2296450Z             >>> torch.testing.assert_close(actual, expected)
2025-07-17T07:05:47.2296680Z             Traceback (most recent call last):
2025-07-17T07:05:47.2296860Z             ...
2025-07-17T07:05:47.2297020Z             AssertionError: Scalars are not close!
2025-07-17T07:05:47.2297220Z             <BLANKLINE>
2025-07-17T07:05:47.2297380Z             Expected nan but got nan.
2025-07-17T07:05:47.2297630Z             Absolute difference: nan (up to 1e-05 allowed)
2025-07-17T07:05:47.2297890Z             Relative difference: nan (up to 1.3e-06 allowed)
2025-07-17T07:05:47.2298180Z             >>> torch.testing.assert_close(actual, expected, equal_nan=True)
2025-07-17T07:05:47.2298450Z     
2025-07-17T07:05:47.2298590Z             >>> expected = torch.tensor([1.0, 2.0, 3.0])
2025-07-17T07:05:47.2298800Z             >>> actual = torch.tensor([1.0, 4.0, 5.0])
2025-07-17T07:05:47.2299030Z             >>> # The default error message can be overwritten.
2025-07-17T07:05:47.2299370Z             >>> torch.testing.assert_close(actual, expected, msg="Argh, the tensors are not close!")
2025-07-17T07:05:47.2299680Z             Traceback (most recent call last):
2025-07-17T07:05:47.2299860Z             ...
2025-07-17T07:05:47.2300040Z             AssertionError: Argh, the tensors are not close!
2025-07-17T07:05:47.2300390Z             >>> # If msg is a callable, it can be used to augment the generated message with
2025-07-17T07:05:47.2300680Z             >>> # extra information
2025-07-17T07:05:47.2300870Z             >>> torch.testing.assert_close(
2025-07-17T07:05:47.2301140Z             ...     actual, expected, msg=lambda msg: f"Header\n\n{msg}\n\nFooter"
2025-07-17T07:05:47.2301370Z             ... )
2025-07-17T07:05:47.2301520Z             Traceback (most recent call last):
2025-07-17T07:05:47.2301700Z             ...
2025-07-17T07:05:47.2301840Z             AssertionError: Header
2025-07-17T07:05:47.2302010Z             <BLANKLINE>
2025-07-17T07:05:47.2302170Z             Tensor-likes are not close!
2025-07-17T07:05:47.2302340Z             <BLANKLINE>
2025-07-17T07:05:47.2302500Z             Mismatched elements: 2 / 3 (66.7%)
2025-07-17T07:05:47.2302780Z             Greatest absolute difference: 2.0 at index (1,) (up to 1e-05 allowed)
2025-07-17T07:05:47.2303120Z             Greatest relative difference: 1.0 at index (1,) (up to 1.3e-06 allowed)
2025-07-17T07:05:47.2303370Z             <BLANKLINE>
2025-07-17T07:05:47.2303510Z             Footer
2025-07-17T07:05:47.2303640Z         
2025-07-17T07:05:47.2303860Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2304120Z     
2025-07-17T07:05:47.2304230Z       warnings.warn(msg)
2025-07-17T07:05:47.2304370Z     
2025-07-17T07:05:47.2304600Z --- Parse Warning: 118 / 136 ---
2025-07-17T07:05:47.2305390Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=triton_op in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/triton.py line=21.
2025-07-17T07:05:47.2306250Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2306630Z     Create a custom operator whose implementation is backed by 1+ triton kernels.
2025-07-17T07:05:47.2306890Z     
2025-07-17T07:05:47.2307080Z         This is a more structured way of using triton kernels with PyTorch.
2025-07-17T07:05:47.2307440Z         Prefer using triton kernels with no ``torch.library`` custom operator wrappers
2025-07-17T07:05:47.2307810Z         (like :func:`torch.library.custom_op`, :func:`torch.library.triton_op`) because
2025-07-17T07:05:47.2308100Z         that is simpler;
2025-07-17T07:05:47.2308350Z         only use :func:`torch.library.custom_op`/:func:`torch.library.triton_op` if you
2025-07-17T07:05:47.2308720Z         want to create an operator that behaves like PyTorch built-in operators.
2025-07-17T07:05:47.2309060Z         For example, you may use a ``torch.library`` wrapper API to define the
2025-07-17T07:05:47.2309390Z         behavior of the triton kernel when passed a tensor subclass or under
2025-07-17T07:05:47.2309660Z         a TorchDispatchMode.
2025-07-17T07:05:47.2309820Z     
2025-07-17T07:05:47.2310040Z         Use :func:`torch.library.triton_op` instead of :func:`torch.library.custom_op`
2025-07-17T07:05:47.2310330Z         when the implementation
2025-07-17T07:05:47.2310640Z         consists of 1+ triton kernels. :func:`torch.library.custom_op` treats
2025-07-17T07:05:47.2310970Z         custom operators as opaque (:func:`torch.compile` and
2025-07-17T07:05:47.2311300Z         :func:`torch.export.export` will never trace into them), but ``triton_op``
2025-07-17T07:05:47.2311680Z         makes the implementation visible to these subsystems, allowing them
2025-07-17T07:05:47.2311950Z         to optimize the triton kernel(s).
2025-07-17T07:05:47.2312130Z     
2025-07-17T07:05:47.2312300Z         Note that ``fn`` must only consist of calls to PyTorch-understood
2025-07-17T07:05:47.2312620Z         operators and triton kernels. Any triton kernels called inside ``fn``
2025-07-17T07:05:47.2312940Z         must be wrapped in a call to :func:`torch.library.wrap_triton`.
2025-07-17T07:05:47.2313170Z     
2025-07-17T07:05:47.2313270Z         Args:
2025-07-17T07:05:47.2313510Z             name (str): A name for the custom op that looks like "{namespace}::{name}",
2025-07-17T07:05:47.2313880Z                 e.g. "mylib::my_linear". The name is used as the op's stable identifier
2025-07-17T07:05:47.2314190Z                 in PyTorch subsystems (e.g. torch.export, FX graphs).
2025-07-17T07:05:47.2314510Z                 To avoid name collisions, please use your project name as the namespace;
2025-07-17T07:05:47.2314850Z                 e.g. all custom ops in pytorch/fbgemm use "fbgemm" as the namespace.
2025-07-17T07:05:47.2315220Z             mutates_args (Iterable[str] or "unknown"): The names of args that the function mutates.
2025-07-17T07:05:47.2315600Z                 This MUST be accurate, otherwise, the behavior is undefined. If "unknown",
2025-07-17T07:05:47.2315970Z                 it pessimistically assumes that all inputs to the operator are being mutated.
2025-07-17T07:05:47.2316310Z             schema (None | str): A schema string for the operator. If None
2025-07-17T07:05:47.2316620Z                 (recommended) we'll infer a schema for the operator from its type
2025-07-17T07:05:47.2316950Z                 annotations. We recommend letting us infer a schema unless you
2025-07-17T07:05:47.2317200Z                 have a specific reason not to.
2025-07-17T07:05:47.2317440Z                 Example: "(Tensor x, int y) -> (Tensor, Tensor)".
2025-07-17T07:05:47.2317640Z     
2025-07-17T07:05:47.2317750Z         Example::
2025-07-17T07:05:47.2317870Z     
2025-07-17T07:05:47.2318020Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA)
2025-07-17T07:05:47.2318220Z             >>> import torch
2025-07-17T07:05:47.2318430Z             >>> from torch.library import triton_op, wrap_triton
2025-07-17T07:05:47.2318630Z             >>>
2025-07-17T07:05:47.2318770Z             >>> import triton
2025-07-17T07:05:47.2318950Z             >>> from triton import language as tl
2025-07-17T07:05:47.2319130Z             >>>
2025-07-17T07:05:47.2319250Z             >>> @triton.jit
2025-07-17T07:05:47.2319410Z             >>> def add_kernel(
2025-07-17T07:05:47.2319570Z             >>>     in_ptr0,
2025-07-17T07:05:47.2319730Z             >>>     in_ptr1,
2025-07-17T07:05:47.2319870Z             >>>     out_ptr,
2025-07-17T07:05:47.2320020Z             >>>     n_elements,
2025-07-17T07:05:47.2320200Z             >>>     BLOCK_SIZE: "tl.constexpr",
2025-07-17T07:05:47.2320380Z             >>> ):
2025-07-17T07:05:47.2320530Z             >>>     pid = tl.program_id(axis=0)
2025-07-17T07:05:47.2320740Z             >>>     block_start = pid * BLOCK_SIZE
2025-07-17T07:05:47.2320980Z             >>>     offsets = block_start + tl.arange(0, BLOCK_SIZE)
2025-07-17T07:05:47.2321210Z             >>>     mask = offsets < n_elements
2025-07-17T07:05:47.2321420Z             >>>     x = tl.load(in_ptr0 + offsets, mask=mask)
2025-07-17T07:05:47.2321650Z             >>>     y = tl.load(in_ptr1 + offsets, mask=mask)
2025-07-17T07:05:47.2321850Z             >>>     output = x + y
2025-07-17T07:05:47.2322070Z             >>>     tl.store(out_ptr + offsets, output, mask=mask)
2025-07-17T07:05:47.2322270Z             >>>
2025-07-17T07:05:47.2322490Z             >>> @triton_op("mylib::add", mutates_args={})
2025-07-17T07:05:47.2322790Z             >>> def add(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor:
2025-07-17T07:05:47.2323040Z             >>>     output = torch.empty_like(x)
2025-07-17T07:05:47.2323270Z             >>>     n_elements = output.numel()
2025-07-17T07:05:47.2323450Z             >>>
2025-07-17T07:05:47.2323590Z             >>>     def grid(meta):
2025-07-17T07:05:47.2323820Z             >>>         return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),)
2025-07-17T07:05:47.2324040Z             >>>
2025-07-17T07:05:47.2324230Z             >>>     # NB: we need to wrap the triton kernel in a call to wrap_triton
2025-07-17T07:05:47.2324540Z             >>>     wrap_triton(add_kernel)[grid](x, y, output, n_elements, 16)
2025-07-17T07:05:47.2324770Z             >>>     return output
2025-07-17T07:05:47.2324930Z             >>>
2025-07-17T07:05:47.2325080Z             >>> @torch.compile
2025-07-17T07:05:47.2325270Z             >>> def f(x, y):
2025-07-17T07:05:47.2325430Z             >>>     return add(x, y)
2025-07-17T07:05:47.2325590Z             >>>
2025-07-17T07:05:47.2325740Z             >>> x = torch.randn(3, device="cuda")
2025-07-17T07:05:47.2325960Z             >>> y = torch.randn(3, device="cuda")
2025-07-17T07:05:47.2326130Z             >>>
2025-07-17T07:05:47.2330860Z             >>> z = f(x, y)
2025-07-17T07:05:47.2331050Z             >>> assert torch.allclose(z, x + y)
2025-07-17T07:05:47.2331230Z     
2025-07-17T07:05:47.2331340Z         
2025-07-17T07:05:47.2331570Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2331840Z     
2025-07-17T07:05:47.2331950Z       warnings.warn(msg)
2025-07-17T07:05:47.2332090Z     
2025-07-17T07:05:47.2332280Z --- Parse Warning: 119 / 136 ---
2025-07-17T07:05:47.2333080Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=wrap_triton in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/triton.py line=202.
2025-07-17T07:05:47.2333960Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2334300Z     Allows capture of a triton kernel into a graph via make_fx or
2025-07-17T07:05:47.2334540Z         non-strict ``torch.export``.
2025-07-17T07:05:47.2334710Z     
2025-07-17T07:05:47.2334890Z         These technologies perform Dispatcher-based tracing (via
2025-07-17T07:05:47.2335190Z         ``__torch_dispatch__``) and cannot see calls to raw triton kernels.
2025-07-17T07:05:47.2335510Z         The ``wrap_triton`` API wraps a triton kernel into a callable that
2025-07-17T07:05:47.2335770Z         can actually be traced into a graph.
2025-07-17T07:05:47.2335950Z     
2025-07-17T07:05:47.2336140Z         Please use this API together with :func:`torch.library.triton_op`.
2025-07-17T07:05:47.2336380Z     
2025-07-17T07:05:47.2336480Z         Examples:
2025-07-17T07:05:47.2336610Z     
2025-07-17T07:05:47.2336720Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2336890Z             >>> import torch
2025-07-17T07:05:47.2337050Z             >>> import triton
2025-07-17T07:05:47.2337230Z             >>> from triton import language as tl
2025-07-17T07:05:47.2337490Z             >>> from torch.fx.experimental.proxy_tensor import make_fx
2025-07-17T07:05:47.2337750Z             >>> from torch.library import wrap_triton
2025-07-17T07:05:47.2337930Z             >>>
2025-07-17T07:05:47.2338060Z             >>> @triton.jit
2025-07-17T07:05:47.2338210Z             >>> def add_kernel(
2025-07-17T07:05:47.2338370Z             >>>     in_ptr0,
2025-07-17T07:05:47.2338520Z             >>>     in_ptr1,
2025-07-17T07:05:47.2338670Z             >>>     out_ptr,
2025-07-17T07:05:47.2338810Z             >>>     n_elements,
2025-07-17T07:05:47.2338990Z             >>>     BLOCK_SIZE: "tl.constexpr",
2025-07-17T07:05:47.2339170Z             >>> ):
2025-07-17T07:05:47.2339420Z             >>>     pid = tl.program_id(axis=0)
2025-07-17T07:05:47.2339630Z             >>>     block_start = pid * BLOCK_SIZE
2025-07-17T07:05:47.2339870Z             >>>     offsets = block_start + tl.arange(0, BLOCK_SIZE)
2025-07-17T07:05:47.2340130Z             >>>     mask = offsets < n_elements
2025-07-17T07:05:47.2340350Z             >>>     x = tl.load(in_ptr0 + offsets, mask=mask)
2025-07-17T07:05:47.2340570Z             >>>     y = tl.load(in_ptr1 + offsets, mask=mask)
2025-07-17T07:05:47.2340770Z             >>>     output = x + y
2025-07-17T07:05:47.2340980Z             >>>     tl.store(out_ptr + offsets, output, mask=mask)
2025-07-17T07:05:47.2341180Z             >>>
2025-07-17T07:05:47.2341310Z             >>> def add(x, y):
2025-07-17T07:05:47.2341490Z             >>>     output = torch.empty_like(x)
2025-07-17T07:05:47.2341690Z             >>>     n_elements = output.numel()
2025-07-17T07:05:47.2341890Z             >>>
2025-07-17T07:05:47.2342040Z             >>>     def grid_fn(meta):
2025-07-17T07:05:47.2342280Z             >>>         return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),)
2025-07-17T07:05:47.2342500Z             >>>
2025-07-17T07:05:47.2342700Z             >>>     wrap_triton(add_kernel)[grid_fn](x, y, output, n_elements, 16)
2025-07-17T07:05:47.2342940Z             >>>     return output
2025-07-17T07:05:47.2343100Z             >>>
2025-07-17T07:05:47.2343250Z             >>> x = torch.randn(3, device="cuda")
2025-07-17T07:05:47.2343460Z             >>> y = torch.randn(3, device="cuda")
2025-07-17T07:05:47.2343650Z             >>> gm = make_fx(add)(x, y)
2025-07-17T07:05:47.2343830Z             >>> print(gm.code)
2025-07-17T07:05:47.2344010Z             >>> # def forward(self, x_1, y_1):
2025-07-17T07:05:47.2344300Z             >>> #     empty_like = torch.ops.aten.empty_like.default(x_1, pin_memory = False)
2025-07-17T07:05:47.2344670Z             >>> #     triton_kernel_wrapper_mutation_proxy = triton_kernel_wrapper_mutation(
2025-07-17T07:05:47.2344970Z             >>> #         kernel_idx = 0, constant_args_idx = 0,
2025-07-17T07:05:47.2345200Z             >>> #         grid = [(1, 1, 1)], kwargs = {
2025-07-17T07:05:47.2345440Z             >>> #             'in_ptr0': x_1, 'in_ptr1': y_1, 'out_ptr': empty_like,
2025-07-17T07:05:47.2345690Z             >>> #             'n_elements': 3, 'BLOCK_SIZE': 16
2025-07-17T07:05:47.2345880Z             >>> #         })
2025-07-17T07:05:47.2346050Z             >>> #     return empty_like
2025-07-17T07:05:47.2346210Z     
2025-07-17T07:05:47.2346310Z         
2025-07-17T07:05:47.2346530Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2346790Z     
2025-07-17T07:05:47.2346910Z       warnings.warn(msg)
2025-07-17T07:05:47.2347050Z     
2025-07-17T07:05:47.2347210Z --- Parse Warning: 120 / 136 ---
2025-07-17T07:05:47.2348050Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=unsafe_generate_fake_kernels in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/fake_profile.py line=94.
2025-07-17T07:05:47.2348970Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2349240Z     
2025-07-17T07:05:47.2349440Z     Registers a fake kernel based on the given operator profiles. This fake
2025-07-17T07:05:47.2349790Z     kernel registration will override any existing fake kernel registrations.
2025-07-17T07:05:47.2350040Z     
2025-07-17T07:05:47.2350230Z     The input is a dictionary mapping operator names to a set of operator
2025-07-17T07:05:47.2350570Z     profiles, which we will use to generate fake kernels. The operator profiles
2025-07-17T07:05:47.2350910Z     are a record of the input and output tensor metadata. Based on this
2025-07-17T07:05:47.2351240Z     information we will match a given input to the recorded profile, and return
2025-07-17T07:05:47.2351630Z     an output with the same metadata as in the recorded profile. If a profile
2025-07-17T07:05:47.2351920Z     doesn't exist then an exception will be thrown.
2025-07-17T07:05:47.2352120Z     
2025-07-17T07:05:47.2352340Z     The fake kernel generation is considered unsafe because it relies on the
2025-07-17T07:05:47.2352680Z     rigid, pre-defined operator profiles that do not account for potential
2025-07-17T07:05:47.2353040Z     variations in output behavior. Specifically, the generated kernels assume a
2025-07-17T07:05:47.2353400Z     fixed relationship between input and output ranks. However, in reality, it's
2025-07-17T07:05:47.2353760Z     possible that data-dependent operations may produce outputs of different
2025-07-17T07:05:47.2354100Z     ranks even when given inputs of the same rank. The generated fake kernels
2025-07-17T07:05:47.2354490Z     are inflexible and unable to accommodate these nuances, making them
2025-07-17T07:05:47.2354770Z     potentially unsafe.
2025-07-17T07:05:47.2354910Z     
2025-07-17T07:05:47.2355020Z     Args:
2025-07-17T07:05:47.2355220Z         op_profiles (dict[str, set[OpProfile]]): A dictionary mapping operator
2025-07-17T07:05:47.2355540Z             name to a set of operator profiles from which we will generate fake
2025-07-17T07:05:47.2355770Z             kernels.
2025-07-17T07:05:47.2355900Z     
2025-07-17T07:05:47.2356010Z     Examples:
2025-07-17T07:05:47.2356120Z     
2025-07-17T07:05:47.2356290Z         >>> # Example: Registering an op-profile from draft-export
2025-07-17T07:05:47.2356510Z         >>> import torch
2025-07-17T07:05:47.2356710Z         >>> from torch.export._draft_export import draft_export
2025-07-17T07:05:47.2356920Z         >>>
2025-07-17T07:05:47.2357110Z         >>> @torch.library.custom_op("mylib::foo", mutates_args=())
2025-07-17T07:05:47.2357360Z         >>> def foo(x: Tensor, y: Tensor) -> Tensor:
2025-07-17T07:05:47.2357550Z         >>>     return x + y
2025-07-17T07:05:47.2357700Z         >>>
2025-07-17T07:05:47.2357830Z         >>> class M(torch.nn.Module):
2025-07-17T07:05:47.2358020Z         >>>     def forward(self, a, b):
2025-07-17T07:05:47.2358240Z         >>>         res = torch.ops.mylib.foo(a, b)  # no fake impl
2025-07-17T07:05:47.2358460Z         >>>         return res
2025-07-17T07:05:47.2358610Z         >>>
2025-07-17T07:05:47.2358790Z         >>> ep = draft_export(M(), (torch.ones(3, 4), torch.ones(3, 4))
2025-07-17T07:05:47.2359000Z         >>>
2025-07-17T07:05:47.2359250Z         >>> with torch._library.fake_profile.unsafe_generate_fake_kernels(ep._report.op_profiles):
2025-07-17T07:05:47.2359580Z         >>>     decomp = ep.run_decompositions()
2025-07-17T07:05:47.2359760Z     
2025-07-17T07:05:47.2359860Z     
2025-07-17T07:05:47.2360080Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2360330Z     
2025-07-17T07:05:47.2360440Z       warnings.warn(msg)
2025-07-17T07:05:47.2360580Z     
2025-07-17T07:05:47.2360750Z --- Parse Warning: 121 / 136 ---
2025-07-17T07:05:47.2361580Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CustomOpDef.register_fake in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_library/custom_ops.py line=396.
2025-07-17T07:05:47.2362510Z     Caused by: DoctestParseError('Failed to parse doctest in _package_groups')
2025-07-17T07:05:47.2362830Z     Register a FakeTensor implementation for this custom op.
2025-07-17T07:05:47.2363050Z     
2025-07-17T07:05:47.2363260Z             This is necessary to get the operator to work efficiently with torch.compile.
2025-07-17T07:05:47.2363520Z     
2025-07-17T07:05:47.2363710Z             The Fake impl (sometimes also known as a meta kernel or abstract impl)
2025-07-17T07:05:47.2364060Z             specifies the behavior of this operator on Tensors that carry no data.
2025-07-17T07:05:47.2364410Z             Given some input Tensors with certain properties
2025-07-17T07:05:47.2364730Z             (sizes/strides/storage_offset/device), it specifies what the properties of
2025-07-17T07:05:47.2365000Z             the output Tensors are.
2025-07-17T07:05:47.2365220Z     
2025-07-17T07:05:47.2365410Z             Please see :func:`torch.library.impl_abstract` for more details.
2025-07-17T07:05:47.2365640Z     
2025-07-17T07:05:47.2365740Z             Args:
2025-07-17T07:05:47.2365930Z                 fn (Callable): The function to register as the FakeTensor
2025-07-17T07:05:47.2366160Z                     implementation.
2025-07-17T07:05:47.2366320Z     
2025-07-17T07:05:47.2366430Z             Examples:
2025-07-17T07:05:47.2366570Z                 >>> import torch
2025-07-17T07:05:47.2366740Z                 >>> import numpy as np
2025-07-17T07:05:47.2366930Z                 >>> from torch import Tensor
2025-07-17T07:05:47.2367110Z                 >>>
2025-07-17T07:05:47.2367330Z                 >>> # Example 1: an operator without data-dependent output shape
2025-07-17T07:05:47.2367660Z                 >>> @torch.library.custom_op("mylib::linear", mutates_args=())
2025-07-17T07:05:47.2367960Z                 >>> def linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor:
2025-07-17T07:05:47.2368220Z                 >>>     return (x @ weight.t()) + bias
2025-07-17T07:05:47.2368400Z                 >>>
2025-07-17T07:05:47.2368540Z                 >>> @linear.register_fake
2025-07-17T07:05:47.2368730Z                 >>> def _(x, weight, bias):
2025-07-17T07:05:47.2368920Z                 >>>     assert x.dim() == 2
2025-07-17T07:05:47.2369110Z                 >>>     assert weight.dim() == 2
2025-07-17T07:05:47.2369310Z                 >>>     assert bias.dim() == 1
2025-07-17T07:05:47.2369530Z                 >>>     assert x.shape[1] == weight.shape[1]
2025-07-17T07:05:47.2369760Z                 >>>     assert weight.shape[0] == bias.shape[0]
2025-07-17T07:05:47.2369990Z                 >>>     assert x.device == weight.device
2025-07-17T07:05:47.2370230Z                 >>>     return x.new_empty(x.size(0), weight.size(0))
2025-07-17T07:05:47.2370430Z                 >>>
2025-07-17T07:05:47.2370570Z                 >>> x = torch.randn(2, 2)
2025-07-17T07:05:47.2370770Z                 >>> weight = torch.randn(2, 2)
2025-07-17T07:05:47.2370960Z                 >>> bias = torch.randn(2)
2025-07-17T07:05:47.2371170Z                 >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-07-17T07:05:47.2371440Z                 >>> out = torch.compile(linear, fullgraph=True)(x, weight, bias)
2025-07-17T07:05:47.2371710Z                 >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-07-17T07:05:47.2372020Z                 >>> assert torch.allclose(out, torch.nn.functional.linear(x, weight, bias))
2025-07-17T07:05:47.2372280Z                 >>>
2025-07-17T07:05:47.2372470Z                 >>> # Example 2: an operator with data-dependent output shape
2025-07-17T07:05:47.2372770Z                 >>> @torch.library.custom_op("mylib::nonzero", mutates_args=())
2025-07-17T07:05:47.2373040Z                 >>> def nonzero(x: Tensor) -> Tensor:
2025-07-17T07:05:47.2373250Z                 >>>     x_np = x.cpu().numpy()
2025-07-17T07:05:47.2373460Z                 >>>     res = np.stack(np.nonzero(x_np), axis=1)
2025-07-17T07:05:47.2373700Z                 >>>     return torch.tensor(res, device=x.device)
2025-07-17T07:05:47.2373890Z                 >>>
2025-07-17T07:05:47.2374040Z                 >>> @nonzero.register_fake
2025-07-17T07:05:47.2374220Z                 >>> def _(x):
2025-07-17T07:05:47.2374420Z                 >>> # Number of nonzero-elements is data-dependent.
2025-07-17T07:05:47.2374690Z                 >>> # Since we cannot peek at the data in an abstract impl,
2025-07-17T07:05:47.2374960Z                 >>> # we use the ctx object to construct a new symint that
2025-07-17T07:05:47.2375200Z                 >>> # represents the data-dependent size.
2025-07-17T07:05:47.2375420Z                 >>>     ctx = torch.library.get_ctx()
2025-07-17T07:05:47.2375690Z                 >>>     nnz = ctx.new_dynamic_size()
2025-07-17T07:05:47.2375900Z                 >>>     shape = [nnz, x.dim()]
2025-07-17T07:05:47.2376130Z                 >>>     result = x.new_empty(shape, dtype=torch.int64)
2025-07-17T07:05:47.2376360Z                 >>>     return result
2025-07-17T07:05:47.2376530Z                 >>>
2025-07-17T07:05:47.2376680Z                 >>> x = torch.tensor([0, 1, 2, 0, 0, 1])
2025-07-17T07:05:47.2376900Z                 >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-07-17T07:05:47.2377150Z                 >>> out = torch.compile(nonzero, fullgraph=True)(x)
2025-07-17T07:05:47.2377390Z                 >>> # xdoctest: +SKIP("Requires Python <= 3.11")
2025-07-17T07:05:47.2377620Z                 >>> assert torch.allclose(out, x.nonzero())
2025-07-17T07:05:47.2377810Z     
2025-07-17T07:05:47.2377910Z             
2025-07-17T07:05:47.2378310Z     Original Error: IndentationError('expected an indented block after function definition on line 36', ('<source_block>', 37, 1, '_._ = None\n', 37, 2))
2025-07-17T07:05:47.2378750Z     
2025-07-17T07:05:47.2378850Z     _._ = None
2025-07-17T07:05:47.2378960Z     ^
2025-07-17T07:05:47.2379080Z       warnings.warn(msg)
2025-07-17T07:05:47.2379220Z     
2025-07-17T07:05:47.2379380Z --- Parse Warning: 122 / 136 ---
2025-07-17T07:05:47.2380190Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Conv1d in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/conv.py line=354.
2025-07-17T07:05:47.2381080Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2381440Z     Applies a 1D convolution over a quantized input signal composed of
2025-07-17T07:05:47.2381700Z         several quantized input planes.
2025-07-17T07:05:47.2381870Z     
2025-07-17T07:05:47.2382070Z         For details on input arguments, parameters, and implementation see
2025-07-17T07:05:47.2382320Z         :class:`~torch.nn.Conv1d`.
2025-07-17T07:05:47.2382480Z     
2025-07-17T07:05:47.2382580Z         .. note::
2025-07-17T07:05:47.2382840Z             Only `zeros` is supported for the :attr:`padding_mode` argument.
2025-07-17T07:05:47.2383070Z     
2025-07-17T07:05:47.2383170Z         .. note::
2025-07-17T07:05:47.2383360Z             Only `torch.quint8` is supported for the input data type.
2025-07-17T07:05:47.2383580Z     
2025-07-17T07:05:47.2383670Z     
2025-07-17T07:05:47.2383780Z         Attributes:
2025-07-17T07:05:47.2384000Z             weight (Tensor):     packed tensor derived from the learnable weight
2025-07-17T07:05:47.2384250Z                                  parameter.
2025-07-17T07:05:47.2384470Z             scale (Tensor):      scalar for the output scale
2025-07-17T07:05:47.2384730Z             zero_point (Tensor): scalar for the output zero point
2025-07-17T07:05:47.2384930Z     
2025-07-17T07:05:47.2385090Z         See :class:`~torch.nn.Conv1d` for other attributes.
2025-07-17T07:05:47.2385280Z     
2025-07-17T07:05:47.2385390Z         Examples::
2025-07-17T07:05:47.2385520Z     
2025-07-17T07:05:47.2385670Z             >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_QENGINE)
2025-07-17T07:05:47.2385910Z             >>> m = nn.quantized.Conv1d(16, 33, 3, stride=2)
2025-07-17T07:05:47.2386120Z             >>> input = torch.randn(20, 16, 100)
2025-07-17T07:05:47.2386320Z             >>> # quantize input to quint8
2025-07-17T07:05:47.2386510Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2386760Z             >>> q_input = torch.quantize_per_tensor(input, scale=1.0, zero_point=0,
2025-07-17T07:05:47.2387050Z             ...                                     dtype=torch.quint8)
2025-07-17T07:05:47.2387250Z             >>> output = m(q_input)
2025-07-17T07:05:47.2387420Z     
2025-07-17T07:05:47.2387520Z         
2025-07-17T07:05:47.2387800Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2388060Z     
2025-07-17T07:05:47.2388170Z       warnings.warn(msg)
2025-07-17T07:05:47.2388310Z     
2025-07-17T07:05:47.2388470Z --- Parse Warning: 123 / 136 ---
2025-07-17T07:05:47.2389310Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LSTM in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/nn/quantized/modules/rnn.py line=12.
2025-07-17T07:05:47.2390180Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2390470Z     A quantized long short-term memory (LSTM).
2025-07-17T07:05:47.2390660Z     
2025-07-17T07:05:47.2390890Z         For the description and the argument types, please, refer to :class:`~torch.nn.LSTM`
2025-07-17T07:05:47.2391160Z     
2025-07-17T07:05:47.2391280Z         Attributes:
2025-07-17T07:05:47.2391460Z             layers : instances of the `_LSTMLayer`
2025-07-17T07:05:47.2391650Z     
2025-07-17T07:05:47.2391750Z         .. note::
2025-07-17T07:05:47.2391960Z             To access the weights and biases, you need to access them per layer.
2025-07-17T07:05:47.2392270Z             See examples in :class:`~torch.ao.nn.quantizable.LSTM`
2025-07-17T07:05:47.2392490Z     
2025-07-17T07:05:47.2392590Z         Examples::
2025-07-17T07:05:47.2392730Z             >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2396690Z             >>> custom_module_config = {
2025-07-17T07:05:47.2396910Z             ...     'float_to_observed_custom_module_class': {
2025-07-17T07:05:47.2397140Z             ...         nn.LSTM: nn.quantizable.LSTM,
2025-07-17T07:05:47.2397330Z             ...     },
2025-07-17T07:05:47.2397520Z             ...     'observed_to_quantized_custom_module_class': {
2025-07-17T07:05:47.2397770Z             ...         nn.quantizable.LSTM: nn.quantized.LSTM,
2025-07-17T07:05:47.2397980Z             ...     }
2025-07-17T07:05:47.2398120Z             ... }
2025-07-17T07:05:47.2398340Z             >>> tq.prepare(model, prepare_custom_module_class=custom_module_config)
2025-07-17T07:05:47.2398670Z             >>> tq.convert(model, convert_custom_module_class=custom_module_config)
2025-07-17T07:05:47.2398910Z         
2025-07-17T07:05:47.2399130Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2399390Z     
2025-07-17T07:05:47.2399500Z       warnings.warn(msg)
2025-07-17T07:05:47.2399640Z     
2025-07-17T07:05:47.2399840Z --- Parse Warning: 124 / 136 ---
2025-07-17T07:05:47.2400730Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DTypeConfig in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/backend_config/backend_config.py line=181.
2025-07-17T07:05:47.2401690Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2401950Z     
2025-07-17T07:05:47.2402160Z     Config object that specifies the supported data types passed as arguments to
2025-07-17T07:05:47.2402520Z     quantize ops in the reference model spec, for input and output activations,
2025-07-17T07:05:47.2402790Z     weights, and biases.
2025-07-17T07:05:47.2402930Z     
2025-07-17T07:05:47.2403030Z     For example, consider the following reference model:
2025-07-17T07:05:47.2403070Z     
2025-07-17T07:05:47.2403160Z       quant1 - [dequant1 - fp32_linear - quant2] - dequant2
2025-07-17T07:05:47.2403200Z     
2025-07-17T07:05:47.2403340Z     The pattern in the square brackets refers to the reference pattern of
2025-07-17T07:05:47.2403480Z     statically quantized linear. Setting the input dtype as `torch.quint8`
2025-07-17T07:05:47.2403620Z     in the DTypeConfig means we pass in `torch.quint8` as the dtype argument
2025-07-17T07:05:47.2403870Z     to the first quantize op (quant1). Similarly, setting the output dtype as
2025-07-17T07:05:47.2404010Z     `torch.quint8` means we pass in `torch.quint8` as the dtype argument to
2025-07-17T07:05:47.2404070Z     the second quantize op (quant2).
2025-07-17T07:05:47.2404110Z     
2025-07-17T07:05:47.2404270Z     Note that the dtype here does not refer to the interface dtypes of the
2025-07-17T07:05:47.2404390Z     op. For example, the "input dtype" here is not the dtype of the input
2025-07-17T07:05:47.2404520Z     tensor passed to the quantized linear op. Though it can still be the
2025-07-17T07:05:47.2404640Z     same as the interface dtype, this is not always the case, e.g. the
2025-07-17T07:05:47.2404770Z     interface dtype is fp32 in dynamic quantization but the "input dtype"
2025-07-17T07:05:47.2404900Z     specified in the DTypeConfig would still be quint8. The semantics of
2025-07-17T07:05:47.2405020Z     dtypes here are the same as the semantics of the dtypes specified in
2025-07-17T07:05:47.2405120Z     the observers.
2025-07-17T07:05:47.2405190Z     
2025-07-17T07:05:47.2405320Z     These dtypes are matched against the ones specified in the user's
2025-07-17T07:05:47.2405450Z     QConfig. If there is a match, and the QConfig satisfies the constraints
2025-07-17T07:05:47.2405580Z     specified in the DTypeConfig (if any), then we will quantize the given
2025-07-17T07:05:47.2405720Z     pattern using this DTypeConfig. Otherwise, the QConfig is ignored and
2025-07-17T07:05:47.2405780Z     the pattern will not be quantized.
2025-07-17T07:05:47.2405820Z     
2025-07-17T07:05:47.2405900Z     Example usage::
2025-07-17T07:05:47.2405940Z     
2025-07-17T07:05:47.2406000Z         >>> # xdoctest: +SKIP(failing)
2025-07-17T07:05:47.2406060Z         >>> dtype_config1 = DTypeConfig(
2025-07-17T07:05:47.2406120Z         ...     input_dtype=torch.quint8,
2025-07-17T07:05:47.2406180Z         ...     output_dtype=torch.quint8,
2025-07-17T07:05:47.2406240Z         ...     weight_dtype=torch.qint8,
2025-07-17T07:05:47.2406300Z         ...     bias_dtype=torch.float)
2025-07-17T07:05:47.2406340Z     
2025-07-17T07:05:47.2406400Z         >>> dtype_config2 = DTypeConfig(
2025-07-17T07:05:47.2406480Z         ...     input_dtype=DTypeWithConstraints(
2025-07-17T07:05:47.2406540Z         ...         dtype=torch.quint8,
2025-07-17T07:05:47.2406600Z         ...         quant_min_lower_bound=0,
2025-07-17T07:05:47.2406670Z         ...         quant_max_upper_bound=255,
2025-07-17T07:05:47.2406710Z         ...     ),
2025-07-17T07:05:47.2406790Z         ...     output_dtype=DTypeWithConstraints(
2025-07-17T07:05:47.2406840Z         ...         dtype=torch.quint8,
2025-07-17T07:05:47.2406900Z         ...         quant_min_lower_bound=0,
2025-07-17T07:05:47.2406970Z         ...         quant_max_upper_bound=255,
2025-07-17T07:05:47.2407010Z         ...     ),
2025-07-17T07:05:47.2407080Z         ...     weight_dtype=DTypeWithConstraints(
2025-07-17T07:05:47.2407140Z         ...         dtype=torch.qint8,
2025-07-17T07:05:47.2407200Z         ...         quant_min_lower_bound=-128,
2025-07-17T07:05:47.2407270Z         ...         quant_max_upper_bound=127,
2025-07-17T07:05:47.2407310Z         ...     ),
2025-07-17T07:05:47.2407370Z         ...     bias_dtype=torch.float)
2025-07-17T07:05:47.2407410Z     
2025-07-17T07:05:47.2407470Z         >>> dtype_config1.input_dtype
2025-07-17T07:05:47.2407510Z         torch.quint8
2025-07-17T07:05:47.2407550Z     
2025-07-17T07:05:47.2407610Z         >>> dtype_config2.input_dtype
2025-07-17T07:05:47.2407660Z         torch.quint8
2025-07-17T07:05:47.2407700Z     
2025-07-17T07:05:47.2407780Z         >>> dtype_config2.input_dtype_with_constraints
2025-07-17T07:05:47.2408100Z         DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=0, quant_max_upper_bound=255, scale_min_lower_bound=None, scale_max_upper_bound=None)
2025-07-17T07:05:47.2408140Z     
2025-07-17T07:05:47.2408290Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2408330Z     
2025-07-17T07:05:47.2408390Z       warnings.warn(msg)
2025-07-17T07:05:47.2408450Z     
2025-07-17T07:05:47.2408550Z --- Parse Warning: 125 / 136 ---
2025-07-17T07:05:47.2409400Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_filtered_tables in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=301.
2025-07-17T07:05:47.2409580Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2409620Z     
2025-07-17T07:05:47.2409780Z     Takes in optional filter values and generates two tables with desired information.
2025-07-17T07:05:47.2409820Z     
2025-07-17T07:05:47.2409940Z     The generated tables are presented in both a list-of-lists format
2025-07-17T07:05:47.2409980Z     
2025-07-17T07:05:47.2410120Z     The reason for the two tables are that they handle different things:
2025-07-17T07:05:47.2410240Z     1.) the first table handles all tensor level information
2025-07-17T07:05:47.2410370Z     2.) the second table handles and displays all channel based information
2025-07-17T07:05:47.2410420Z     
2025-07-17T07:05:47.2410610Z     The reasoning for this is that having all the info in one table can make it ambiguous which collected
2025-07-17T07:05:47.2410800Z         statistics are global, and which are actually per-channel, so it's better to split it up into two
2025-07-17T07:05:47.2411010Z         tables. This also makes the information much easier to digest given the plethora of statistics collected
2025-07-17T07:05:47.2411050Z     
2025-07-17T07:05:47.2411100Z     Tensor table columns:
2025-07-17T07:05:47.2411220Z         idx  layer_fqn  feature_1   feature_2   feature_3   .... feature_n
2025-07-17T07:05:47.2411320Z         ----  ---------  ---------   ---------   ---------        ---------
2025-07-17T07:05:47.2411360Z     
2025-07-17T07:05:47.2411420Z     Per-Channel table columns:
2025-07-17T07:05:47.2411560Z         idx  layer_fqn  channel  feature_1   feature_2   feature_3   .... feature_n
2025-07-17T07:05:47.2411670Z         ----  ---------  -------  ---------   ---------   ---------        ---------
2025-07-17T07:05:47.2411700Z     
2025-07-17T07:05:47.2411750Z     Args:
2025-07-17T07:05:47.2411900Z         feature_filter (str, optional): Filters the features presented to only those that
2025-07-17T07:05:47.2411970Z             contain this filter substring
2025-07-17T07:05:47.2412060Z             Default = "", results in all the features being printed
2025-07-17T07:05:47.2412220Z         module_fqn_filter (str, optional): Only includes modules that contains this string
2025-07-17T07:05:47.2412370Z             Default = "", results in all the modules in the reports to be visible in the table
2025-07-17T07:05:47.2412410Z     
2025-07-17T07:05:47.2412470Z     Returns a dictionary with two keys:
2025-07-17T07:05:47.2412580Z         (Dict[str, Tuple[List, List]]) A dict containing two keys:
2025-07-17T07:05:47.2412660Z         "tensor_level_info", "channel_level_info"
2025-07-17T07:05:47.2412720Z             Each key maps to a tuple with:
2025-07-17T07:05:47.2412790Z                 A list of the headers of each table
2025-07-17T07:05:47.2412900Z                 A list of lists containing the table information row by row
2025-07-17T07:05:47.2413010Z                 The 0th index row will contain the headers of the columns
2025-07-17T07:05:47.2413080Z                 The rest of the rows will contain data
2025-07-17T07:05:47.2413120Z     
2025-07-17T07:05:47.2413170Z     Example Use:
2025-07-17T07:05:47.2413240Z         >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:47.2413330Z         >>> mod_report_visualizer.generate_filtered_tables(
2025-07-17T07:05:47.2413450Z         ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-07-17T07:05:47.2413620Z         ... )  # generates table with per_channel_min info for all modules in block 1 of the model
2025-07-17T07:05:47.2413710Z     
2025-07-17T07:05:47.2413860Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2413900Z     
2025-07-17T07:05:47.2413950Z       warnings.warn(msg)
2025-07-17T07:05:47.2414010Z     
2025-07-17T07:05:47.2414110Z --- Parse Warning: 126 / 136 ---
2025-07-17T07:05:47.2414970Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_table_visualization in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=399.
2025-07-17T07:05:47.2415130Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2415170Z     
2025-07-17T07:05:47.2415350Z     Takes in optional filter values and prints out formatted tables of the information.
2025-07-17T07:05:47.2415410Z     
2025-07-17T07:05:47.2415610Z     The reason for the two tables printed out instead of one large one are that they handle different things:
2025-07-17T07:05:47.2415710Z     1.) the first table handles all tensor level information
2025-07-17T07:05:47.2415840Z     2.) the second table handles and displays all channel based information
2025-07-17T07:05:47.2415880Z     
2025-07-17T07:05:47.2416070Z     The reasoning for this is that having all the info in one table can make it ambiguous which collected
2025-07-17T07:05:47.2416260Z         statistics are global, and which are actually per-channel, so it's better to split it up into two
2025-07-17T07:05:47.2416470Z         tables. This also makes the information much easier to digest given the plethora of statistics collected
2025-07-17T07:05:47.2416510Z     
2025-07-17T07:05:47.2416560Z     Tensor table columns:
2025-07-17T07:05:47.2416680Z      idx  layer_fqn  feature_1   feature_2   feature_3   .... feature_n
2025-07-17T07:05:47.2416780Z     ----  ---------  ---------   ---------   ---------        ---------
2025-07-17T07:05:47.2416820Z     
2025-07-17T07:05:47.2416880Z     Per-Channel table columns:
2025-07-17T07:05:47.2416920Z     
2025-07-17T07:05:47.2417060Z      idx  layer_fqn  channel  feature_1   feature_2   feature_3   .... feature_n
2025-07-17T07:05:47.2417160Z     ----  ---------  -------  ---------   ---------   ---------        ---------
2025-07-17T07:05:47.2417200Z     
2025-07-17T07:05:47.2417240Z     Args:
2025-07-17T07:05:47.2417400Z         feature_filter (str, optional): Filters the features presented to only those that
2025-07-17T07:05:47.2417460Z             contain this filter substring
2025-07-17T07:05:47.2417560Z             Default = "", results in all the features being printed
2025-07-17T07:05:47.2417710Z         module_fqn_filter (str, optional): Only includes modules that contains this string
2025-07-17T07:05:47.2417860Z             Default = "", results in all the modules in the reports to be visible in the table
2025-07-17T07:05:47.2417910Z     
2025-07-17T07:05:47.2417950Z     Example Use:
2025-07-17T07:05:47.2418030Z         >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:47.2418130Z         >>> mod_report_visualizer.generate_table_visualization(
2025-07-17T07:05:47.2418250Z         ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-07-17T07:05:47.2418290Z         ... )
2025-07-17T07:05:47.2418410Z         >>> # prints out neatly formatted table with per_channel_min info
2025-07-17T07:05:47.2418480Z         >>> # for all modules in block 1 of the model
2025-07-17T07:05:47.2418520Z     
2025-07-17T07:05:47.2418670Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2418710Z     
2025-07-17T07:05:47.2418760Z       warnings.warn(msg)
2025-07-17T07:05:47.2418800Z     
2025-07-17T07:05:47.2418900Z --- Parse Warning: 127 / 136 ---
2025-07-17T07:05:47.2419770Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_plot_visualization in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=564.
2025-07-17T07:05:47.2419960Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2420000Z     
2025-07-17T07:05:47.2420140Z     Takes in a feature and optional module_filter and plots of the desired data.
2025-07-17T07:05:47.2420180Z     
2025-07-17T07:05:47.2420340Z     For per channel features, it averages the value across the channels and plots a point
2025-07-17T07:05:47.2420490Z     per module. The reason for this is that for models with hundreds of channels, it can
2025-07-17T07:05:47.2420660Z     be hard to differentiate one channel line from another, and so the point of generating
2025-07-17T07:05:47.2420830Z     a single average point per module is to give a sense of general trends that encourage
2025-07-17T07:05:47.2420900Z     further deep dives.
2025-07-17T07:05:47.2420940Z     
2025-07-17T07:05:47.2420980Z     Note:
2025-07-17T07:05:47.2421140Z         Only features in the report that have tensor value data are plottable by this class
2025-07-17T07:05:47.2421240Z         When the tensor information is plotted, it will plot:
2025-07-17T07:05:47.2421330Z             idx as the x val, feature value as the y_val
2025-07-17T07:05:47.2421430Z         When the channel information is plotted, it will plot:
2025-07-17T07:05:47.2421590Z             the first idx of each module as the x val, feature value as the y_val [for each channel]
2025-07-17T07:05:47.2421730Z             The reason for this is that we want to be able to compare values across the
2025-07-17T07:05:47.2421870Z             channels for same layer, and it will be hard if values are staggered by idx
2025-07-17T07:05:47.2421970Z             This means each module is represented by only 1 x value
2025-07-17T07:05:47.2422010Z     Args:
2025-07-17T07:05:47.2422150Z         feature_filter (str): Filters the features presented to only those that
2025-07-17T07:05:47.2422210Z             contain this filter substring
2025-07-17T07:05:47.2422370Z         module_fqn_filter (str, optional): Only includes modules that contains this string
2025-07-17T07:05:47.2422520Z             Default = "", results in all the modules in the reports to be visible in the table
2025-07-17T07:05:47.2422560Z     
2025-07-17T07:05:47.2422600Z     Example Use:
2025-07-17T07:05:47.2422680Z         >>> # xdoctest: +SKIP("undefined variables")
2025-07-17T07:05:47.2422780Z         >>> mod_report_visualizer.generate_plot_visualization(
2025-07-17T07:05:47.2422900Z         ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-07-17T07:05:47.2422940Z         ... )
2025-07-17T07:05:47.2423050Z         >>> # outputs line plot of per_channel_min information for all
2025-07-17T07:05:47.2423160Z         >>> # modules in block1 of model each channel gets it's own line,
2025-07-17T07:05:47.2423270Z         >>> # and it's plotted across the in-order modules on the x-axis
2025-07-17T07:05:47.2423310Z     
2025-07-17T07:05:47.2423450Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2423500Z     
2025-07-17T07:05:47.2423550Z       warnings.warn(msg)
2025-07-17T07:05:47.2423590Z     
2025-07-17T07:05:47.2423690Z --- Parse Warning: 128 / 136 ---
2025-07-17T07:05:47.2424550Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_histogram_visualization in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=643.
2025-07-17T07:05:47.2424710Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2424770Z     
2025-07-17T07:05:47.2424940Z     Takes in a feature and optional module_filter and plots the histogram of desired data.
2025-07-17T07:05:47.2424980Z     
2025-07-17T07:05:47.2425020Z     Note:
2025-07-17T07:05:47.2425200Z         Only features in the report that have tensor value data can be viewed as a histogram
2025-07-17T07:05:47.2425360Z         If you want to plot a histogram from all the channel values of a specific feature for
2025-07-17T07:05:47.2425510Z             a specific model, make sure to specify both the model and the feature properly
2025-07-17T07:05:47.2425660Z             in the filters and you should be able to see a distribution of the channel data
2025-07-17T07:05:47.2425700Z     
2025-07-17T07:05:47.2425740Z     Args:
2025-07-17T07:05:47.2425890Z         feature_filter (str, optional): Filters the features presented to only those that
2025-07-17T07:05:47.2425980Z             contain this filter substring
2025-07-17T07:05:47.2426110Z             Default = "", results in all the features being printed
2025-07-17T07:05:47.2426270Z         module_fqn_filter (str, optional): Only includes modules that contains this string
2025-07-17T07:05:47.2426420Z             Default = "", results in all the modules in the reports to be visible in the table
2025-07-17T07:05:47.2426550Z         num_bins (int, optional): The number of bins to create the histogram with
2025-07-17T07:05:47.2426670Z             Default = 10, the values will be split into 10 equal sized bins
2025-07-17T07:05:47.2426710Z     
2025-07-17T07:05:47.2426750Z     Example Use:
2025-07-17T07:05:47.2426810Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2426990Z         >>> mod_report_visualizer.generategenerate_histogram_visualization_plot_visualization(
2025-07-17T07:05:47.2427100Z         ...     feature_filter="per_channel_min", module_fqn_filter="block1"
2025-07-17T07:05:47.2427150Z         ... )
2025-07-17T07:05:47.2427310Z         # outputs histogram of per_channel_min information for all modules in block1 of model
2025-07-17T07:05:47.2427470Z             information is gathered across all channels for all modules in block 1 for the
2025-07-17T07:05:47.2427600Z             per_channel_min and is displayed in a histogram of equally sized bins
2025-07-17T07:05:47.2427640Z     
2025-07-17T07:05:47.2427790Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2427830Z     
2025-07-17T07:05:47.2427880Z       warnings.warn(msg)
2025-07-17T07:05:47.2427920Z     
2025-07-17T07:05:47.2428020Z --- Parse Warning: 129 / 136 ---
2025-07-17T07:05:47.2428750Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReport in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/quantization/fx/_model_report/model_report.py line=24.
2025-07-17T07:05:47.2428900Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2428950Z     
2025-07-17T07:05:47.2429130Z     The ModelReport class aims to provide users an easy way to diagnose issues that they run into
2025-07-17T07:05:47.2429300Z     with their models. The class works with all traceable GraphModules to help diagnose issues,
2025-07-17T07:05:47.2429480Z     though the requirements on the type of model more-so depends on the specific report the user
2025-07-17T07:05:47.2429660Z     is trying to generate. With respect to the reports, the ModelReport class is initialized with
2025-07-17T07:05:47.2429820Z     a set of Detector classes, each of which generate reports on quantization configuration
2025-07-17T07:05:47.2429880Z     issues a use might have.
2025-07-17T07:05:47.2429920Z     
2025-07-17T07:05:47.2429990Z     Currently supports generating reports on:
2025-07-17T07:05:47.2430130Z     - Suggestions for per-channel vs. per-tensor quantization (nn.Module)
2025-07-17T07:05:47.2430310Z     - Suggestions for dynamic vs static quantization for linear layers (Graph Modules)
2025-07-17T07:05:47.2430490Z     - Suggestions for input-weight equalization for linear and conv layers (Graph Modules)
2025-07-17T07:05:47.2430620Z     - Suggestions for outlier detection for all layers (Graph Modules)
2025-07-17T07:05:47.2430680Z     
2025-07-17T07:05:47.2430920Z     The ModelReport class has the primary functionality of inserting observers (primarily the ModelReportObserver)
2025-07-17T07:05:47.2431140Z     where needed for each detector to gather the information it needs, and then after calibration, the ModelReport
2025-07-17T07:05:47.2431350Z     class compiles the report generated by each Detector class into a single report to return to the user. It also
2025-07-17T07:05:47.2431480Z     has the capability to remove all the observers it inserted as well.
2025-07-17T07:05:47.2431520Z     
2025-07-17T07:05:47.2431720Z     * :attr:`_model` The model we wish to generate the report for. Must be a traceable GraphModule
2025-07-17T07:05:47.2431780Z     
2025-07-17T07:05:47.2432000Z     * :attr:`_desired_report_detectors` The set of Detectors representing desired reports from the ModelReport class
2025-07-17T07:05:47.2432190Z         Make sure that these are all unique types of detectors [do not have more than 1 of the same class]
2025-07-17T07:05:47.2432230Z     
2025-07-17T07:05:47.2432400Z     * :attr:`_desired_detector_names` The set of detector names of the _desired_report_detectors.
2025-07-17T07:05:47.2432540Z         This set is generated by calling the get_detector_name() of each detector
2025-07-17T07:05:47.2432580Z     
2025-07-17T07:05:47.2432770Z     * :attr:`_detector_name_to_observer_fqns` The mapping from each detector to fqns of observers of interest
2025-07-17T07:05:47.2432960Z         The purpose of this is to keep track of what observers were inserted for each detector, so that they
2025-07-17T07:05:47.2433030Z         can be removed at the end if desired
2025-07-17T07:05:47.2433070Z     
2025-07-17T07:05:47.2433260Z     * :attr:`_prepared_flag` A boolean flag that keeps track of whether we have prepared the model or not
2025-07-17T07:05:47.2433410Z         This is to ensure we only insert observers once with the ModelReport instance
2025-07-17T07:05:47.2433450Z     
2025-07-17T07:05:47.2433600Z     * :attr:`_removed_observers` A boolean to track if we have removed observers already
2025-07-17T07:05:47.2433770Z         The purpose is to ensure we don't attempt to remove observers twice with the same ModelReport
2025-07-17T07:05:47.2433960Z         instance. This also allows the functionality where we can generate the report multiple times
2025-07-17T07:05:47.2434050Z         as long as we haven't removed the observers yet.
2025-07-17T07:05:47.2434090Z     
2025-07-17T07:05:47.2434130Z     Note:
2025-07-17T07:05:47.2434310Z         This class was initially designed to work with the Fx Graph Mode workflow in mind. However,
2025-07-17T07:05:47.2434490Z         full functionality is available as long as there is a traceable GraphModule that is being used.
2025-07-17T07:05:47.2434670Z         One method to get a traceable GraphModule without going through the Fx workflow is to use
2025-07-17T07:05:47.2434730Z         the QuantizationTracer class.
2025-07-17T07:05:47.2434770Z     
2025-07-17T07:05:47.2434830Z     General Flow for Fx workflow:
2025-07-17T07:05:47.2435060Z     1.) Initialize ModelReport object with reports of interest by passing in initialized detector objects and model
2025-07-17T07:05:47.2435130Z     2.) Prepare your model with prepare_fx
2025-07-17T07:05:47.2435270Z     3.) Call model_report.prepare_detailed_calibration to add relevant observers
2025-07-17T07:05:47.2435340Z     4.) Calibrate your model with data
2025-07-17T07:05:47.2435540Z     5.) Call model_report.generate_report on your model to generate report and optionally remove added observers
2025-07-17T07:05:47.2435590Z     Optional
2025-07-17T07:05:47.2435750Z         6.) Call model_report.generate_visualizer to get a ModelReportVisualizer instance
2025-07-17T07:05:47.2435950Z         7.) To help in parsing report information and debugging, view report info as a:
2025-07-17T07:05:47.2436000Z             - Table
2025-07-17T07:05:47.2436050Z             - Histogram
2025-07-17T07:05:47.2436100Z             - Line plot
2025-07-17T07:05:47.2436310Z     8.) Call model_report.generate_qconfigs to generate the qconfigs based on the report suggestions
2025-07-17T07:05:47.2436350Z     
2025-07-17T07:05:47.2436410Z     Example (with QuantizationTracer):
2025-07-17T07:05:47.2436470Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2436520Z         >>> # get the necessary qconfig
2025-07-17T07:05:47.2436590Z         >>> config = PrepareCustomConfig()
2025-07-17T07:05:47.2436680Z         >>> skipped_module_names, skipped_module_classes = (
2025-07-17T07:05:47.2436780Z         ...     get_skipped_module_name_and_classes(config, False)
2025-07-17T07:05:47.2436820Z         ... )
2025-07-17T07:05:47.2436860Z     
2025-07-17T07:05:47.2436960Z         >>> # initialize our model and get GraphModule
2025-07-17T07:05:47.2437040Z         >>> model = SomeModel()
2025-07-17T07:05:47.2437190Z         >>> tracer = QuantizationTracer(skipped_module_names, skipped_module_classes)
2025-07-17T07:05:47.2437290Z         >>> graph_module = GraphModule(model, tracer.trace(model))
2025-07-17T07:05:47.2437330Z     
2025-07-17T07:05:47.2437430Z         >>> # get our set of detectors and ModelReport instance
2025-07-17T07:05:47.2437480Z         >>> detector_set = set(
2025-07-17T07:05:47.2437520Z         ...     [
2025-07-17T07:05:47.2437610Z         ...         DynamicStaticDetector(tolerance=0.5),
2025-07-17T07:05:47.2437720Z         ...         InputWeightEqualizationDetector(ratio_threshold=0.7),
2025-07-17T07:05:47.2437770Z         ...     ]
2025-07-17T07:05:47.2437810Z         ... )
2025-07-17T07:05:47.2437930Z         >>> tracer_reporter = ModelReport(graph_module, tracer_detector_set)
2025-07-17T07:05:47.2437970Z     
2025-07-17T07:05:47.2438070Z         >>> # now we insert the observers and calibrate the model
2025-07-17T07:05:47.2438220Z         >>> tracer_model_with_observers = tracer_reporter.prepare_detailed_calibration()
2025-07-17T07:05:47.2438300Z         >>> for i in range(num_callibration_batches):
2025-07-17T07:05:47.2438380Z         >>>     example_input = get_callibration_input()
2025-07-17T07:05:47.2438460Z         >>>     tracer_model_with_observers(example_input)
2025-07-17T07:05:47.2438500Z     
2025-07-17T07:05:47.2438660Z         >>> # finally we generate the reports and optionally remove the observers we inserted
2025-07-17T07:05:47.2438750Z         >>> reports = tracer_reporter.generate_model_report(
2025-07-17T07:05:47.2438820Z         ...     remove_inserted_observers=True
2025-07-17T07:05:47.2438860Z         ... )
2025-07-17T07:05:47.2438900Z     
2025-07-17T07:05:47.2439030Z         >>> # Optional: we can generate the qconfig mapping based on the suggestions
2025-07-17T07:05:47.2439130Z         >>> qconfigs = model_report.generate_qconfig_mapping()
2025-07-17T07:05:47.2439170Z     
2025-07-17T07:05:47.2439310Z         >>> # Optional: we can generate the equalization mapping based on the suggestions
2025-07-17T07:05:47.2439420Z         >>> qconfigs = model_report.generate_equalization_mapping()
2025-07-17T07:05:47.2439470Z     
2025-07-17T07:05:47.2439640Z         >>> # Optional: we get a ModelReportVisualizer instance to do any visualizations desired
2025-07-17T07:05:47.2439760Z         >>> model_report_visualizer = tracer_reporter.generate_visualizer()
2025-07-17T07:05:47.2439800Z     
2025-07-17T07:05:47.2439840Z     
2025-07-17T07:05:47.2439990Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2440030Z     
2025-07-17T07:05:47.2440080Z       warnings.warn(msg)
2025-07-17T07:05:47.2440120Z     
2025-07-17T07:05:47.2440220Z --- Parse Warning: 130 / 136 ---
2025-07-17T07:05:47.2441010Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BaseSparsifier.squash_mask in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py line=229.
2025-07-17T07:05:47.2441170Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2441310Z     Squashes the sparse masks into the appropriate tensors.
2025-07-17T07:05:47.2441350Z     
2025-07-17T07:05:47.2441480Z             If either the `params_to_keep` or `params_to_keep_per_layer` is set,
2025-07-17T07:05:47.2441590Z             the module will have a `sparse_params` dict attached to it.
2025-07-17T07:05:47.2441630Z     
2025-07-17T07:05:47.2441670Z             Args:
2025-07-17T07:05:47.2441790Z                 params_to_keep: List of keys to save in the module or a dict
2025-07-17T07:05:47.2441890Z                                 representing the modules and keys that will have
2025-07-17T07:05:47.2441980Z                                 sparsity parameters saved
2025-07-17T07:05:47.2442130Z                 params_to_keep_per_layer: Dict to specify the params that should be
2025-07-17T07:05:47.2442230Z                                 saved for specific layers. The keys in the dict
2025-07-17T07:05:47.2442320Z                                 should be the module fqn, while the values should
2025-07-17T07:05:47.2442420Z                                 be a list of strings with the names of the variables
2025-07-17T07:05:47.2442500Z                                 to save in the `sparse_params`
2025-07-17T07:05:47.2442540Z     
2025-07-17T07:05:47.2442590Z             Examples:
2025-07-17T07:05:47.2442670Z                 >>> # xdoctest: +SKIP("locals are undefined")
2025-07-17T07:05:47.2442740Z                 >>> # Don't save any sparse params
2025-07-17T07:05:47.2442800Z                 >>> sparsifier.squash_mask()
2025-07-17T07:05:47.2442890Z                 >>> hasattr(model.submodule1, "sparse_params")
2025-07-17T07:05:47.2442930Z                 False
2025-07-17T07:05:47.2442980Z     
2025-07-17T07:05:47.2443050Z                 >>> # Keep sparse params per layer
2025-07-17T07:05:47.2443110Z                 >>> sparsifier.squash_mask(
2025-07-17T07:05:47.2443180Z                 ...     params_to_keep_per_layer={
2025-07-17T07:05:47.2443260Z                 ...         "submodule1.linear1": ("foo", "bar"),
2025-07-17T07:05:47.2443340Z                 ...         "submodule2.linear42": ("baz",),
2025-07-17T07:05:47.2443390Z                 ...     }
2025-07-17T07:05:47.2443430Z                 ... )
2025-07-17T07:05:47.2443520Z                 >>> print(model.submodule1.linear1.sparse_params)
2025-07-17T07:05:47.2443580Z                 {'foo': 42, 'bar': 24}
2025-07-17T07:05:47.2443680Z                 >>> print(model.submodule2.linear42.sparse_params)
2025-07-17T07:05:47.2443730Z                 {'baz': 0.1}
2025-07-17T07:05:47.2443770Z     
2025-07-17T07:05:47.2443850Z                 >>> # Keep sparse params for all layers
2025-07-17T07:05:47.2443950Z                 >>> sparsifier.squash_mask(params_to_keep=("foo", "bar"))
2025-07-17T07:05:47.2444050Z                 >>> print(model.submodule1.linear1.sparse_params)
2025-07-17T07:05:47.2444100Z                 {'foo': 42, 'bar': 24}
2025-07-17T07:05:47.2444200Z                 >>> print(model.submodule2.linear42.sparse_params)
2025-07-17T07:05:47.2444250Z                 {'foo': 42, 'bar': 24}
2025-07-17T07:05:47.2444300Z     
2025-07-17T07:05:47.2444410Z                 >>> # Keep some sparse params for all layers, and specific ones for
2025-07-17T07:05:47.2444470Z                 >>> # some other layers
2025-07-17T07:05:47.2444530Z                 >>> sparsifier.squash_mask(
2025-07-17T07:05:47.2444610Z                 ...     params_to_keep=("foo", "bar"),
2025-07-17T07:05:47.2444720Z                 ...     params_to_keep_per_layer={"submodule2.linear42": ("baz",)},
2025-07-17T07:05:47.2444770Z                 ... )
2025-07-17T07:05:47.2444860Z                 >>> print(model.submodule1.linear1.sparse_params)
2025-07-17T07:05:47.2444940Z                 {'foo': 42, 'bar': 24}
2025-07-17T07:05:47.2445040Z                 >>> print(model.submodule2.linear42.sparse_params)
2025-07-17T07:05:47.2445110Z                 {'foo': 42, 'bar': 24, 'baz': 0.1}
2025-07-17T07:05:47.2445170Z             
2025-07-17T07:05:47.2445320Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2445360Z     
2025-07-17T07:05:47.2445410Z       warnings.warn(msg)
2025-07-17T07:05:47.2445460Z     
2025-07-17T07:05:47.2445560Z --- Parse Warning: 131 / 136 ---
2025-07-17T07:05:47.2446400Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ActivationSparsifier in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/pruning/_experimental/activation_sparsifier/activation_sparsifier.py line=16.
2025-07-17T07:05:47.2446590Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2446630Z     
2025-07-17T07:05:47.2446780Z     The Activation sparsifier class aims to sparsify/prune activations in a neural
2025-07-17T07:05:47.2446920Z     network. The idea is to attach the sparsifier to a layer (or layers) and it
2025-07-17T07:05:47.2447070Z     zeroes out the activations based on the mask_fn (or sparsification function)
2025-07-17T07:05:47.2447110Z     input by the user.
2025-07-17T07:05:47.2447250Z     The mask_fn is applied once all the inputs are aggregated and reduced i.e.
2025-07-17T07:05:47.2447340Z     mask = mask_fn(reduce_fn(aggregate_fn(activations)))
2025-07-17T07:05:47.2447380Z     
2025-07-17T07:05:47.2447450Z     Note::
2025-07-17T07:05:47.2447640Z         The sparsification mask is computed on the input **before it goes through the attached layer**.
2025-07-17T07:05:47.2447680Z     
2025-07-17T07:05:47.2447730Z     Args:
2025-07-17T07:05:47.2447780Z         model (nn.Module):
2025-07-17T07:05:47.2447920Z             The model whose layers will be sparsified. The layers that needs to be
2025-07-17T07:05:47.2448060Z             sparsified should be added separately using the register_layer() function
2025-07-17T07:05:47.2448130Z         aggregate_fn (Optional, Callable):
2025-07-17T07:05:47.2448290Z             default aggregate_fn that is used if not specified while registering the layer.
2025-07-17T07:05:47.2448390Z             specifies how inputs should be aggregated over time.
2025-07-17T07:05:47.2448560Z             The aggregate_fn should usually take 2 torch tensors and return the aggregated tensor.
2025-07-17T07:05:47.2448610Z             Example
2025-07-17T07:05:47.2448710Z                 def add_agg_fn(tensor1, tensor2):  return tensor1 + tensor2
2025-07-17T07:05:47.2448780Z                 reduce_fn (Optional, Callable):
2025-07-17T07:05:47.2448930Z                     default reduce_fn that is used if not specified while registering the layer.
2025-07-17T07:05:47.2449080Z                     reduce_fn will be called on the aggregated tensor i.e. the tensor obtained after
2025-07-17T07:05:47.2449150Z                     calling agg_fn() on all inputs.
2025-07-17T07:05:47.2449200Z                     Example
2025-07-17T07:05:47.2449330Z                 def mean_reduce_fn(agg_tensor):    return agg_tensor.mean(dim=0)
2025-07-17T07:05:47.2449390Z                 mask_fn (Optional, Callable):
2025-07-17T07:05:47.2449580Z                     default mask_fn that is used to create the sparsification mask using the tensor obtained after
2025-07-17T07:05:47.2449730Z                     calling the reduce_fn(). This is used by default if a custom one is passed in the
2025-07-17T07:05:47.2449780Z                     register_layer().
2025-07-17T07:05:47.2449990Z                     Note that the mask_fn() definition should contain the sparse arguments that is passed in sparse_config
2025-07-17T07:05:47.2450040Z                     arguments.
2025-07-17T07:05:47.2450100Z                 features (Optional, list):
2025-07-17T07:05:47.2450200Z                     default selected features to sparsify.
2025-07-17T07:05:47.2450370Z                     If this is non-empty, then the mask_fn will be applied for each feature of the input.
2025-07-17T07:05:47.2450440Z                     For example,
2025-07-17T07:05:47.2450600Z                 mask = [mask_fn(reduce_fn(aggregated_fn(input[feature])) for feature in features]
2025-07-17T07:05:47.2450660Z                 feature_dim (Optional, int):
2025-07-17T07:05:47.2450830Z                     default dimension of input features. Again, features along this dim will be chosen
2025-07-17T07:05:47.2450890Z                     for sparsification.
2025-07-17T07:05:47.2450940Z                 sparse_config (Dict):
2025-07-17T07:05:47.2451070Z                     Default configuration for the mask_fn. This config will be passed
2025-07-17T07:05:47.2451130Z                     with the mask_fn()
2025-07-17T07:05:47.2451190Z     
2025-07-17T07:05:47.2451260Z     Example:
2025-07-17T07:05:47.2451310Z         >>> # xdoctest: +SKIP
2025-07-17T07:05:47.2451370Z         >>> model = SomeModel()
2025-07-17T07:05:47.2451510Z         >>> act_sparsifier = ActivationSparsifier(...)  # init activation sparsifier
2025-07-17T07:05:47.2451570Z         >>> # Initialize aggregate_fn
2025-07-17T07:05:47.2451620Z         >>> def agg_fn(x, y):
2025-07-17T07:05:47.2451680Z         >>>     return x + y
2025-07-17T07:05:47.2451720Z         >>>
2025-07-17T07:05:47.2451770Z         >>> # Initialize reduce_fn
2025-07-17T07:05:47.2451820Z         >>> def reduce_fn(x):
2025-07-17T07:05:47.2451890Z         >>>     return torch.mean(x, dim=0)
2025-07-17T07:05:47.2451930Z         >>>
2025-07-17T07:05:47.2451990Z         >>> # Initialize mask_fn
2025-07-17T07:05:47.2452040Z         >>> def mask_fn(data):
2025-07-17T07:05:47.2452130Z         >>>     return torch.eye(data.shape).to(data.device)
2025-07-17T07:05:47.2452170Z         >>>
2025-07-17T07:05:47.2452210Z         >>>
2025-07-17T07:05:47.2452280Z         >>> act_sparsifier.register_layer(
2025-07-17T07:05:47.2452330Z         ...     model.some_layer,
2025-07-17T07:05:47.2452390Z         ...     aggregate_fn=agg_fn,
2025-07-17T07:05:47.2452440Z         ...     reduce_fn=reduce_fn,
2025-07-17T07:05:47.2452490Z         ...     mask_fn=mask_fn,
2025-07-17T07:05:47.2452530Z         ... )
2025-07-17T07:05:47.2452570Z         >>>
2025-07-17T07:05:47.2452630Z         >>> # start training process
2025-07-17T07:05:47.2452680Z         >>> for _ in [...]:
2025-07-17T07:05:47.2452730Z         >>> # epoch starts
2025-07-17T07:05:47.2456800Z         >>> # model.forward(), compute_loss() and model.backwards()
2025-07-17T07:05:47.2456870Z         >>> # epoch ends
2025-07-17T07:05:47.2456940Z         >>>     act_sparsifier.step()
2025-07-17T07:05:47.2457000Z         >>> # end training process
2025-07-17T07:05:47.2457050Z         >>> sparsifier.squash_mask()
2025-07-17T07:05:47.2457090Z     
2025-07-17T07:05:47.2457250Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2457290Z     
2025-07-17T07:05:47.2457350Z       warnings.warn(msg)
2025-07-17T07:05:47.2457390Z     
2025-07-17T07:05:47.2457540Z --- Parse Warning: 132 / 136 ---
2025-07-17T07:05:47.2458370Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BaseDataScheduler.get_schedule_param in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/ao/pruning/_experimental/data_scheduler/base_data_scheduler.py line=91.
2025-07-17T07:05:47.2458530Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2458570Z     
2025-07-17T07:05:47.2458700Z     Abstract method that needs to be implemented by the child class.
2025-07-17T07:05:47.2458860Z     The expected return type should is a dictionary of name to schedule_param value
2025-07-17T07:05:47.2459150Z     The returned values will be updated in sparsifier when the scheduler step() function
2025-07-17T07:05:47.2459200Z     is called.
2025-07-17T07:05:47.2459240Z     
2025-07-17T07:05:47.2459280Z     Example:
2025-07-17T07:05:47.2459340Z         >>> def get_schedule_param(self):
2025-07-17T07:05:47.2459420Z         ...     new_param = {}
2025-07-17T07:05:47.2459520Z         ...     for name in self.sparsifier.data_groups.keys():
2025-07-17T07:05:47.2459570Z         ...         new_param[name] = (
2025-07-17T07:05:47.2459700Z         ...             self.sparsifier.data_groups[name][self.schedule_param] * 0.5
2025-07-17T07:05:47.2459740Z         ...         )
2025-07-17T07:05:47.2459800Z         ...     return new_param
2025-07-17T07:05:47.2459840Z     
2025-07-17T07:05:47.2460040Z     When the step() function is called, the value in self.sparsifier.data_groups[name][self.schedule_param]
2025-07-17T07:05:47.2460090Z     would be halved
2025-07-17T07:05:47.2460130Z     
2025-07-17T07:05:47.2460300Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2460360Z     
2025-07-17T07:05:47.2460420Z       warnings.warn(msg)
2025-07-17T07:05:47.2460450Z     
2025-07-17T07:05:47.2460560Z --- Parse Warning: 133 / 136 ---
2025-07-17T07:05:47.2461260Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RelaxedBernoulli in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/relaxed_bernoulli.py line=120.
2025-07-17T07:05:47.2461420Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2461460Z     
2025-07-17T07:05:47.2461570Z     Creates a RelaxedBernoulli distribution, parametrized by
2025-07-17T07:05:47.2461680Z     :attr:`temperature`, and either :attr:`probs` or :attr:`logits`
2025-07-17T07:05:47.2461820Z     (but not both). This is a relaxed version of the `Bernoulli` distribution,
2025-07-17T07:05:47.2461930Z     so the values are in (0, 1), and has reparametrizable samples.
2025-07-17T07:05:47.2461970Z     
2025-07-17T07:05:47.2462020Z     Example::
2025-07-17T07:05:47.2462060Z     
2025-07-17T07:05:47.2462150Z         >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-07-17T07:05:47.2462230Z         >>> m = RelaxedBernoulli(torch.tensor([2.2]),
2025-07-17T07:05:47.2462310Z         ...                      torch.tensor([0.1, 0.2, 0.3, 0.99]))
2025-07-17T07:05:47.2462350Z         >>> m.sample()
2025-07-17T07:05:47.2462420Z         tensor([ 0.2951,  0.3442,  0.8918,  0.9021])
2025-07-17T07:05:47.2462460Z     
2025-07-17T07:05:47.2462510Z     Args:
2025-07-17T07:05:47.2462590Z         temperature (Tensor): relaxation temperature
2025-07-17T07:05:47.2462700Z         probs (Number, Tensor): the probability of sampling `1`
2025-07-17T07:05:47.2462790Z         logits (Number, Tensor): the log-odds of sampling `1`
2025-07-17T07:05:47.2462830Z     
2025-07-17T07:05:47.2462990Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2463030Z     
2025-07-17T07:05:47.2463080Z       warnings.warn(msg)
2025-07-17T07:05:47.2463120Z     
2025-07-17T07:05:47.2463220Z --- Parse Warning: 134 / 136 ---
2025-07-17T07:05:47.2463950Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RelaxedOneHotCategorical in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/relaxed_categorical.py line=109.
2025-07-17T07:05:47.2464110Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2464150Z     
2025-07-17T07:05:47.2464290Z     Creates a RelaxedOneHotCategorical distribution parametrized by
2025-07-17T07:05:47.2464400Z     :attr:`temperature`, and either :attr:`probs` or :attr:`logits`.
2025-07-17T07:05:47.2464570Z     This is a relaxed version of the :class:`OneHotCategorical` distribution, so
2025-07-17T07:05:47.2464670Z     its samples are on simplex, and are reparametrizable.
2025-07-17T07:05:47.2464720Z     
2025-07-17T07:05:47.2464760Z     Example::
2025-07-17T07:05:47.2464840Z     
2025-07-17T07:05:47.2464920Z         >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-07-17T07:05:47.2465020Z         >>> m = RelaxedOneHotCategorical(torch.tensor([2.2]),
2025-07-17T07:05:47.2465100Z         ...                              torch.tensor([0.1, 0.2, 0.3, 0.4]))
2025-07-17T07:05:47.2465140Z         >>> m.sample()
2025-07-17T07:05:47.2465210Z         tensor([ 0.1294,  0.2324,  0.3859,  0.2523])
2025-07-17T07:05:47.2465250Z     
2025-07-17T07:05:47.2465300Z     Args:
2025-07-17T07:05:47.2465380Z         temperature (Tensor): relaxation temperature
2025-07-17T07:05:47.2465450Z         probs (Tensor): event probabilities
2025-07-17T07:05:47.2465580Z         logits (Tensor): unnormalized log probability for each event
2025-07-17T07:05:47.2465640Z     
2025-07-17T07:05:47.2465790Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2465830Z     
2025-07-17T07:05:47.2465880Z       warnings.warn(msg)
2025-07-17T07:05:47.2465920Z     
2025-07-17T07:05:47.2466020Z --- Parse Warning: 135 / 136 ---
2025-07-17T07:05:47.2466780Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LowRankMultivariateNormal in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/lowrank_multivariate_normal.py line=56.
2025-07-17T07:05:47.2466940Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2466980Z     
2025-07-17T07:05:47.2467170Z     Creates a multivariate normal distribution with covariance matrix having a low-rank form
2025-07-17T07:05:47.2467280Z     parameterized by :attr:`cov_factor` and :attr:`cov_diag`::
2025-07-17T07:05:47.2467320Z     
2025-07-17T07:05:47.2467430Z         covariance_matrix = cov_factor @ cov_factor.T + cov_diag
2025-07-17T07:05:47.2467480Z     
2025-07-17T07:05:47.2467520Z     Example:
2025-07-17T07:05:47.2467610Z         >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK)
2025-07-17T07:05:47.2467690Z         >>> # xdoctest: +IGNORE_WANT("non-deterministic")
2025-07-17T07:05:47.2467760Z         >>> m = LowRankMultivariateNormal(
2025-07-17T07:05:47.2467880Z         ...     torch.zeros(2), torch.tensor([[1.0], [0.0]]), torch.ones(2)
2025-07-17T07:05:47.2467920Z         ... )
2025-07-17T07:05:47.2468100Z         >>> m.sample()  # normally distributed with mean=`[0,0]`, cov_factor=`[[1],[0]]`, cov_diag=`[1,1]`
2025-07-17T07:05:47.2468160Z         tensor([-0.2102, -0.5429])
2025-07-17T07:05:47.2468200Z     
2025-07-17T07:05:47.2468240Z     Args:
2025-07-17T07:05:47.2468390Z         loc (Tensor): mean of the distribution with shape `batch_shape + event_shape`
2025-07-17T07:05:47.2468540Z         cov_factor (Tensor): factor part of low-rank form of covariance matrix with shape
2025-07-17T07:05:47.2468610Z             `batch_shape + event_shape + (rank,)`
2025-07-17T07:05:47.2468760Z         cov_diag (Tensor): diagonal part of low-rank form of covariance matrix with shape
2025-07-17T07:05:47.2468830Z             `batch_shape + event_shape`
2025-07-17T07:05:47.2468860Z     
2025-07-17T07:05:47.2468910Z     Note:
2025-07-17T07:05:47.2469060Z         The computation for determinant and inverse of covariance matrix is avoided when
2025-07-17T07:05:47.2469210Z         `cov_factor.shape[1] << cov_factor.shape[0]` thanks to `Woodbury matrix identity
2025-07-17T07:05:47.2469360Z         <https://en.wikipedia.org/wiki/Woodbury_matrix_identity>`_ and
2025-07-17T07:05:47.2469540Z         `matrix determinant lemma <https://en.wikipedia.org/wiki/Matrix_determinant_lemma>`_.
2025-07-17T07:05:47.2469690Z         Thanks to these formulas, we just need to compute the determinant and inverse of
2025-07-17T07:05:47.2469790Z         the small size "capacitance" matrix::
2025-07-17T07:05:47.2469830Z     
2025-07-17T07:05:47.2469950Z             capacitance = I + cov_factor.T @ inv(cov_diag) @ cov_factor
2025-07-17T07:05:47.2469990Z     
2025-07-17T07:05:47.2470160Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2470210Z     
2025-07-17T07:05:47.2470260Z       warnings.warn(msg)
2025-07-17T07:05:47.2470300Z     
2025-07-17T07:05:47.2470390Z --- Parse Warning: 136 / 136 ---
2025-07-17T07:05:47.2471110Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MixtureSameFamily in modpath=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/distributions/mixture_same_family.py line=15.
2025-07-17T07:05:47.2471290Z     Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines')
2025-07-17T07:05:47.2471360Z     
2025-07-17T07:05:47.2471500Z     The `MixtureSameFamily` distribution implements a (batch of) mixture
2025-07-17T07:05:47.2471640Z     distribution where all component are from different parameterizations of
2025-07-17T07:05:47.2471770Z     the same distribution type. It is parameterized by a `Categorical`
2025-07-17T07:05:47.2471890Z     "selecting distribution" (over `k` component) and a component
2025-07-17T07:05:47.2472010Z     distribution, i.e., a `Distribution` with a rightmost batch shape
2025-07-17T07:05:47.2472110Z     (equal to `[k]`) which indexes each (batch of) component.
2025-07-17T07:05:47.2472150Z     
2025-07-17T07:05:47.2472200Z     Examples::
2025-07-17T07:05:47.2472240Z     
2025-07-17T07:05:47.2472300Z         >>> # xdoctest: +SKIP("undefined vars")
2025-07-17T07:05:47.2472430Z         >>> # Construct Gaussian Mixture Model in 1D consisting of 5 equally
2025-07-17T07:05:47.2472490Z         >>> # weighted normal distributions
2025-07-17T07:05:47.2472560Z         >>> mix = D.Categorical(torch.ones(5,))
2025-07-17T07:05:47.2472650Z         >>> comp = D.Normal(torch.randn(5,), torch.rand(5,))
2025-07-17T07:05:47.2472720Z         >>> gmm = MixtureSameFamily(mix, comp)
2025-07-17T07:05:47.2472760Z     
2025-07-17T07:05:47.2472880Z         >>> # Construct Gaussian Mixture Model in 2D consisting of 5 equally
2025-07-17T07:05:47.2472960Z         >>> # weighted bivariate normal distributions
2025-07-17T07:05:47.2473030Z         >>> mix = D.Categorical(torch.ones(5,))
2025-07-17T07:05:47.2473100Z         >>> comp = D.Independent(D.Normal(
2025-07-17T07:05:47.2473170Z         ...          torch.randn(5,2), torch.rand(5,2)), 1)
2025-07-17T07:05:47.2473240Z         >>> gmm = MixtureSameFamily(mix, comp)
2025-07-17T07:05:47.2473280Z     
2025-07-17T07:05:47.2473390Z         >>> # Construct a batch of 3 Gaussian Mixture Models in 2D each
2025-07-17T07:05:47.2473510Z         >>> # consisting of 5 random weighted bivariate normal distributions
2025-07-17T07:05:47.2473590Z         >>> mix = D.Categorical(torch.rand(3,5))
2025-07-17T07:05:47.2473650Z         >>> comp = D.Independent(D.Normal(
2025-07-17T07:05:47.2473730Z         ...         torch.randn(3,5,2), torch.rand(3,5,2)), 1)
2025-07-17T07:05:47.2473800Z         >>> gmm = MixtureSameFamily(mix, comp)
2025-07-17T07:05:47.2473850Z     
2025-07-17T07:05:47.2473890Z     Args:
2025-07-17T07:05:47.2474010Z         mixture_distribution: `torch.distributions.Categorical`-like
2025-07-17T07:05:47.2474130Z             instance. Manages the probability of selecting component.
2025-07-17T07:05:47.2474230Z             The number of categories must match the rightmost batch
2025-07-17T07:05:47.2474340Z             dimension of the `component_distribution`. Must have either
2025-07-17T07:05:47.2474430Z             scalar `batch_shape` or `batch_shape` matching
2025-07-17T07:05:47.2474510Z             `component_distribution.batch_shape[:-1]`
2025-07-17T07:05:47.2474640Z         component_distribution: `torch.distributions.Distribution`-like
2025-07-17T07:05:47.2474770Z             instance. Right-most batch dimension indexes component.
2025-07-17T07:05:47.2474810Z     
2025-07-17T07:05:47.2474960Z     Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0))
2025-07-17T07:05:47.2475020Z     
2025-07-17T07:05:47.2475080Z       warnings.warn(msg)
2025-07-17T07:05:47.2475120Z     
2025-07-17T07:05:47.2475200Z 
2025-07-17T07:05:47.2475290Z === Found 9 run-time warnings ===
2025-07-17T07:05:47.2475390Z --- Runtime Warning: 1 / 9 ---
2025-07-17T07:05:47.2475560Z example = <DocTest(torch.library Library._impl_with_aoti_compile:0 ln 246) at 0x12ddcda90>
2025-07-17T07:05:47.2476000Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/library.py:281: UserWarning: Warning only once for all operators,  other operators may also be overridden.
2025-07-17T07:05:47.2476200Z       Overriding a previously registered kernel for the same operator and the same dispatch key
2025-07-17T07:05:47.2476350Z       operator: aten::div.Tensor(Tensor self, Tensor other) -> Tensor
2025-07-17T07:05:47.2476570Z         registered at /Users/ec2-user/runner/_work/pytorch/pytorch/build/aten/src/ATen/RegisterSchema.cpp:6
2025-07-17T07:05:47.2476620Z       dispatch key: CPU
2025-07-17T07:05:47.2476910Z       previous kernel: registered at /Users/ec2-user/runner/_work/pytorch/pytorch/aten/src/ATen/LegacyBatchingRegistrations.cpp:1079
2025-07-17T07:05:47.2477270Z            new kernel: registered at /dev/null:811 (Triggered internally at /Users/ec2-user/runner/_work/pytorch/pytorch/aten/src/ATen/core/dispatch/OperatorEntry.cpp:225.)
2025-07-17T07:05:47.2477360Z       impl_fn(self.ns, name.split("::")[-1], dispatch_key)
2025-07-17T07:05:47.2477410Z     
2025-07-17T07:05:47.2477500Z --- Runtime Warning: 2 / 9 ---
2025-07-17T07:05:47.2477660Z example = <DocTest(torch._tensor Tensor.refine_names:0 ln 1333) at 0x12ddd8dd0>
2025-07-17T07:05:47.2478530Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/_tensor.py:1351: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /Users/ec2-user/runner/_work/pytorch/pytorch/c10/core/TensorImpl.h:1978.)
2025-07-17T07:05:47.2478600Z       return super().refine_names(names)
2025-07-17T07:05:47.2478640Z     
2025-07-17T07:05:47.2478730Z --- Runtime Warning: 3 / 9 ---
2025-07-17T07:05:47.2478880Z example = <DocTest(torch.sparse as_sparse_gradcheck:0 ln 561) at 0x12df2b560>
2025-07-17T07:05:47.2479900Z     <doctest:/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/sparse/__init__.py::as_sparse_gradcheck:0>:1: UserWarning: Sparse CSR tensor support is in beta state. If you miss a functionality in the sparse tensor support, please submit a feature request to https://github.com/pytorch/pytorch/issues. (Triggered internally at /Users/ec2-user/runner/_work/pytorch/pytorch/aten/src/ATen/SparseCsrTensorImpl.cpp:55.)
2025-07-17T07:05:47.2479940Z     
2025-07-17T07:05:47.2480040Z --- Runtime Warning: 4 / 9 ---
2025-07-17T07:05:47.2480170Z example = <DocTest(torch.nested as_nested_tensor:0 ln 61) at 0x12df2b9b0>
2025-07-17T07:05:47.2481320Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nested/__init__.py:117: UserWarning: The PyTorch API of nested tensors is in prototype stage and will change in the near future. We recommend specifying layout=torch.jagged when constructing a nested tensor, as this layout receives active development, has better operator coverage, and works with torch.compile. (Triggered internally at /Users/ec2-user/runner/_work/pytorch/pytorch/aten/src/ATen/NestedTensorImpl.cpp:182.)
2025-07-17T07:05:47.2481500Z       return torch._nested_tensor_from_tensor_list(ts, dtype, None, device, None)
2025-07-17T07:05:47.2481540Z     
2025-07-17T07:05:47.2481690Z --- Runtime Warning: 5 / 9 ---
2025-07-17T07:05:47.2481870Z example = <DocTest(torch._functorch.eager_transforms linearize:0 ln 1704) at 0x12df2b950>
2025-07-17T07:05:47.2482860Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/fx/experimental/const_fold.py:271: UserWarning: Attempted to insert a get_attr Node with no underlying reference in the owning GraphModule! Call GraphModule.add_submodule to add the necessary submodule, GraphModule.add_parameter to add the necessary Parameter, or nn.Module.register_buffer to add the necessary buffer
2025-07-17T07:05:47.2482990Z       new_node = root_const_gm.graph.get_attr(in_node.target)
2025-07-17T07:05:47.2483030Z     
2025-07-17T07:05:47.2483150Z --- Runtime Warning: 6 / 9 ---
2025-07-17T07:05:47.2483310Z example = <DocTest(torch.nn.utils.weight_norm weight_norm:0 ln 134) at 0x12df85eb0>
2025-07-17T07:05:47.2483900Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/weight_norm.py:144: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`.
2025-07-17T07:05:47.2483990Z       WeightNorm.apply(module, name, dim)
2025-07-17T07:05:47.2484030Z     
2025-07-17T07:05:47.2484120Z --- Runtime Warning: 7 / 9 ---
2025-07-17T07:05:47.2484300Z example = <DocTest(torch.nn.utils.weight_norm remove_weight_norm:0 ln 156) at 0x12df85460>
2025-07-17T07:05:47.2484840Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/utils/weight_norm.py:144: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`.
2025-07-17T07:05:47.2484910Z       WeightNorm.apply(module, name, dim)
2025-07-17T07:05:47.2484950Z     
2025-07-17T07:05:47.2485040Z --- Runtime Warning: 8 / 9 ---
2025-07-17T07:05:47.2485210Z example = <DocTest(torch.nn.modules.transformer Transformer:0 ln 90) at 0x12df6d370>
2025-07-17T07:05:47.2485900Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py:392: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.self_attn.batch_first was not True(use batch_first for better inference performance)
2025-07-17T07:05:47.2485950Z       warnings.warn(
2025-07-17T07:05:47.2485990Z     
2025-07-17T07:05:47.2486080Z --- Runtime Warning: 9 / 9 ---
2025-07-17T07:05:47.2486280Z example = <DocTest(torch.nn.modules.transformer TransformerEncoder:0 ln 336) at 0x12df6c8c0>
2025-07-17T07:05:47.2486950Z     /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/nn/modules/transformer.py:392: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.self_attn.batch_first was not True(use batch_first for better inference performance)
2025-07-17T07:05:47.2487010Z       warnings.warn(
2025-07-17T07:05:47.2487050Z     
2025-07-17T07:05:47.2487220Z === 342 passed, 377 skipped, 145 warnings in 9.29 seconds ===
2025-07-17T07:05:48.5353580Z running install
2025-07-17T07:05:48.5354500Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/setuptools/_distutils/cmd.py:66: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-07-17T07:05:48.5355070Z !!
2025-07-17T07:05:48.5355140Z 
2025-07-17T07:05:48.5355230Z         ********************************************************************************
2025-07-17T07:05:48.5355480Z         Please avoid running ``setup.py`` directly.
2025-07-17T07:05:48.5355730Z         Instead, use pypa/build, pypa/installer or other
2025-07-17T07:05:48.5355960Z         standards-based tools.
2025-07-17T07:05:48.5356080Z 
2025-07-17T07:05:48.5356270Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-07-17T07:05:48.5356800Z         ********************************************************************************
2025-07-17T07:05:48.5356960Z 
2025-07-17T07:05:48.5357000Z !!
2025-07-17T07:05:48.5357130Z   self.initialize_options()
2025-07-17T07:05:48.5420980Z running build
2025-07-17T07:05:48.5421160Z running build_py
2025-07-17T07:05:48.5458430Z creating build
2025-07-17T07:05:48.5459940Z creating build/lib.macosx-14.0-arm64-cpython-312
2025-07-17T07:05:48.5460610Z creating build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension
2025-07-17T07:05:48.5461380Z copying torch_test_cpp_extension/__init__.py -> build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension
2025-07-17T07:05:48.5471210Z running build_ext
2025-07-17T07:05:48.5479300Z building 'torch_test_cpp_extension.cpp' extension
2025-07-17T07:05:48.5479630Z creating build/temp.macosx-14.0-arm64-cpython-312
2025-07-17T07:05:48.5482970Z clang -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c extension.cpp -o build/temp.macosx-14.0-arm64-cpython-312/extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=cpp -std=c++17
2025-07-17T07:05:55.2226100Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk build/temp.macosx-14.0-arm64-cpython-312/extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/cpp.cpython-312-darwin.so
2025-07-17T07:05:55.2662340Z building 'torch_test_cpp_extension.maia' extension
2025-07-17T07:05:55.2665850Z clang -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c maia_extension.cpp -o build/temp.macosx-14.0-arm64-cpython-312/maia_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=maia -std=c++17
2025-07-17T07:06:01.7627730Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk build/temp.macosx-14.0-arm64-cpython-312/maia_extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/maia.cpython-312-darwin.so
2025-07-17T07:06:01.8063800Z building 'torch_test_cpp_extension.rng' extension
2025-07-17T07:06:01.8067120Z clang -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c rng_extension.cpp -o build/temp.macosx-14.0-arm64-cpython-312/rng_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=rng -std=c++17
2025-07-17T07:06:08.9302080Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk build/temp.macosx-14.0-arm64-cpython-312/rng_extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/rng.cpython-312-darwin.so
2025-07-17T07:06:08.9741450Z building 'torch_test_cpp_extension.mps' extension
2025-07-17T07:06:08.9745000Z clang -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c mps_extension.mm -o build/temp.macosx-14.0-arm64-cpython-312/mps_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=mps -std=c++17
2025-07-17T07:06:12.6436880Z In file included from mps_extension.mm:2:
2025-07-17T07:06:12.6437460Z In file included from /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/ATen/native/mps/OperationUtils.h:10:
2025-07-17T07:06:12.6438500Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/ATen/mps/MPSStream.h:120:3: warning: 'MPSGraphCompilationDescriptor' is only available on macOS 12.0 or newer [-Wunguarded-availability-new]
2025-07-17T07:06:12.6439320Z   MPSGraphCompilationDescriptor* _compilationDescriptor = nil;
2025-07-17T07:06:12.6439570Z   ^
2025-07-17T07:06:12.6440360Z /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk/System/Library/Frameworks/MetalPerformanceShadersGraph.framework/Headers/MPSGraph.h:94:12: note: 'MPSGraphCompilationDescriptor' has been marked as being introduced in macOS 12.0 here, but the deployment target is macOS 11.1.0
2025-07-17T07:06:12.6441300Z @interface MPSGraphCompilationDescriptor : MPSGraphObject <NSCopying>
2025-07-17T07:06:12.6441570Z            ^
2025-07-17T07:06:12.6442150Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/ATen/mps/MPSStream.h:54:17: note: annotate 'MPSStream' with an availability attribute to silence this warning
2025-07-17T07:06:12.6442750Z class TORCH_API MPSStream {
2025-07-17T07:06:12.6442900Z                 ^
2025-07-17T07:06:12.6443050Z       API_AVAILABLE(macos(12.0))
2025-07-17T07:06:15.4332920Z 1 warning generated.
2025-07-17T07:06:15.4443920Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk build/temp.macosx-14.0-arm64-cpython-312/mps_extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/mps.cpython-312-darwin.so
2025-07-17T07:06:15.4870910Z running install_lib
2025-07-17T07:06:15.4908390Z creating install
2025-07-17T07:06:15.4908910Z creating install/Users
2025-07-17T07:06:15.4909440Z creating install/Users/ec2-user
2025-07-17T07:06:15.4909990Z creating install/Users/ec2-user/runner
2025-07-17T07:06:15.4910510Z creating install/Users/ec2-user/runner/_work
2025-07-17T07:06:15.4911030Z creating install/Users/ec2-user/runner/_work/_temp
2025-07-17T07:06:15.4911790Z creating install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:06:15.4912220Z creating install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib
2025-07-17T07:06:15.4912810Z creating install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12
2025-07-17T07:06:15.4913280Z creating install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages
2025-07-17T07:06:15.4914350Z creating install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:06:15.4915250Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/cpp.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:06:15.4919080Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/mps.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:06:15.4921170Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/__init__.py -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:06:15.4922810Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/rng.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:06:15.4925950Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/maia.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:06:15.4938670Z byte-compiling ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension/__init__.py to __init__.cpython-312.pyc
2025-07-17T07:06:15.4941460Z running install_egg_info
2025-07-17T07:06:15.5016040Z running egg_info
2025-07-17T07:06:15.5016360Z creating torch_test_cpp_extension.egg-info
2025-07-17T07:06:15.5043750Z writing torch_test_cpp_extension.egg-info/PKG-INFO
2025-07-17T07:06:15.5047430Z writing dependency_links to torch_test_cpp_extension.egg-info/dependency_links.txt
2025-07-17T07:06:15.5048540Z writing entry points to torch_test_cpp_extension.egg-info/entry_points.txt
2025-07-17T07:06:15.5049970Z writing top-level names to torch_test_cpp_extension.egg-info/top_level.txt
2025-07-17T07:06:15.5050940Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-07-17T07:06:15.5081300Z reading manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-07-17T07:06:15.5084460Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-07-17T07:06:15.5085350Z Copying torch_test_cpp_extension.egg-info to ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension-0.0.0-py3.12.egg-info
2025-07-17T07:06:15.5094410Z running install_scripts
2025-07-17T07:06:17.2008560Z 
2025-07-17T07:06:17.2008860Z Running tests...
2025-07-17T07:06:17.2009130Z ----------------------------------------------------------------------
2025-07-17T07:06:17.2955150Z .
2025-07-17T07:06:17.2955390Z ----------------------------------------------------------------------
2025-07-17T07:06:17.2955930Z Ran 1 test in 0.095s
2025-07-17T07:06:17.2956060Z 
2025-07-17T07:06:17.2956100Z OK
2025-07-17T07:06:17.2956170Z 
2025-07-17T07:06:17.2956230Z Generating XML reports...
2025-07-17T07:06:17.6264370Z Running test_autoload_enable 1/1 ... [2025-07-17 07:06:17.626310]
2025-07-17T07:06:19.0177150Z running install
2025-07-17T07:06:19.0178630Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/setuptools/_distutils/cmd.py:66: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-07-17T07:06:19.0179210Z !!
2025-07-17T07:06:19.0179280Z 
2025-07-17T07:06:19.0179610Z         ********************************************************************************
2025-07-17T07:06:19.0179860Z         Please avoid running ``setup.py`` directly.
2025-07-17T07:06:19.0180210Z         Instead, use pypa/build, pypa/installer or other
2025-07-17T07:06:19.0180440Z         standards-based tools.
2025-07-17T07:06:19.0180560Z 
2025-07-17T07:06:19.0180760Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-07-17T07:06:19.0181100Z         ********************************************************************************
2025-07-17T07:06:19.0181250Z 
2025-07-17T07:06:19.0181300Z !!
2025-07-17T07:06:19.0181420Z   self.initialize_options()
2025-07-17T07:06:19.0253610Z running build
2025-07-17T07:06:19.0253980Z running build_py
2025-07-17T07:06:19.0279840Z creating build
2025-07-17T07:06:19.0280400Z creating build/lib.macosx-14.0-arm64-cpython-312
2025-07-17T07:06:19.0281260Z creating build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension
2025-07-17T07:06:19.0281920Z copying torch_test_cpp_extension/__init__.py -> build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension
2025-07-17T07:06:19.0285460Z running build_ext
2025-07-17T07:06:19.0293660Z building 'torch_test_cpp_extension.cpp' extension
2025-07-17T07:06:19.0294000Z creating build/temp.macosx-14.0-arm64-cpython-312
2025-07-17T07:06:19.0297320Z clang -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c extension.cpp -o build/temp.macosx-14.0-arm64-cpython-312/extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=cpp -std=c++17
2025-07-17T07:06:25.6965210Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk build/temp.macosx-14.0-arm64-cpython-312/extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/cpp.cpython-312-darwin.so
2025-07-17T07:06:25.7395820Z building 'torch_test_cpp_extension.maia' extension
2025-07-17T07:06:25.7399170Z clang -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c maia_extension.cpp -o build/temp.macosx-14.0-arm64-cpython-312/maia_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=maia -std=c++17
2025-07-17T07:06:32.2439110Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk build/temp.macosx-14.0-arm64-cpython-312/maia_extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/maia.cpython-312-darwin.so
2025-07-17T07:06:32.2876050Z building 'torch_test_cpp_extension.rng' extension
2025-07-17T07:06:32.2879090Z clang -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c rng_extension.cpp -o build/temp.macosx-14.0-arm64-cpython-312/rng_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=rng -std=c++17
2025-07-17T07:06:39.4203290Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk build/temp.macosx-14.0-arm64-cpython-312/rng_extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/rng.cpython-312-darwin.so
2025-07-17T07:06:39.4636650Z building 'torch_test_cpp_extension.mps' extension
2025-07-17T07:06:39.4639730Z clang -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c mps_extension.mm -o build/temp.macosx-14.0-arm64-cpython-312/mps_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=mps -std=c++17
2025-07-17T07:06:43.1257850Z In file included from mps_extension.mm:2:
2025-07-17T07:06:43.1258420Z In file included from /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/ATen/native/mps/OperationUtils.h:10:
2025-07-17T07:06:43.1259450Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/ATen/mps/MPSStream.h:120:3: warning: 'MPSGraphCompilationDescriptor' is only available on macOS 12.0 or newer [-Wunguarded-availability-new]
2025-07-17T07:06:43.1260270Z   MPSGraphCompilationDescriptor* _compilationDescriptor = nil;
2025-07-17T07:06:43.1260520Z   ^
2025-07-17T07:06:43.1261330Z /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk/System/Library/Frameworks/MetalPerformanceShadersGraph.framework/Headers/MPSGraph.h:94:12: note: 'MPSGraphCompilationDescriptor' has been marked as being introduced in macOS 12.0 here, but the deployment target is macOS 11.1.0
2025-07-17T07:06:43.1262280Z @interface MPSGraphCompilationDescriptor : MPSGraphObject <NSCopying>
2025-07-17T07:06:43.1262550Z            ^
2025-07-17T07:06:43.1263120Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/ATen/mps/MPSStream.h:54:17: note: annotate 'MPSStream' with an availability attribute to silence this warning
2025-07-17T07:06:43.1263710Z class TORCH_API MPSStream {
2025-07-17T07:06:43.1263860Z                 ^
2025-07-17T07:06:43.1264010Z       API_AVAILABLE(macos(12.0))
2025-07-17T07:06:45.9173990Z 1 warning generated.
2025-07-17T07:06:45.9285840Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk build/temp.macosx-14.0-arm64-cpython-312/mps_extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/mps.cpython-312-darwin.so
2025-07-17T07:06:45.9717420Z running install_lib
2025-07-17T07:06:45.9756800Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/cpp.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:06:45.9761360Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/mps.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:06:45.9764820Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/rng.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:06:45.9768390Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/maia.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:06:45.9774310Z running install_egg_info
2025-07-17T07:06:45.9848620Z running egg_info
2025-07-17T07:06:45.9875120Z writing torch_test_cpp_extension.egg-info/PKG-INFO
2025-07-17T07:06:45.9879470Z writing dependency_links to torch_test_cpp_extension.egg-info/dependency_links.txt
2025-07-17T07:06:45.9880610Z writing entry points to torch_test_cpp_extension.egg-info/entry_points.txt
2025-07-17T07:06:45.9882230Z writing top-level names to torch_test_cpp_extension.egg-info/top_level.txt
2025-07-17T07:06:45.9912600Z reading manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-07-17T07:06:45.9916250Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-07-17T07:06:45.9917170Z removing './install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension-0.0.0-py3.12.egg-info' (and everything under it)
2025-07-17T07:06:45.9921450Z Copying torch_test_cpp_extension.egg-info to ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension-0.0.0-py3.12.egg-info
2025-07-17T07:06:45.9930120Z running install_scripts
2025-07-17T07:06:47.6834800Z 
2025-07-17T07:06:47.6835070Z Running tests...
2025-07-17T07:06:47.6835320Z ----------------------------------------------------------------------
2025-07-17T07:06:47.7764380Z .
2025-07-17T07:06:47.7764580Z ----------------------------------------------------------------------
2025-07-17T07:06:47.7764970Z Ran 1 test in 0.093s
2025-07-17T07:06:47.7765190Z 
2025-07-17T07:06:47.7765250Z OK
2025-07-17T07:06:47.7765330Z 
2025-07-17T07:06:47.7765390Z Generating XML reports...
2025-07-17T07:06:48.1029170Z Running test_cpp_extensions_aot_ninja 1/1 ... [2025-07-17 07:06:48.102777]
2025-07-17T07:06:49.5421710Z running install
2025-07-17T07:06:49.5422820Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/setuptools/_distutils/cmd.py:66: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-07-17T07:06:49.5423380Z !!
2025-07-17T07:06:49.5423450Z 
2025-07-17T07:06:49.5423540Z         ********************************************************************************
2025-07-17T07:06:49.5423780Z         Please avoid running ``setup.py`` directly.
2025-07-17T07:06:49.5424040Z         Instead, use pypa/build, pypa/installer or other
2025-07-17T07:06:49.5424260Z         standards-based tools.
2025-07-17T07:06:49.5424370Z 
2025-07-17T07:06:49.5424560Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-07-17T07:06:49.5424890Z         ********************************************************************************
2025-07-17T07:06:49.5425030Z 
2025-07-17T07:06:49.5425080Z !!
2025-07-17T07:06:49.5425190Z   self.initialize_options()
2025-07-17T07:06:49.5489310Z running build
2025-07-17T07:06:49.5489840Z running build_py
2025-07-17T07:06:49.5519720Z creating build
2025-07-17T07:06:49.5520300Z creating build/lib.macosx-14.0-arm64-cpython-312
2025-07-17T07:06:49.5520970Z creating build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension
2025-07-17T07:06:49.5521740Z copying torch_test_cpp_extension/__init__.py -> build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension
2025-07-17T07:06:49.5525390Z running build_ext
2025-07-17T07:06:49.5842920Z building 'torch_test_cpp_extension.cpp' extension
2025-07-17T07:06:49.5843450Z creating /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/build/temp.macosx-14.0-arm64-cpython-312
2025-07-17T07:06:56.3200070Z [1/1] clang++ -MMD -MF /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/build/temp.macosx-14.0-arm64-cpython-312/extension.o.d -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -I/Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/self_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c -c /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/extension.cpp -o /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/build/temp.macosx-14.0-arm64-cpython-312/extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_clang"' '-DPYBIND11_STDLIB="_libcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1002"' -DTORCH_EXTENSION_NAME=cpp -std=c++17
2025-07-17T07:06:56.3315540Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/build/temp.macosx-14.0-arm64-cpython-312/extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/cpp.cpython-312-darwin.so
2025-07-17T07:06:56.3755160Z building 'torch_test_cpp_extension.maia' extension
2025-07-17T07:07:02.9430150Z [1/1] clang++ -MMD -MF /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/build/temp.macosx-14.0-arm64-cpython-312/maia_extension.o.d -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -I/Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/self_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c -c /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/maia_extension.cpp -o /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/build/temp.macosx-14.0-arm64-cpython-312/maia_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_clang"' '-DPYBIND11_STDLIB="_libcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1002"' -DTORCH_EXTENSION_NAME=maia -std=c++17
2025-07-17T07:07:02.9470260Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/build/temp.macosx-14.0-arm64-cpython-312/maia_extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/maia.cpython-312-darwin.so
2025-07-17T07:07:02.9908060Z building 'torch_test_cpp_extension.rng' extension
2025-07-17T07:07:10.1935770Z [1/1] clang++ -MMD -MF /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/build/temp.macosx-14.0-arm64-cpython-312/rng_extension.o.d -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -I/Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/self_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c -c /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/rng_extension.cpp -o /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/build/temp.macosx-14.0-arm64-cpython-312/rng_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_clang"' '-DPYBIND11_STDLIB="_libcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1002"' -DTORCH_EXTENSION_NAME=rng -std=c++17
2025-07-17T07:07:10.1974930Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/build/temp.macosx-14.0-arm64-cpython-312/rng_extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/rng.cpython-312-darwin.so
2025-07-17T07:07:10.2417270Z building 'torch_test_cpp_extension.mps' extension
2025-07-17T07:07:16.7828910Z [1/1] clang++ -MMD -MF /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/build/temp.macosx-14.0-arm64-cpython-312/mps_extension.o.d -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -I/Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/self_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c -c /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/mps_extension.mm -o /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/build/temp.macosx-14.0-arm64-cpython-312/mps_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_clang"' '-DPYBIND11_STDLIB="_libcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1002"' -DTORCH_EXTENSION_NAME=mps -std=c++17
2025-07-17T07:07:16.7832480Z In file included from /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/mps_extension.mm:2:
2025-07-17T07:07:16.7833150Z In file included from /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/ATen/native/mps/OperationUtils.h:10:
2025-07-17T07:07:16.7834260Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/ATen/mps/MPSStream.h:120:3: warning: 'MPSGraphCompilationDescriptor' is only available on macOS 12.0 or newer [-Wunguarded-availability-new]
2025-07-17T07:07:16.7835050Z   MPSGraphCompilationDescriptor* _compilationDescriptor = nil;
2025-07-17T07:07:16.7835290Z   ^
2025-07-17T07:07:16.7836300Z /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk/System/Library/Frameworks/MetalPerformanceShadersGraph.framework/Headers/MPSGraph.h:94:12: note: 'MPSGraphCompilationDescriptor' has been marked as being introduced in macOS 12.0 here, but the deployment target is macOS 11.1.0
2025-07-17T07:07:16.7837230Z @interface MPSGraphCompilationDescriptor : MPSGraphObject <NSCopying>
2025-07-17T07:07:16.7837490Z            ^
2025-07-17T07:07:16.7838180Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/ATen/mps/MPSStream.h:54:17: note: annotate 'MPSStream' with an availability attribute to silence this warning
2025-07-17T07:07:16.7838770Z class TORCH_API MPSStream {
2025-07-17T07:07:16.7838930Z                 ^
2025-07-17T07:07:16.7839070Z       API_AVAILABLE(macos(12.0))
2025-07-17T07:07:16.7839240Z 1 warning generated.
2025-07-17T07:07:16.7868890Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/build/temp.macosx-14.0-arm64-cpython-312/mps_extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/mps.cpython-312-darwin.so
2025-07-17T07:07:16.8301680Z running install_lib
2025-07-17T07:07:16.8340360Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/cpp.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:07:16.8344770Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/mps.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:07:16.8347870Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/rng.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:07:16.8351740Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/maia.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:07:16.8357400Z running install_egg_info
2025-07-17T07:07:16.8431240Z running egg_info
2025-07-17T07:07:16.8457200Z writing torch_test_cpp_extension.egg-info/PKG-INFO
2025-07-17T07:07:16.8461540Z writing dependency_links to torch_test_cpp_extension.egg-info/dependency_links.txt
2025-07-17T07:07:16.8462800Z writing entry points to torch_test_cpp_extension.egg-info/entry_points.txt
2025-07-17T07:07:16.8464270Z writing top-level names to torch_test_cpp_extension.egg-info/top_level.txt
2025-07-17T07:07:16.8493960Z reading manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-07-17T07:07:16.8497540Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-07-17T07:07:16.8498430Z removing './install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension-0.0.0-py3.12.egg-info' (and everything under it)
2025-07-17T07:07:16.8503020Z Copying torch_test_cpp_extension.egg-info to ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension-0.0.0-py3.12.egg-info
2025-07-17T07:07:16.8511860Z running install_scripts
2025-07-17T07:07:18.0397010Z running install
2025-07-17T07:07:18.0398050Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/setuptools/_distutils/cmd.py:66: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-07-17T07:07:18.0398610Z !!
2025-07-17T07:07:18.0398680Z 
2025-07-17T07:07:18.0398770Z         ********************************************************************************
2025-07-17T07:07:18.0399020Z         Please avoid running ``setup.py`` directly.
2025-07-17T07:07:18.0399270Z         Instead, use pypa/build, pypa/installer or other
2025-07-17T07:07:18.0399500Z         standards-based tools.
2025-07-17T07:07:18.0399620Z 
2025-07-17T07:07:18.0400070Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-07-17T07:07:18.0400400Z         ********************************************************************************
2025-07-17T07:07:18.0400640Z 
2025-07-17T07:07:18.0400690Z !!
2025-07-17T07:07:18.0400800Z   self.initialize_options()
2025-07-17T07:07:18.0463860Z running build
2025-07-17T07:07:18.0464120Z running build_ext
2025-07-17T07:07:18.0787140Z building 'no_python_abi_suffix_test' extension
2025-07-17T07:07:18.0787590Z creating /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/no_python_abi_suffix_test/build
2025-07-17T07:07:18.0788350Z creating /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/no_python_abi_suffix_test/build/temp.macosx-14.0-arm64-cpython-312
2025-07-17T07:07:18.1529100Z [1/1] clang++ -MMD -MF /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/no_python_abi_suffix_test/build/temp.macosx-14.0-arm64-cpython-312/no_python_abi_suffix_test.o.d -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c -c /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/no_python_abi_suffix_test/no_python_abi_suffix_test.cpp -o /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/no_python_abi_suffix_test/build/temp.macosx-14.0-arm64-cpython-312/no_python_abi_suffix_test.o -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_clang"' '-DPYBIND11_STDLIB="_libcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1002"' -DTORCH_EXTENSION_NAME=no_python_abi_suffix_test -std=c++17
2025-07-17T07:07:18.1565750Z creating build/lib.macosx-14.0-arm64-cpython-312
2025-07-17T07:07:18.1568950Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/no_python_abi_suffix_test/build/temp.macosx-14.0-arm64-cpython-312/no_python_abi_suffix_test.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/no_python_abi_suffix_test.so
2025-07-17T07:07:18.1976800Z running install_lib
2025-07-17T07:07:18.2013770Z creating install
2025-07-17T07:07:18.2014220Z creating install/Users
2025-07-17T07:07:18.2014790Z creating install/Users/ec2-user
2025-07-17T07:07:18.2015340Z creating install/Users/ec2-user/runner
2025-07-17T07:07:18.2015870Z creating install/Users/ec2-user/runner/_work
2025-07-17T07:07:18.2016440Z creating install/Users/ec2-user/runner/_work/_temp
2025-07-17T07:07:18.2016980Z creating install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:07:18.2017490Z creating install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib
2025-07-17T07:07:18.2018110Z creating install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12
2025-07-17T07:07:18.2018630Z creating install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages
2025-07-17T07:07:18.2019580Z copying build/lib.macosx-14.0-arm64-cpython-312/no_python_abi_suffix_test.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages
2025-07-17T07:07:18.2024550Z running install_egg_info
2025-07-17T07:07:18.2104580Z running egg_info
2025-07-17T07:07:18.2105000Z creating no_python_abi_suffix_test.egg-info
2025-07-17T07:07:18.2131820Z writing no_python_abi_suffix_test.egg-info/PKG-INFO
2025-07-17T07:07:18.2135610Z writing dependency_links to no_python_abi_suffix_test.egg-info/dependency_links.txt
2025-07-17T07:07:18.2137000Z writing top-level names to no_python_abi_suffix_test.egg-info/top_level.txt
2025-07-17T07:07:18.2138030Z writing manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt'
2025-07-17T07:07:18.2166620Z reading manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt'
2025-07-17T07:07:18.2169690Z writing manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt'
2025-07-17T07:07:18.2170600Z Copying no_python_abi_suffix_test.egg-info to ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/no_python_abi_suffix_test-0.0.0-py3.12.egg-info
2025-07-17T07:07:18.2179970Z running install_scripts
2025-07-17T07:07:18.4215920Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:07:18.4221140Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_cpp_extensions_aot_ninja.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:07:18.421982]
2025-07-17T07:07:20.6105860Z 
2025-07-17T07:07:20.6106430Z test_cpp_extensions_aot_ninja 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_aot_ninja_1.1_65f155936d2399fd_.log
2025-07-17T07:07:20.6111770Z Running 21 items in this shard: test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_backward, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_cublas_extension, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_cuda_dlink_libs, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_cuda_extension, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_cusolver_extension, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_extension_function, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_extension_module, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_mps_extension, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_no_python_abi_suffix_sets_the_correct_library_name, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_optional, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_sycl_extension, test/test_cpp_extensions_aot_ninja.py::TestPybindTypeCasters::test_pybind_return_types, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_add, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_autocast_apis_for_maia_device, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_conv_backend_override, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_matmul_autocast_default_precision, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_matmul_autocast_float16_precision, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_unregistered, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_zeros, test/test_cpp_extensions_aot_ninja.py::TestRNGExtension::test_rng, test/test_cpp_extensions_aot_ninja.py::TestTorchLibrary::test_torch_library
2025-07-17T07:07:20.6116040Z 
2025-07-17T07:07:20.6116190Z Running test_cpp_extensions_aot_no_ninja 1/1 ... [2025-07-17 07:07:20.611243]
2025-07-17T07:07:20.6128270Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading
2025-07-17T07:07:20.6128580Z Uploading artifacts took 0.00 seconds
2025-07-17T07:07:22.0115270Z running install
2025-07-17T07:07:22.0116280Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/setuptools/_distutils/cmd.py:66: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-07-17T07:07:22.0116830Z !!
2025-07-17T07:07:22.0116900Z 
2025-07-17T07:07:22.0116990Z         ********************************************************************************
2025-07-17T07:07:22.0117240Z         Please avoid running ``setup.py`` directly.
2025-07-17T07:07:22.0117490Z         Instead, use pypa/build, pypa/installer or other
2025-07-17T07:07:22.0117730Z         standards-based tools.
2025-07-17T07:07:22.0117860Z 
2025-07-17T07:07:22.0118320Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-07-17T07:07:22.0118660Z         ********************************************************************************
2025-07-17T07:07:22.0118890Z 
2025-07-17T07:07:22.0118930Z !!
2025-07-17T07:07:22.0119060Z   self.initialize_options()
2025-07-17T07:07:22.0182730Z running build
2025-07-17T07:07:22.0182940Z running build_py
2025-07-17T07:07:22.0213090Z creating build
2025-07-17T07:07:22.0213680Z creating build/lib.macosx-14.0-arm64-cpython-312
2025-07-17T07:07:22.0214310Z creating build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension
2025-07-17T07:07:22.0215110Z copying torch_test_cpp_extension/__init__.py -> build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension
2025-07-17T07:07:22.0218670Z running build_ext
2025-07-17T07:07:22.0226410Z building 'torch_test_cpp_extension.cpp' extension
2025-07-17T07:07:22.0226800Z creating build/temp.macosx-14.0-arm64-cpython-312
2025-07-17T07:07:22.0229950Z clang -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c extension.cpp -o build/temp.macosx-14.0-arm64-cpython-312/extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=cpp -std=c++17
2025-07-17T07:07:28.7083200Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk build/temp.macosx-14.0-arm64-cpython-312/extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/cpp.cpython-312-darwin.so
2025-07-17T07:07:28.7516450Z building 'torch_test_cpp_extension.maia' extension
2025-07-17T07:07:28.7519860Z clang -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c maia_extension.cpp -o build/temp.macosx-14.0-arm64-cpython-312/maia_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=maia -std=c++17
2025-07-17T07:07:35.2603310Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk build/temp.macosx-14.0-arm64-cpython-312/maia_extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/maia.cpython-312-darwin.so
2025-07-17T07:07:35.3041930Z building 'torch_test_cpp_extension.rng' extension
2025-07-17T07:07:35.3045610Z clang -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c rng_extension.cpp -o build/temp.macosx-14.0-arm64-cpython-312/rng_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=rng -std=c++17
2025-07-17T07:07:42.4324910Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk build/temp.macosx-14.0-arm64-cpython-312/rng_extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/rng.cpython-312-darwin.so
2025-07-17T07:07:42.4757030Z building 'torch_test_cpp_extension.mps' extension
2025-07-17T07:07:42.4760280Z clang -fno-strict-overflow -Wsign-compare -Wunreachable-code -fno-common -dynamic -DNDEBUG -g -O3 -Wall -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/include -I/opt/homebrew/opt/python@3.12/Frameworks/Python.framework/Versions/3.12/include/python3.12 -c mps_extension.mm -o build/temp.macosx-14.0-arm64-cpython-312/mps_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE=\"_clang\" -DPYBIND11_STDLIB=\"_libcpp\" -DPYBIND11_BUILD_ABI=\"_cxxabi1002\" -DTORCH_EXTENSION_NAME=mps -std=c++17
2025-07-17T07:07:46.1417720Z In file included from mps_extension.mm:2:
2025-07-17T07:07:46.1418340Z In file included from /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/ATen/native/mps/OperationUtils.h:10:
2025-07-17T07:07:46.1419370Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/ATen/mps/MPSStream.h:120:3: warning: 'MPSGraphCompilationDescriptor' is only available on macOS 12.0 or newer [-Wunguarded-availability-new]
2025-07-17T07:07:46.1420170Z   MPSGraphCompilationDescriptor* _compilationDescriptor = nil;
2025-07-17T07:07:46.1420420Z   ^
2025-07-17T07:07:46.1421190Z /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk/System/Library/Frameworks/MetalPerformanceShadersGraph.framework/Headers/MPSGraph.h:94:12: note: 'MPSGraphCompilationDescriptor' has been marked as being introduced in macOS 12.0 here, but the deployment target is macOS 11.1.0
2025-07-17T07:07:46.1422110Z @interface MPSGraphCompilationDescriptor : MPSGraphObject <NSCopying>
2025-07-17T07:07:46.1422370Z            ^
2025-07-17T07:07:46.1422920Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/ATen/mps/MPSStream.h:54:17: note: annotate 'MPSStream' with an availability attribute to silence this warning
2025-07-17T07:07:46.1423510Z class TORCH_API MPSStream {
2025-07-17T07:07:46.1423660Z                 ^
2025-07-17T07:07:46.1423800Z       API_AVAILABLE(macos(12.0))
2025-07-17T07:07:48.9294710Z 1 warning generated.
2025-07-17T07:07:48.9405120Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk build/temp.macosx-14.0-arm64-cpython-312/mps_extension.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/mps.cpython-312-darwin.so
2025-07-17T07:07:48.9833010Z running install_lib
2025-07-17T07:07:48.9872520Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/cpp.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:07:48.9877080Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/mps.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:07:48.9880220Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/rng.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:07:48.9883970Z copying build/lib.macosx-14.0-arm64-cpython-312/torch_test_cpp_extension/maia.cpython-312-darwin.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension
2025-07-17T07:07:48.9890430Z running install_egg_info
2025-07-17T07:07:48.9965480Z running egg_info
2025-07-17T07:07:48.9991890Z writing torch_test_cpp_extension.egg-info/PKG-INFO
2025-07-17T07:07:48.9996200Z writing dependency_links to torch_test_cpp_extension.egg-info/dependency_links.txt
2025-07-17T07:07:48.9997300Z writing entry points to torch_test_cpp_extension.egg-info/entry_points.txt
2025-07-17T07:07:48.9998690Z writing top-level names to torch_test_cpp_extension.egg-info/top_level.txt
2025-07-17T07:07:49.0029860Z reading manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-07-17T07:07:49.0033720Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt'
2025-07-17T07:07:49.0034670Z removing './install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension-0.0.0-py3.12.egg-info' (and everything under it)
2025-07-17T07:07:49.0039170Z Copying torch_test_cpp_extension.egg-info to ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch_test_cpp_extension-0.0.0-py3.12.egg-info
2025-07-17T07:07:49.0047840Z running install_scripts
2025-07-17T07:07:50.1855370Z running install
2025-07-17T07:07:50.1856460Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/setuptools/_distutils/cmd.py:66: SetuptoolsDeprecationWarning: setup.py install is deprecated.
2025-07-17T07:07:50.1857020Z !!
2025-07-17T07:07:50.1857090Z 
2025-07-17T07:07:50.1857180Z         ********************************************************************************
2025-07-17T07:07:50.1857430Z         Please avoid running ``setup.py`` directly.
2025-07-17T07:07:50.1857680Z         Instead, use pypa/build, pypa/installer or other
2025-07-17T07:07:50.1857910Z         standards-based tools.
2025-07-17T07:07:50.1858020Z 
2025-07-17T07:07:50.1858220Z         See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details.
2025-07-17T07:07:50.1858540Z         ********************************************************************************
2025-07-17T07:07:50.1858690Z 
2025-07-17T07:07:50.1858740Z !!
2025-07-17T07:07:50.1858860Z   self.initialize_options()
2025-07-17T07:07:50.1922560Z running build
2025-07-17T07:07:50.1922750Z running build_ext
2025-07-17T07:07:50.2244560Z building 'no_python_abi_suffix_test' extension
2025-07-17T07:07:50.2781200Z ninja: no work to do.
2025-07-17T07:07:50.2817000Z clang++ -bundle -undefined dynamic_lookup -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk /Users/ec2-user/runner/_work/pytorch/pytorch/test/cpp_extensions/no_python_abi_suffix_test/build/temp.macosx-14.0-arm64-cpython-312/no_python_abi_suffix_test.o -L/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.macosx-14.0-arm64-cpython-312/no_python_abi_suffix_test.so
2025-07-17T07:07:50.3239850Z running install_lib
2025-07-17T07:07:50.3277100Z copying build/lib.macosx-14.0-arm64-cpython-312/no_python_abi_suffix_test.so -> ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages
2025-07-17T07:07:50.3282070Z running install_egg_info
2025-07-17T07:07:50.3362810Z running egg_info
2025-07-17T07:07:50.3389070Z writing no_python_abi_suffix_test.egg-info/PKG-INFO
2025-07-17T07:07:50.3393830Z writing dependency_links to no_python_abi_suffix_test.egg-info/dependency_links.txt
2025-07-17T07:07:50.3395290Z writing top-level names to no_python_abi_suffix_test.egg-info/top_level.txt
2025-07-17T07:07:50.3424580Z reading manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt'
2025-07-17T07:07:50.3427850Z writing manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt'
2025-07-17T07:07:50.3428820Z removing './install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/no_python_abi_suffix_test-0.0.0-py3.12.egg-info' (and everything under it)
2025-07-17T07:07:50.3432620Z Copying no_python_abi_suffix_test.egg-info to ./install/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/no_python_abi_suffix_test-0.0.0-py3.12.egg-info
2025-07-17T07:07:50.3439780Z running install_scripts
2025-07-17T07:07:50.5479510Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:07:50.5483640Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_cpp_extensions_aot_no_ninja.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:07:50.548247]
2025-07-17T07:07:52.7294870Z 
2025-07-17T07:07:52.7295530Z test_cpp_extensions_aot_no_ninja 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_aot_no_ninja_1.1_24f3d5c48ba739d3_.log
2025-07-17T07:07:52.7300370Z Running 21 items in this shard: test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_backward, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_cublas_extension, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_cuda_dlink_libs, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_cuda_extension, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_cusolver_extension, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_extension_function, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_extension_module, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_mps_extension, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_no_python_abi_suffix_sets_the_correct_library_name, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_optional, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_sycl_extension, test/test_cpp_extensions_aot_no_ninja.py::TestPybindTypeCasters::test_pybind_return_types, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_add, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_autocast_apis_for_maia_device, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_conv_backend_override, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_matmul_autocast_default_precision, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_matmul_autocast_float16_precision, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_unregistered, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_zeros, test/test_cpp_extensions_aot_no_ninja.py::TestRNGExtension::test_rng, test/test_cpp_extensions_aot_no_ninja.py::TestTorchLibrary::test_torch_library
2025-07-17T07:07:52.7304830Z 
2025-07-17T07:07:52.7305020Z Running inductor/test_torchinductor_dynamic_shapes 1/2 ... [2025-07-17 07:07:52.730051]
2025-07-17T07:07:52.7305340Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:07:52.7306290Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor_dynamic_shapes.py', '-m', 'serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:07:52.730302]
2025-07-17T07:07:55.3469610Z 
2025-07-17T07:07:55.3470770Z inductor/test_torchinductor_dynamic_shapes 1/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_dynamic_shapes_1.2_c09c62cc731ae947_.log
2025-07-17T07:07:55.3472400Z Running 2 items in this shard: test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_large_block_sizes_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_wrapper_codegen_statically_known_int_or_none_cpu
2025-07-17T07:07:55.3473260Z 
2025-07-17T07:07:55.3474450Z Running test_decomp 2/4 ... [2025-07-17 07:07:55.347386]
2025-07-17T07:07:55.3474750Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:07:55.3478120Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_decomp.py', '-m', 'serial', '--shard-id=2', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:07:55.347701]
2025-07-17T07:07:58.6624080Z 
2025-07-17T07:07:58.6624630Z test_decomp 2/4 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_2.4_4df8f75176e57e8a_.log
2025-07-17T07:07:58.6625200Z Running 0 items in this shard:
2025-07-17T07:07:58.6625360Z 
2025-07-17T07:07:58.6629280Z Running test_decomp 3/4 ... [2025-07-17 07:07:58.662851]
2025-07-17T07:07:58.6629590Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:07:58.6632950Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_decomp.py', '-m', 'serial', '--shard-id=3', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:07:58.663186]
2025-07-17T07:08:01.9802510Z 
2025-07-17T07:08:01.9803140Z test_decomp 3/4 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_3.4_0e23fd5b46739c33_.log
2025-07-17T07:08:01.9803740Z Running 0 items in this shard:
2025-07-17T07:08:01.9803920Z 
2025-07-17T07:08:01.9808110Z Running test_decomp 4/4 ... [2025-07-17 07:08:01.980738]
2025-07-17T07:08:01.9808470Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:01.9812200Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_decomp.py', '-m', 'serial', '--shard-id=4', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:01.981099]
2025-07-17T07:08:05.2523880Z 
2025-07-17T07:08:05.2524600Z test_decomp 4/4 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_4.4_370855f05f1166d3_.log
2025-07-17T07:08:05.2525050Z Running 0 items in this shard:
2025-07-17T07:08:05.2525180Z 
2025-07-17T07:08:05.2528720Z Running inductor/test_triton_extension_backend 1/1 ... [2025-07-17 07:08:05.252781]
2025-07-17T07:08:05.2529050Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:05.2531850Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_triton_extension_backend.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:05.253068]
2025-07-17T07:08:07.5476850Z 
2025-07-17T07:08:07.5477530Z inductor/test_triton_extension_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_triton_extension_backend_1.1_0cb08fb42153ece5_.log
2025-07-17T07:08:07.5478050Z 
2025-07-17T07:08:07.5481320Z Running inductor/test_extension_backend 1/1 ... [2025-07-17 07:08:07.548052]
2025-07-17T07:08:07.5481630Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:07.5484850Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_extension_backend.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:07.548341]
2025-07-17T07:08:09.8230080Z 
2025-07-17T07:08:09.8230760Z inductor/test_extension_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_extension_backend_1.1_f84fa21f967e89a7_.log
2025-07-17T07:08:09.8231250Z 
2025-07-17T07:08:09.8234550Z Running inductor/test_kernel_benchmark 1/1 ... [2025-07-17 07:08:09.823371]
2025-07-17T07:08:09.8234860Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:09.8237960Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_kernel_benchmark.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:09.823663]
2025-07-17T07:08:12.0114680Z 
2025-07-17T07:08:12.0115320Z inductor/test_kernel_benchmark 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_kernel_benchmark_1.1_3400d2fbcf9a9184_.log
2025-07-17T07:08:12.0115820Z 
2025-07-17T07:08:12.0119390Z Running inductor/test_cpu_cpp_wrapper 1/1 ... [2025-07-17 07:08:12.011855]
2025-07-17T07:08:12.0119710Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:12.0122790Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_cpu_cpp_wrapper.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:12.012166]
2025-07-17T07:08:14.6043700Z 
2025-07-17T07:08:14.6044350Z inductor/test_cpu_cpp_wrapper 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_cpp_wrapper_1.1_6989aced2401824f_.log
2025-07-17T07:08:14.6044840Z 
2025-07-17T07:08:14.6048060Z Running inductor/test_torchinductor_strided_blocks 1/1 ... [2025-07-17 07:08:14.604721]
2025-07-17T07:08:14.6048410Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:14.6050900Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor_strided_blocks.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:14.605006]
2025-07-17T07:08:16.9080590Z 
2025-07-17T07:08:16.9081240Z inductor/test_torchinductor_strided_blocks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_strided_blocks_1.1_e21fea0ad86cd003_.log
2025-07-17T07:08:16.9081790Z 
2025-07-17T07:08:16.9084810Z Running inductor/test_pad_mm 1/1 ... [2025-07-17 07:08:16.908406]
2025-07-17T07:08:16.9085080Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:16.9087980Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_pad_mm.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:16.908689]
2025-07-17T07:08:19.1054230Z 
2025-07-17T07:08:19.1054840Z inductor/test_pad_mm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_pad_mm_1.1_9ffee3ca4fc5c966_.log
2025-07-17T07:08:19.1055270Z 
2025-07-17T07:08:19.1059050Z Running inductor/test_torchinductor 2/2 ... [2025-07-17 07:08:19.105818]
2025-07-17T07:08:19.1059360Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:19.1062180Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor.py', '-m', 'serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:19.106114]
2025-07-17T07:08:21.7092690Z 
2025-07-17T07:08:21.7093330Z inductor/test_torchinductor 2/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_2.2_96dea08f27202994_.log
2025-07-17T07:08:21.7094460Z Running 1 items in this shard: test/inductor/test_torchinductor.py::GPUTests::test_large_block_sizes_mps
2025-07-17T07:08:21.7094830Z 
2025-07-17T07:08:21.7097790Z Running test_file_check 1/1 ... [2025-07-17 07:08:21.709705]
2025-07-17T07:08:21.7098110Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:21.7101650Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_file_check.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:21.710032]
2025-07-17T07:08:23.4588110Z 
2025-07-17T07:08:23.4588610Z test_file_check 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_file_check_1.1_169fe66bf80d11c5_.log
2025-07-17T07:08:23.4589070Z Running 0 items in this shard:
2025-07-17T07:08:23.4589210Z 
2025-07-17T07:08:23.4592270Z Running export/test_tree_utils 1/1 ... [2025-07-17 07:08:23.459172]
2025-07-17T07:08:23.4592540Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:23.4595260Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_tree_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:23.459438]
2025-07-17T07:08:25.2281700Z 
2025-07-17T07:08:25.2282360Z export/test_tree_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_tree_utils_1.1_ad9d25cbb016eef3_.log
2025-07-17T07:08:25.2283010Z Running 0 items in this shard:
2025-07-17T07:08:25.2283170Z 
2025-07-17T07:08:25.2286710Z Running inductor/test_indexing 1/1 ... [2025-07-17 07:08:25.228604]
2025-07-17T07:08:25.2287070Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:25.2290410Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_indexing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:25.228932]
2025-07-17T07:08:27.5288040Z 
2025-07-17T07:08:27.5290900Z inductor/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_indexing_1.1_2f2c863a388ee552_.log
2025-07-17T07:08:27.5291530Z Running 0 items in this shard:
2025-07-17T07:08:27.5291690Z 
2025-07-17T07:08:27.5294720Z Running dynamo/test_buffers_override 1/1 ... [2025-07-17 07:08:27.529396]
2025-07-17T07:08:27.5295110Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:27.5299060Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_buffers_override.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:27.529768]
2025-07-17T07:08:29.2908740Z 
2025-07-17T07:08:29.2909470Z dynamo/test_buffers_override 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_buffers_override_1.1_9878c1412f44463d_.log
2025-07-17T07:08:29.2910140Z Running 0 items in this shard:
2025-07-17T07:08:29.2910300Z 
2025-07-17T07:08:29.2913960Z Running test_appending_byte_serializer 1/1 ... [2025-07-17 07:08:29.291325]
2025-07-17T07:08:29.2914320Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:29.2917920Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_appending_byte_serializer.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:29.291656]
2025-07-17T07:08:31.0474430Z 
2025-07-17T07:08:31.0475030Z test_appending_byte_serializer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_appending_byte_serializer_1.1_8bcb2dec943a9a51_.log
2025-07-17T07:08:31.0475630Z Running 0 items in this shard:
2025-07-17T07:08:31.0475770Z 
2025-07-17T07:08:31.0478950Z Running dynamo/test_resume 1/1 ... [2025-07-17 07:08:31.047829]
2025-07-17T07:08:31.0479240Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:31.0482440Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_resume.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:31.048128]
2025-07-17T07:08:32.8184710Z 
2025-07-17T07:08:32.8185370Z dynamo/test_resume 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_resume_1.1_6b9fd277b05c5c30_.log
2025-07-17T07:08:32.8186030Z Running 0 items in this shard:
2025-07-17T07:08:32.8186210Z 
2025-07-17T07:08:32.8190520Z Running inductor/test_aot_inductor 1/1 ... [2025-07-17 07:08:32.818967]
2025-07-17T07:08:32.8190920Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:32.8194510Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_aot_inductor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:32.819324]
2025-07-17T07:08:35.3028630Z 
2025-07-17T07:08:35.3029230Z inductor/test_aot_inductor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_1.1_a7295b71df3b1c01_.log
2025-07-17T07:08:35.3029820Z Running 0 items in this shard:
2025-07-17T07:08:35.3029960Z 
2025-07-17T07:08:35.3033230Z Running inductor/test_combo_kernels 1/1 ... [2025-07-17 07:08:35.303263]
2025-07-17T07:08:35.3033550Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:35.3036500Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_combo_kernels.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:35.303553]
2025-07-17T07:08:37.6693410Z 
2025-07-17T07:08:37.6694020Z inductor/test_combo_kernels 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_combo_kernels_1.1_aa3d38fcb809ece8_.log
2025-07-17T07:08:37.6694610Z Running 0 items in this shard:
2025-07-17T07:08:37.6694750Z 
2025-07-17T07:08:37.6697980Z Running torch_np/test_dtype 1/1 ... [2025-07-17 07:08:37.669736]
2025-07-17T07:08:37.6698270Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:37.6701460Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'torch_np/test_dtype.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:37.670047]
2025-07-17T07:08:39.4236460Z 
2025-07-17T07:08:39.4237060Z torch_np/test_dtype 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_dtype_1.1_a61e552b468b1825_.log
2025-07-17T07:08:39.4237590Z Running 0 items in this shard:
2025-07-17T07:08:39.4237740Z 
2025-07-17T07:08:39.4241540Z Running inductor/test_metrics 1/1 ... [2025-07-17 07:08:39.424088]
2025-07-17T07:08:39.4241850Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:39.4245240Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_metrics.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:39.424405]
2025-07-17T07:08:41.6168510Z 
2025-07-17T07:08:41.6169110Z inductor/test_metrics 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_metrics_1.1_7ffe6a52dae86d62_.log
2025-07-17T07:08:41.6169550Z 
2025-07-17T07:08:41.6172770Z Running test_proxy_tensor 1/1 ... [2025-07-17 07:08:41.617204]
2025-07-17T07:08:41.6173050Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:41.6176040Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_proxy_tensor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:41.617490]
2025-07-17T07:08:44.5803120Z 
2025-07-17T07:08:44.5803690Z test_proxy_tensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_proxy_tensor_1.1_d43b6db329e5e214_.log
2025-07-17T07:08:44.5804260Z Running 0 items in this shard:
2025-07-17T07:08:44.5804420Z 
2025-07-17T07:08:44.5808370Z Running inductor/test_gpu_cpp_wrapper 1/1 ... [2025-07-17 07:08:44.580763]
2025-07-17T07:08:44.5808700Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:44.5811870Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_gpu_cpp_wrapper.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:44.581088]
2025-07-17T07:08:47.0065490Z 
2025-07-17T07:08:47.0066160Z inductor/test_gpu_cpp_wrapper 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_gpu_cpp_wrapper_1.1_9bbb72b43df82e15_.log
2025-07-17T07:08:47.0066640Z 
2025-07-17T07:08:47.0069860Z Running inductor/test_torchinductor_opinfo 2/14 ... [2025-07-17 07:08:47.006909]
2025-07-17T07:08:47.0070180Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:47.0073130Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor_opinfo.py', '-m', 'serial', '--shard-id=2', '--num-shards=14', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:47.007195]
2025-07-17T07:08:50.2528990Z 
2025-07-17T07:08:50.2529640Z inductor/test_torchinductor_opinfo 2/14 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_opinfo_2.14_9d60b94bf5f4861d_.log
2025-07-17T07:08:50.2530320Z Running 0 items in this shard:
2025-07-17T07:08:50.2530480Z 
2025-07-17T07:08:50.2534130Z Running inductor/test_torchinductor_opinfo 6/14 ... [2025-07-17 07:08:50.253342]
2025-07-17T07:08:50.2534480Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:50.2537790Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor_opinfo.py', '-m', 'serial', '--shard-id=6', '--num-shards=14', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:50.253664]
2025-07-17T07:08:53.5055340Z 
2025-07-17T07:08:53.5056140Z inductor/test_torchinductor_opinfo 6/14 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_opinfo_6.14_def2fdd3dbfd2971_.log
2025-07-17T07:08:53.5056930Z Running 0 items in this shard:
2025-07-17T07:08:53.5057100Z 
2025-07-17T07:08:53.5061230Z Running inductor/test_torchinductor_opinfo 7/14 ... [2025-07-17 07:08:53.506035]
2025-07-17T07:08:53.5061680Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:53.5065340Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor_opinfo.py', '-m', 'serial', '--shard-id=7', '--num-shards=14', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:53.506389]
2025-07-17T07:08:56.7798760Z 
2025-07-17T07:08:56.7799470Z inductor/test_torchinductor_opinfo 7/14 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_opinfo_7.14_6dde482f4653cdf6_.log
2025-07-17T07:08:56.7800220Z Running 0 items in this shard:
2025-07-17T07:08:56.7800390Z 
2025-07-17T07:08:56.7804280Z Running inductor/test_torchinductor_opinfo 11/14 ... [2025-07-17 07:08:56.780337]
2025-07-17T07:08:56.7804680Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:08:56.7808100Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor_opinfo.py', '-m', 'serial', '--shard-id=11', '--num-shards=14', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:08:56.780675]
2025-07-17T07:09:00.0531620Z 
2025-07-17T07:09:00.0532410Z inductor/test_torchinductor_opinfo 11/14 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_opinfo_11.14_7642364862bd9d2d_.log
2025-07-17T07:09:00.0533190Z Running 0 items in this shard:
2025-07-17T07:09:00.0533360Z 
2025-07-17T07:09:00.0537080Z Running inductor/test_static_cuda_launcher 1/1 ... [2025-07-17 07:09:00.053623]
2025-07-17T07:09:00.0537510Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:00.0541060Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_static_cuda_launcher.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:00.053979]
2025-07-17T07:09:02.3533380Z 
2025-07-17T07:09:02.3534000Z inductor/test_static_cuda_launcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_static_cuda_launcher_1.1_25a1bc7b057baf21_.log
2025-07-17T07:09:02.3534670Z Running 0 items in this shard:
2025-07-17T07:09:02.3534810Z 
2025-07-17T07:09:02.3538140Z Running inductor/test_utils 1/1 ... [2025-07-17 07:09:02.353744]
2025-07-17T07:09:02.3538430Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:02.3541490Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:02.354045]
2025-07-17T07:09:04.2442090Z 
2025-07-17T07:09:04.2442760Z inductor/test_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_utils_1.1_c96c1c5840a96783_.log
2025-07-17T07:09:04.2443330Z Running 0 items in this shard:
2025-07-17T07:09:04.2443480Z 
2025-07-17T07:09:04.2446880Z Running dynamo/test_subgraphs 1/1 ... [2025-07-17 07:09:04.244622]
2025-07-17T07:09:04.2447200Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:04.2453250Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_subgraphs.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:04.244942]
2025-07-17T07:09:06.0802350Z 
2025-07-17T07:09:06.0802920Z dynamo/test_subgraphs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_subgraphs_1.1_8195f6fd8b34751d_.log
2025-07-17T07:09:06.0803460Z Running 0 items in this shard:
2025-07-17T07:09:06.0803620Z 
2025-07-17T07:09:06.0807240Z Running dynamo/test_reconstruct 1/1 ... [2025-07-17 07:09:06.080648]
2025-07-17T07:09:06.0807560Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:06.0810570Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_reconstruct.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:06.080955]
2025-07-17T07:09:08.3885970Z 
2025-07-17T07:09:08.3886620Z dynamo/test_reconstruct 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_reconstruct_1.1_fa338c7dd1e8b9ae_.log
2025-07-17T07:09:08.3887300Z Running 0 items in this shard:
2025-07-17T07:09:08.3887460Z 
2025-07-17T07:09:08.3891280Z Running inductor/test_subgraph_choice 1/1 ... [2025-07-17 07:09:08.389045]
2025-07-17T07:09:08.3891880Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:08.3895120Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_subgraph_choice.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:08.389396]
2025-07-17T07:09:10.6003900Z 
2025-07-17T07:09:10.6004510Z inductor/test_subgraph_choice 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_subgraph_choice_1.1_df0c1b9dc9924a22_.log
2025-07-17T07:09:10.6005020Z 
2025-07-17T07:09:10.6008070Z Running dynamo/test_dicts 1/1 ... [2025-07-17 07:09:10.600734]
2025-07-17T07:09:10.6008350Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:10.6011020Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_dicts.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:10.601024]
2025-07-17T07:09:12.4844100Z 
2025-07-17T07:09:12.4844660Z dynamo/test_dicts 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_dicts_1.1_4e36b2c4fadf442a_.log
2025-07-17T07:09:12.4845230Z Running 0 items in this shard:
2025-07-17T07:09:12.4845380Z 
2025-07-17T07:09:12.4849210Z Running dynamo/test_dynamic_shapes 1/3 ... [2025-07-17 07:09:12.484847]
2025-07-17T07:09:12.4849560Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:12.4852700Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_dynamic_shapes.py', '-m', 'serial', '--shard-id=1', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:12.485165]
2025-07-17T07:09:15.6805970Z 
2025-07-17T07:09:15.6806600Z dynamo/test_dynamic_shapes 1/3 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_dynamic_shapes_1.3_3eb37c22f719deff_.log
2025-07-17T07:09:15.6807140Z Running 0 items in this shard:
2025-07-17T07:09:15.6807280Z 
2025-07-17T07:09:15.6810080Z Running dynamo/test_dynamic_shapes 2/3 ... [2025-07-17 07:09:15.680932]
2025-07-17T07:09:15.6810370Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:15.6813320Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_dynamic_shapes.py', '-m', 'serial', '--shard-id=2', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:15.681220]
2025-07-17T07:09:19.7770160Z 
2025-07-17T07:09:19.7770940Z dynamo/test_dynamic_shapes 2/3 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_dynamic_shapes_2.3_9e29138df0b97cd8_.log
2025-07-17T07:09:19.7772220Z Running 1 items in this shard: test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_dont_dce_rand_dynamic_shapes
2025-07-17T07:09:19.7772720Z 
2025-07-17T07:09:19.7775720Z Running dynamo/test_list 1/1 ... [2025-07-17 07:09:19.777487]
2025-07-17T07:09:19.7776090Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:19.7779820Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_list.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:19.777864]
2025-07-17T07:09:21.6166500Z 
2025-07-17T07:09:21.6166950Z dynamo/test_list 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_list_1.1_63a4f3b1b2928dbd_.log
2025-07-17T07:09:21.6167420Z Running 0 items in this shard:
2025-07-17T07:09:21.6167550Z 
2025-07-17T07:09:21.6170870Z Running higher_order_ops/test_with_effects 1/1 ... [2025-07-17 07:09:21.617013]
2025-07-17T07:09:21.6171250Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:21.6173760Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'higher_order_ops/test_with_effects.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:21.617282]
2025-07-17T07:09:23.6912180Z 
2025-07-17T07:09:23.6912830Z higher_order_ops/test_with_effects 1/1 was successful, full logs can be found in artifacts with path test/test-reports/higher_order_ops.test_with_effects_1.1_96d33c5e9338edee_.log
2025-07-17T07:09:23.6913400Z Running 0 items in this shard:
2025-07-17T07:09:23.6913530Z 
2025-07-17T07:09:23.6916330Z Running dynamo/test_fx_graph_runnable 1/1 ... [2025-07-17 07:09:23.691575]
2025-07-17T07:09:23.6916640Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:23.6919290Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_fx_graph_runnable.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:23.691834]
2025-07-17T07:09:25.4118780Z 
2025-07-17T07:09:25.4119450Z dynamo/test_fx_graph_runnable 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_fx_graph_runnable_1.1_9ed1adb161682565_.log
2025-07-17T07:09:25.4120000Z Running 0 items in this shard:
2025-07-17T07:09:25.4120130Z 
2025-07-17T07:09:25.4123170Z Running inductor/test_graph_transform_observer 1/1 ... [2025-07-17 07:09:25.412253]
2025-07-17T07:09:25.4123500Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:25.4126560Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_graph_transform_observer.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:25.412554]
2025-07-17T07:09:27.6129900Z 
2025-07-17T07:09:27.6130530Z inductor/test_graph_transform_observer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_graph_transform_observer_1.1_84922a069fc6a3fa_.log
2025-07-17T07:09:27.6131060Z 
2025-07-17T07:09:27.6134320Z Running test_openmp 1/1 ... [2025-07-17 07:09:27.613361]
2025-07-17T07:09:27.6134560Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:27.6137310Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_openmp.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:27.613633]
2025-07-17T07:09:29.3905890Z 
2025-07-17T07:09:29.3906640Z test_openmp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_openmp_1.1_7229378311afc2ed_.log
2025-07-17T07:09:29.3907200Z Running 0 items in this shard:
2025-07-17T07:09:29.3907360Z 
2025-07-17T07:09:29.3911380Z Running inductor/test_compiled_optimizers 1/1 ... [2025-07-17 07:09:29.391063]
2025-07-17T07:09:29.3911880Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:29.3915240Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_compiled_optimizers.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:29.391409]
2025-07-17T07:09:32.3624560Z 
2025-07-17T07:09:32.3625350Z inductor/test_compiled_optimizers 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compiled_optimizers_1.1_7025cf3e3ebc7584_.log
2025-07-17T07:09:32.3626060Z Running 0 items in this shard:
2025-07-17T07:09:32.3626440Z 
2025-07-17T07:09:32.3629690Z Running dynamo/test_functions 1/1 ... [2025-07-17 07:09:32.362893]
2025-07-17T07:09:32.3630030Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:32.3633340Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_functions.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:32.363221]
2025-07-17T07:09:34.7092900Z 
2025-07-17T07:09:34.7093490Z dynamo/test_functions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_functions_1.1_c26be90843449159_.log
2025-07-17T07:09:34.7094120Z Running 0 items in this shard:
2025-07-17T07:09:34.7094280Z 
2025-07-17T07:09:34.7097800Z Running torch_np/test_ufuncs_basic 1/1 ... [2025-07-17 07:09:34.709703]
2025-07-17T07:09:34.7098150Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:34.7101650Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'torch_np/test_ufuncs_basic.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:34.710053]
2025-07-17T07:09:36.4610440Z 
2025-07-17T07:09:36.4611050Z torch_np/test_ufuncs_basic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_ufuncs_basic_1.1_2f831282055f268f_.log
2025-07-17T07:09:36.4611600Z Running 0 items in this shard:
2025-07-17T07:09:36.4611720Z 
2025-07-17T07:09:36.4614720Z Running inductor/test_ordered_set 1/1 ... [2025-07-17 07:09:36.461392]
2025-07-17T07:09:36.4615020Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:36.4617870Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_ordered_set.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:36.461671]
2025-07-17T07:09:38.2423900Z 
2025-07-17T07:09:38.2424530Z inductor/test_ordered_set 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_ordered_set_1.1_8f73b765eb3b4c53_.log
2025-07-17T07:09:38.2425070Z Running 0 items in this shard:
2025-07-17T07:09:38.2425190Z 
2025-07-17T07:09:38.2428010Z Running test_compile_benchmark_util 1/1 ... [2025-07-17 07:09:38.242748]
2025-07-17T07:09:38.2428300Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:38.2431000Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_compile_benchmark_util.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:38.243009]
2025-07-17T07:09:40.0149790Z 
2025-07-17T07:09:40.0150700Z test_compile_benchmark_util 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_compile_benchmark_util_1.1_65954a52037f4f46_.log
2025-07-17T07:09:40.0151430Z Running 0 items in this shard:
2025-07-17T07:09:40.0151730Z 
2025-07-17T07:09:40.0155300Z Running export/test_passes 1/1 ... [2025-07-17 07:09:40.015453]
2025-07-17T07:09:40.0155670Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:40.0159340Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_passes.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:40.015813]
2025-07-17T07:09:42.2687660Z 
2025-07-17T07:09:42.2688260Z export/test_passes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_passes_1.1_965647bf0a208c71_.log
2025-07-17T07:09:42.2689050Z Running 0 items in this shard:
2025-07-17T07:09:42.2689280Z 
2025-07-17T07:09:42.2692870Z Running inductor/test_helion_kernels 1/1 ... [2025-07-17 07:09:42.269204]
2025-07-17T07:09:42.2693250Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:42.2696680Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_helion_kernels.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:42.269544]
2025-07-17T07:09:44.5648130Z 
2025-07-17T07:09:44.5648720Z inductor/test_helion_kernels 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_helion_kernels_1.1_02e49e729c793f39_.log
2025-07-17T07:09:44.5649300Z Running 0 items in this shard:
2025-07-17T07:09:44.5649440Z 
2025-07-17T07:09:44.5652810Z Running torch_np/test_random 1/1 ... [2025-07-17 07:09:44.565220]
2025-07-17T07:09:44.5653110Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:44.5656010Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'torch_np/test_random.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:44.565521]
2025-07-17T07:09:46.3321500Z 
2025-07-17T07:09:46.3322140Z torch_np/test_random 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_random_1.1_c8c00ae5c8872a17_.log
2025-07-17T07:09:46.3322750Z Running 0 items in this shard:
2025-07-17T07:09:46.3322900Z 
2025-07-17T07:09:46.3326280Z Running inductor/test_alignment 1/1 ... [2025-07-17 07:09:46.332555]
2025-07-17T07:09:46.3326620Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:46.3329610Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_alignment.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:46.332865]
2025-07-17T07:09:48.6979790Z 
2025-07-17T07:09:48.6980330Z inductor/test_alignment 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_alignment_1.1_d9e175f6aa1adcf0_.log
2025-07-17T07:09:48.6980880Z Running 0 items in this shard:
2025-07-17T07:09:48.6981010Z 
2025-07-17T07:09:48.6983920Z Running test_namedtensor 1/1 ... [2025-07-17 07:09:48.698338]
2025-07-17T07:09:48.6984180Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:48.6986930Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_namedtensor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:48.698605]
2025-07-17T07:09:50.5874300Z 
2025-07-17T07:09:50.5874930Z test_namedtensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_namedtensor_1.1_67e3d9c951107211_.log
2025-07-17T07:09:50.5875460Z Running 0 items in this shard:
2025-07-17T07:09:50.5875690Z 
2025-07-17T07:09:50.5878610Z Running export/test_package 1/1 ... [2025-07-17 07:09:50.587804]
2025-07-17T07:09:50.5878900Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:50.5881880Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_package.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:50.588093]
2025-07-17T07:09:52.3489590Z 
2025-07-17T07:09:52.3490330Z export/test_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_package_1.1_b4f0dd9da95423d8_.log
2025-07-17T07:09:52.3491030Z Running 0 items in this shard:
2025-07-17T07:09:52.3491190Z 
2025-07-17T07:09:52.3494550Z Running dynamo/test_config 1/1 ... [2025-07-17 07:09:52.349381]
2025-07-17T07:09:52.3494870Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:52.3497830Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_config.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:52.349682]
2025-07-17T07:09:54.1603110Z 
2025-07-17T07:09:54.1603670Z dynamo/test_config 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_config_1.1_5093a6d47ca21a7c_.log
2025-07-17T07:09:54.1604380Z Running 0 items in this shard:
2025-07-17T07:09:54.1604550Z 
2025-07-17T07:09:54.1607170Z Running inductor/test_cudacodecache 1/1 ... [2025-07-17 07:09:54.160669]
2025-07-17T07:09:54.1607490Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:54.1610420Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_cudacodecache.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:54.160943]
2025-07-17T07:09:55.8566500Z 
2025-07-17T07:09:55.8567140Z inductor/test_cudacodecache 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cudacodecache_1.1_82b5bd913b98a293_.log
2025-07-17T07:09:55.8567620Z 
2025-07-17T07:09:55.8570770Z Running inductor/test_codecache 1/1 ... [2025-07-17 07:09:55.856994]
2025-07-17T07:09:55.8571070Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:55.8573780Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_codecache.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:55.857267]
2025-07-17T07:09:58.2358360Z 
2025-07-17T07:09:58.2359080Z inductor/test_codecache 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_codecache_1.1_b00b23d29fe00cbd_.log
2025-07-17T07:09:58.2359810Z Running 0 items in this shard:
2025-07-17T07:09:58.2359980Z 
2025-07-17T07:09:58.2364060Z Running torch_np/numpy_tests/core/test_scalarinherit 1/1 ... [2025-07-17 07:09:58.236318]
2025-07-17T07:09:58.2364500Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:09:58.2368030Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'torch_np/numpy_tests/core/test_scalarinherit.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:09:58.236676]
2025-07-17T07:10:00.0035350Z 
2025-07-17T07:10:00.0036190Z torch_np/numpy_tests/core/test_scalarinherit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_scalarinherit_1.1_45156db0570d3214_.log
2025-07-17T07:10:00.0036980Z Running 0 items in this shard:
2025-07-17T07:10:00.0037120Z 
2025-07-17T07:10:00.0039670Z Running export/test_upgrader 1/1 ... [2025-07-17 07:10:00.003911]
2025-07-17T07:10:00.0039960Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:00.0042780Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_upgrader.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:00.004185]
2025-07-17T07:10:01.7775670Z 
2025-07-17T07:10:01.7776530Z export/test_upgrader 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_upgrader_1.1_4976d87c2ac3c7a7_.log
2025-07-17T07:10:01.7777280Z Running 0 items in this shard:
2025-07-17T07:10:01.7777450Z 
2025-07-17T07:10:01.7780860Z Running dynamo/test_compile 1/1 ... [2025-07-17 07:10:01.778008]
2025-07-17T07:10:01.7781240Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:01.7784970Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_compile.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:01.778374]
2025-07-17T07:10:03.6153290Z 
2025-07-17T07:10:03.6153880Z dynamo/test_compile 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_compile_1.1_54d8e236363f4246_.log
2025-07-17T07:10:03.6154490Z Running 0 items in this shard:
2025-07-17T07:10:03.6154640Z 
2025-07-17T07:10:03.6158020Z Running dynamo/test_after_aot 1/1 ... [2025-07-17 07:10:03.615733]
2025-07-17T07:10:03.6158350Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:03.6161470Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_after_aot.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:03.616046]
2025-07-17T07:10:05.4322230Z 
2025-07-17T07:10:05.4322840Z dynamo/test_after_aot 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_after_aot_1.1_8420cb62f37dba51_.log
2025-07-17T07:10:05.4323490Z Running 0 items in this shard:
2025-07-17T07:10:05.4323630Z 
2025-07-17T07:10:05.4326290Z Running test_hub 1/1 ... [2025-07-17 07:10:05.432578]
2025-07-17T07:10:05.4326530Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:05.4329190Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_hub.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:05.432837]
2025-07-17T07:10:07.2096010Z 
2025-07-17T07:10:07.2096590Z test_hub 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_hub_1.1_7fe88453f65bd6c7_.log
2025-07-17T07:10:07.2097200Z Running 0 items in this shard:
2025-07-17T07:10:07.2097370Z 
2025-07-17T07:10:07.2101480Z Running dynamo/test_autograd_function 1/1 ... [2025-07-17 07:10:07.210061]
2025-07-17T07:10:07.2101900Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:07.2105540Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_autograd_function.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:07.210427]
2025-07-17T07:10:09.5247800Z 
2025-07-17T07:10:09.5248690Z dynamo/test_autograd_function 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_autograd_function_1.1_b22e0015f63685b8_.log
2025-07-17T07:10:09.5249370Z Running 0 items in this shard:
2025-07-17T07:10:09.5249700Z 
2025-07-17T07:10:09.5252710Z Running export/test_db 1/1 ... [2025-07-17 07:10:09.525198]
2025-07-17T07:10:09.5253040Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:09.5256460Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_db.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:09.525536]
2025-07-17T07:10:11.2916630Z 
2025-07-17T07:10:11.2917430Z export/test_db 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_db_1.1_f9bdd27db00313a2_.log
2025-07-17T07:10:11.2918120Z Running 0 items in this shard:
2025-07-17T07:10:11.2918270Z 
2025-07-17T07:10:11.2921490Z Running test_optim 1/1 ... [2025-07-17 07:10:11.292072]
2025-07-17T07:10:11.2921780Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:11.2924820Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_optim.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:11.292381]
2025-07-17T07:10:13.8958040Z 
2025-07-17T07:10:13.8958530Z test_optim 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_optim_1.1_af33785b907011ab_.log
2025-07-17T07:10:13.8959080Z Running 0 items in this shard:
2025-07-17T07:10:13.8959240Z 
2025-07-17T07:10:13.8963190Z Running inductor/test_profiler 1/1 ... [2025-07-17 07:10:13.896239]
2025-07-17T07:10:13.8963560Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:13.8966800Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_profiler.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:13.896569]
2025-07-17T07:10:16.0829230Z 
2025-07-17T07:10:16.0829830Z inductor/test_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_profiler_1.1_1fbd66b42fb50021_.log
2025-07-17T07:10:16.0830310Z 
2025-07-17T07:10:16.0833430Z Running inductor/test_cpu_select_algorithm 1/1 ... [2025-07-17 07:10:16.083262]
2025-07-17T07:10:16.0833760Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:16.0836180Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_cpu_select_algorithm.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:16.083534]
2025-07-17T07:10:18.4288180Z 
2025-07-17T07:10:18.4288910Z inductor/test_cpu_select_algorithm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_select_algorithm_1.1_82113a5c3910d19f_.log
2025-07-17T07:10:18.4289420Z 
2025-07-17T07:10:18.4292960Z Running dynamo/test_cudagraphs_expandable_segments 1/1 ... [2025-07-17 07:10:18.429206]
2025-07-17T07:10:18.4293290Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:18.4296100Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_cudagraphs_expandable_segments.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:18.429497]
2025-07-17T07:10:20.2839590Z 
2025-07-17T07:10:20.2840510Z dynamo/test_cudagraphs_expandable_segments 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_expandable_segments_1.1_17fae2d3c46f3bbb_.log
2025-07-17T07:10:20.2841060Z 
2025-07-17T07:10:20.2844020Z Running inductor/test_halide 1/1 ... [2025-07-17 07:10:20.284324]
2025-07-17T07:10:20.2844440Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:20.2847160Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_halide.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:20.284608]
2025-07-17T07:10:22.5620300Z 
2025-07-17T07:10:22.5620840Z inductor/test_halide 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_halide_1.1_d8d2e19666f2c84e_.log
2025-07-17T07:10:22.5621270Z 
2025-07-17T07:10:22.5624650Z Running inductor/test_online_softmax 1/1 ... [2025-07-17 07:10:22.562368]
2025-07-17T07:10:22.5625010Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:22.5627670Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_online_softmax.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:22.562649]
2025-07-17T07:10:24.7494930Z 
2025-07-17T07:10:24.7495590Z inductor/test_online_softmax 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_online_softmax_1.1_6f51b1200d3496ea_.log
2025-07-17T07:10:24.7496060Z 
2025-07-17T07:10:24.7499310Z Running inductor/test_inplacing_pass 1/1 ... [2025-07-17 07:10:24.749841]
2025-07-17T07:10:24.7499620Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:24.7502380Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_inplacing_pass.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:24.750127]
2025-07-17T07:10:26.9710790Z 
2025-07-17T07:10:26.9711380Z inductor/test_inplacing_pass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inplacing_pass_1.1_03d99b152571d8de_.log
2025-07-17T07:10:26.9711860Z 
2025-07-17T07:10:26.9714920Z Running inductor/test_fxir_backend 1/1 ... [2025-07-17 07:10:26.971414]
2025-07-17T07:10:26.9715210Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:26.9717760Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_fxir_backend.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:26.971690]
2025-07-17T07:10:29.1825880Z 
2025-07-17T07:10:29.1826510Z inductor/test_fxir_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_fxir_backend_1.1_82067f54e97b2293_.log
2025-07-17T07:10:29.1827020Z 
2025-07-17T07:10:29.1830040Z Running inductor/test_layout_optim 1/1 ... [2025-07-17 07:10:29.182924]
2025-07-17T07:10:29.1830350Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:29.1833040Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_layout_optim.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:29.183204]
2025-07-17T07:10:31.3858500Z 
2025-07-17T07:10:31.3859120Z inductor/test_layout_optim 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_layout_optim_1.1_32496558a52c5f3f_.log
2025-07-17T07:10:31.3859590Z 
2025-07-17T07:10:31.3862970Z Running xpu/test_gemm 1/1 ... [2025-07-17 07:10:31.386192]
2025-07-17T07:10:31.3867770Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:31.3868650Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'xpu/test_gemm.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:31.386478]
2025-07-17T07:10:33.2632670Z 
2025-07-17T07:10:33.2633170Z xpu/test_gemm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/xpu.test_gemm_1.1_a62d3635b766dd07_.log
2025-07-17T07:10:33.2633630Z Running 0 items in this shard:
2025-07-17T07:10:33.2633760Z 
2025-07-17T07:10:33.2637110Z Running inductor/test_memory 1/1 ... [2025-07-17 07:10:33.263640]
2025-07-17T07:10:33.2637380Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:33.2640440Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_memory.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:33.263917]
2025-07-17T07:10:35.4702500Z 
2025-07-17T07:10:35.4703100Z inductor/test_memory 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_memory_1.1_818e5adef3830a59_.log
2025-07-17T07:10:35.4703540Z 
2025-07-17T07:10:35.4706640Z Running inductor/test_dependencies 1/1 ... [2025-07-17 07:10:35.470587]
2025-07-17T07:10:35.4706940Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:35.4709520Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_dependencies.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:35.470859]
2025-07-17T07:10:37.6942070Z 
2025-07-17T07:10:37.6942620Z inductor/test_dependencies 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_dependencies_1.1_bf60fc93da88aff3_.log
2025-07-17T07:10:37.6943100Z 
2025-07-17T07:10:37.6946360Z Running dynamo/test_python_dispatcher 1/1 ... [2025-07-17 07:10:37.694555]
2025-07-17T07:10:37.6946670Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:37.6949600Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_python_dispatcher.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:37.694847]
2025-07-17T07:10:39.6510640Z 
2025-07-17T07:10:39.6511300Z dynamo/test_python_dispatcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_python_dispatcher_1.1_161bc3a9305f1ed4_.log
2025-07-17T07:10:39.6511940Z Running 0 items in this shard:
2025-07-17T07:10:39.6512080Z 
2025-07-17T07:10:39.6515360Z Running test_pruning_op 1/1 ... [2025-07-17 07:10:39.651463]
2025-07-17T07:10:39.6515670Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:39.6518800Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_pruning_op.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:39.651776]
2025-07-17T07:10:41.4185880Z 
2025-07-17T07:10:41.4186400Z test_pruning_op 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_pruning_op_1.1_cb51e26ad751194d_.log
2025-07-17T07:10:41.4186980Z Running 0 items in this shard:
2025-07-17T07:10:41.4187120Z 
2025-07-17T07:10:41.4190810Z Running test_set_default_mobile_cpu_allocator 1/1 ... [2025-07-17 07:10:41.419001]
2025-07-17T07:10:41.4191360Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:41.4194280Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_set_default_mobile_cpu_allocator.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:41.419318]
2025-07-17T07:10:43.2035250Z 
2025-07-17T07:10:43.2036010Z test_set_default_mobile_cpu_allocator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_set_default_mobile_cpu_allocator_1.1_0cf649327b969fcd_.log
2025-07-17T07:10:43.2036820Z Running 0 items in this shard:
2025-07-17T07:10:43.2037000Z 
2025-07-17T07:10:43.2040930Z Running test_monitor 1/1 ... [2025-07-17 07:10:43.204013]
2025-07-17T07:10:43.2041260Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:43.2045200Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_monitor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:43.204377]
2025-07-17T07:10:44.9637990Z 
2025-07-17T07:10:44.9638520Z test_monitor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_monitor_1.1_838cc875f2d57e4a_.log
2025-07-17T07:10:44.9639050Z Running 0 items in this shard:
2025-07-17T07:10:44.9639200Z 
2025-07-17T07:10:44.9642840Z Running dynamo/test_verify_correctness 1/1 ... [2025-07-17 07:10:44.964209]
2025-07-17T07:10:44.9643190Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:44.9646370Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_verify_correctness.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:44.964525]
2025-07-17T07:10:46.8086650Z 
2025-07-17T07:10:46.8087340Z dynamo/test_verify_correctness 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_verify_correctness_1.1_47e25925bf1ce68d_.log
2025-07-17T07:10:46.8088040Z Running 0 items in this shard:
2025-07-17T07:10:46.8088200Z 
2025-07-17T07:10:46.8091660Z Running dynamo/test_logging 1/1 ... [2025-07-17 07:10:46.809094]
2025-07-17T07:10:46.8091990Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:46.8095370Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_logging.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:46.809417]
2025-07-17T07:10:49.1218180Z 
2025-07-17T07:10:49.1218810Z dynamo/test_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_logging_1.1_744eedd08a5ff155_.log
2025-07-17T07:10:49.1219430Z Running 0 items in this shard:
2025-07-17T07:10:49.1219590Z 
2025-07-17T07:10:49.1223400Z Running dynamo/test_package 1/1 ... [2025-07-17 07:10:49.122261]
2025-07-17T07:10:49.1223740Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:49.1227230Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_package.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:49.122614]
2025-07-17T07:10:51.4281870Z 
2025-07-17T07:10:51.4282430Z dynamo/test_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_package_1.1_6d1450e78af0345f_.log
2025-07-17T07:10:51.4283010Z Running 0 items in this shard:
2025-07-17T07:10:51.4283160Z 
2025-07-17T07:10:51.4286920Z Running dynamo/test_backends 1/1 ... [2025-07-17 07:10:51.428614]
2025-07-17T07:10:51.4287450Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:51.4290710Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_backends.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:51.428959]
2025-07-17T07:10:53.6892410Z 
2025-07-17T07:10:53.6892990Z dynamo/test_backends 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_backends_1.1_365764c9ccc9864a_.log
2025-07-17T07:10:53.6893500Z Running 0 items in this shard:
2025-07-17T07:10:53.6893630Z 
2025-07-17T07:10:53.6896780Z Running inductor/test_torchbind 1/1 ... [2025-07-17 07:10:53.689600]
2025-07-17T07:10:53.6897070Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:53.6899820Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchbind.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:53.689865]
2025-07-17T07:10:55.9760590Z 
2025-07-17T07:10:55.9761150Z inductor/test_torchbind 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchbind_1.1_66ab7de6eefc912d_.log
2025-07-17T07:10:55.9761700Z Running 0 items in this shard:
2025-07-17T07:10:55.9761840Z 
2025-07-17T07:10:55.9765430Z Running export/test_serialize 1/1 ... [2025-07-17 07:10:55.976443]
2025-07-17T07:10:55.9765720Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:55.9768070Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_serialize.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:55.976709]
2025-07-17T07:10:57.8493000Z 
2025-07-17T07:10:57.8493640Z export/test_serialize 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_serialize_1.1_dd1387d0f58cc034_.log
2025-07-17T07:10:57.8494330Z Running 0 items in this shard:
2025-07-17T07:10:57.8494490Z 
2025-07-17T07:10:57.8498230Z Running test_segment_reductions 1/1 ... [2025-07-17 07:10:57.849750]
2025-07-17T07:10:57.8498580Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:57.8501920Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_segment_reductions.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:57.850080]
2025-07-17T07:10:59.7478710Z 
2025-07-17T07:10:59.7479360Z test_segment_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_segment_reductions_1.1_3495f650471679e3_.log
2025-07-17T07:10:59.7480030Z Running 0 items in this shard:
2025-07-17T07:10:59.7480190Z 
2025-07-17T07:10:59.7484040Z Running inductor/test_auto_functionalize 1/1 ... [2025-07-17 07:10:59.748325]
2025-07-17T07:10:59.7484420Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:10:59.7487800Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_auto_functionalize.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:10:59.748666]
2025-07-17T07:11:01.6244530Z 
2025-07-17T07:11:01.6245300Z inductor/test_auto_functionalize 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_auto_functionalize_1.1_af735ac0bbcf65ac_.log
2025-07-17T07:11:01.6246080Z Running 0 items in this shard:
2025-07-17T07:11:01.6246270Z 
2025-07-17T07:11:01.6250320Z Running test_out_dtype_op 1/1 ... [2025-07-17 07:11:01.624941]
2025-07-17T07:11:01.6250680Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:01.6254130Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_out_dtype_op.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:01.625293]
2025-07-17T07:11:03.5793800Z 
2025-07-17T07:11:03.5794330Z test_out_dtype_op 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_out_dtype_op_1.1_911e909aab1b68cc_.log
2025-07-17T07:11:03.5798220Z Running 0 items in this shard:
2025-07-17T07:11:03.5798360Z 
2025-07-17T07:11:03.5798480Z Running export/test_hop 1/1 ... [2025-07-17 07:11:03.579771]
2025-07-17T07:11:03.5798760Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:03.5801610Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_hop.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:03.580051]
2025-07-17T07:11:05.9335890Z 
2025-07-17T07:11:05.9336410Z export/test_hop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_hop_1.1_4b6dbb34ef701ce6_.log
2025-07-17T07:11:05.9336920Z Running 0 items in this shard:
2025-07-17T07:11:05.9337050Z 
2025-07-17T07:11:05.9340850Z Running dynamo/test_higher_order_ops 1/1 ... [2025-07-17 07:11:05.934020]
2025-07-17T07:11:05.9341160Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:05.9344630Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_higher_order_ops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:05.934359]
2025-07-17T07:11:08.6040330Z 
2025-07-17T07:11:08.6040920Z dynamo/test_higher_order_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_higher_order_ops_1.1_40554dbad7d6b3bd_.log
2025-07-17T07:11:08.6041510Z Running 0 items in this shard:
2025-07-17T07:11:08.6041650Z 
2025-07-17T07:11:08.6045020Z Running inductor/test_efficient_conv_bn_eval 1/1 ... [2025-07-17 07:11:08.604436]
2025-07-17T07:11:08.6045350Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:08.6048490Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_efficient_conv_bn_eval.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:08.604741]
2025-07-17T07:11:10.9574810Z 
2025-07-17T07:11:10.9575470Z inductor/test_efficient_conv_bn_eval 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_efficient_conv_bn_eval_1.1_f582bcd85dc49a4c_.log
2025-07-17T07:11:10.9576040Z Running 0 items in this shard:
2025-07-17T07:11:10.9576170Z 
2025-07-17T07:11:10.9579370Z Running test_model_exports_to_core_aten 1/1 ... [2025-07-17 07:11:10.957863]
2025-07-17T07:11:10.9579670Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:10.9582600Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_model_exports_to_core_aten.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:10.958147]
2025-07-17T07:11:12.7894950Z 
2025-07-17T07:11:12.7895540Z test_model_exports_to_core_aten 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_model_exports_to_core_aten_1.1_62ddc719d171a63a_.log
2025-07-17T07:11:12.7896270Z Running 0 items in this shard:
2025-07-17T07:11:12.7896410Z 
2025-07-17T07:11:12.7899280Z Running test_mkldnn 1/1 ... [2025-07-17 07:11:12.789876]
2025-07-17T07:11:12.7899530Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:12.7902230Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_mkldnn.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:12.790137]
2025-07-17T07:11:14.6736770Z 
2025-07-17T07:11:14.6737240Z test_mkldnn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_1.1_c5ad42a7192f36b5_.log
2025-07-17T07:11:14.6737690Z Running 0 items in this shard:
2025-07-17T07:11:14.6737820Z 
2025-07-17T07:11:14.6741250Z Running torch_np/numpy_tests/lib/test_function_base 1/1 ... [2025-07-17 07:11:14.674049]
2025-07-17T07:11:14.6741650Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:14.6744090Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_function_base.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:14.674314]
2025-07-17T07:11:16.5128460Z 
2025-07-17T07:11:16.5129120Z torch_np/numpy_tests/lib/test_function_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_function_base_1.1_90616c1b6dc9e04f_.log
2025-07-17T07:11:16.5129780Z Running 0 items in this shard:
2025-07-17T07:11:16.5129910Z 
2025-07-17T07:11:16.5132960Z Running lazy/test_functionalization 1/1 ... [2025-07-17 07:11:16.513234]
2025-07-17T07:11:16.5133270Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:16.5136090Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'lazy/test_functionalization.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:16.513513]
2025-07-17T07:11:18.2991670Z 
2025-07-17T07:11:18.2992370Z lazy/test_functionalization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_functionalization_1.1_62544c9aaa6db233_.log
2025-07-17T07:11:18.2993110Z Running 0 items in this shard:
2025-07-17T07:11:18.2993280Z 
2025-07-17T07:11:18.2997110Z Running test_jit 1/1 ... [2025-07-17 07:11:18.299635]
2025-07-17T07:11:18.2997450Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:18.3001260Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_jit.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:18.300000]
2025-07-17T07:11:21.3066580Z 
2025-07-17T07:11:21.3067110Z test_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_1.1_7ad18cb9ffeb2be2_.log
2025-07-17T07:11:21.3067580Z Running 0 items in this shard:
2025-07-17T07:11:21.3067710Z 
2025-07-17T07:11:21.3071090Z Running dynamo/test_aot_autograd_cache 1/1 ... [2025-07-17 07:11:21.307027]
2025-07-17T07:11:21.3071400Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:21.3074160Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_aot_autograd_cache.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:21.307307]
2025-07-17T07:11:23.6120570Z 
2025-07-17T07:11:23.6121320Z dynamo/test_aot_autograd_cache 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_aot_autograd_cache_1.1_0987804798ec5461_.log
2025-07-17T07:11:23.6121920Z Running 0 items in this shard:
2025-07-17T07:11:23.6122060Z 
2025-07-17T07:11:23.6125210Z Running dynamo/test_einops 1/1 ... [2025-07-17 07:11:23.612465]
2025-07-17T07:11:23.6125640Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:23.6128430Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_einops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:23.612748]
2025-07-17T07:11:25.3682120Z 
2025-07-17T07:11:25.3682660Z dynamo/test_einops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_einops_1.1_74a094da7590f54a_.log
2025-07-17T07:11:25.3683220Z Running 0 items in this shard:
2025-07-17T07:11:25.3683370Z 
2025-07-17T07:11:25.3687310Z Running dynamo/test_compiler_bisector 1/1 ... [2025-07-17 07:11:25.368634]
2025-07-17T07:11:25.3687780Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:25.3690890Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_compiler_bisector.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:25.368972]
2025-07-17T07:11:27.6785700Z 
2025-07-17T07:11:27.6786340Z dynamo/test_compiler_bisector 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_compiler_bisector_1.1_4f87240ede1694d3_.log
2025-07-17T07:11:27.6786970Z Running 0 items in this shard:
2025-07-17T07:11:27.6787110Z 
2025-07-17T07:11:27.6790490Z Running test_modules 1/1 ... [2025-07-17 07:11:27.678978]
2025-07-17T07:11:27.6790790Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:27.6793960Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_modules.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:27.679294]
2025-07-17T07:11:30.6748110Z 
2025-07-17T07:11:30.6748640Z test_modules 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_modules_1.1_b2645d4e318980a4_.log
2025-07-17T07:11:30.6749210Z Running 0 items in this shard:
2025-07-17T07:11:30.6749370Z 
2025-07-17T07:11:30.6753150Z Running inductor/test_cpu_repro 1/1 ... [2025-07-17 07:11:30.675238]
2025-07-17T07:11:30.6753510Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:30.6756890Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_cpu_repro.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:30.675569]
2025-07-17T07:11:33.0040220Z 
2025-07-17T07:11:33.0040820Z inductor/test_cpu_repro 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_repro_1.1_9e34af917f158dc9_.log
2025-07-17T07:11:33.0041320Z 
2025-07-17T07:11:33.0044530Z Running optim/test_swa_utils 1/1 ... [2025-07-17 07:11:33.004369]
2025-07-17T07:11:33.0044820Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:33.0047130Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'optim/test_swa_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:33.004638]
2025-07-17T07:11:34.6662320Z 
2025-07-17T07:11:34.6662960Z optim/test_swa_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/optim.test_swa_utils_1.1_eac17174b546019c_.log
2025-07-17T07:11:34.6663400Z 
2025-07-17T07:11:34.6666810Z Running test_rename_privateuse1_to_existing_device 1/1 ... [2025-07-17 07:11:34.666573]
2025-07-17T07:11:34.6667150Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:34.6669780Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_rename_privateuse1_to_existing_device.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:34.666861]
2025-07-17T07:11:36.3768990Z 
2025-07-17T07:11:36.3769670Z test_rename_privateuse1_to_existing_device 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_rename_privateuse1_to_existing_device_1.1_86a5aba614f437f7_.log
2025-07-17T07:11:36.3770280Z Running 0 items in this shard:
2025-07-17T07:11:36.3770400Z 
2025-07-17T07:11:38.5011830Z Running inductor/test_torchinductor_dynamic_shapes 1/2 ... [2025-07-17 07:11:38.500884]
2025-07-17T07:11:38.5012550Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:38.5012800Z Running test_decomp 2/4 ... [2025-07-17 07:11:38.500927]
2025-07-17T07:11:38.5013040Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:38.5013280Z Running test_decomp 3/4 ... [2025-07-17 07:11:38.501017]
2025-07-17T07:11:38.5013520Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:11:38.5014380Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor_dynamic_shapes.py', '-m', 'not serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:38.501197]
2025-07-17T07:11:38.5015850Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_decomp.py', '-m', 'not serial', '--shard-id=2', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:38.501216]
2025-07-17T07:11:38.5017250Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_decomp.py', '-m', 'not serial', '--shard-id=3', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:11:38.501289]
2025-07-17T07:18:53.4294050Z 
2025-07-17T07:18:53.4295660Z inductor/test_torchinductor_dynamic_shapes 1/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_dynamic_shapes_1.2_7aad1269cd2578a0_.log
2025-07-17T07:18:53.4473990Z Running 451 items in this shard: test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_AllenaiLongformerBase_repro_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test__dyn_quant_matmul_4bit_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test__unsafe_masked_index_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_adaptive_avg_pool1d_argmax_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_adaptive_avg_pool2d1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_adaptive_avg_pool2d_low_prec_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_adaptive_avg_pool_with_output_size_0_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_adaptive_max_pool2d1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_adaptive_max_pool2d2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_adaptive_pool_errors_with_long_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_add_complex3_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_add_complex4_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_add_complex_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_add_const_float_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_add_const_int_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_add_inplace_permuted_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_addmm_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_addmv_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_alexnet_prefix_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_aliased_buffer_reuse_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_angle_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_any_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_aoti_eager_cache_hit_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_aoti_eager_dtype_device_layout_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_aoti_eager_with_persistent_cache_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_arange2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_arange5_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_arange6_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_argmax_argmin1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_argmax_argmin2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_argmax_argmin_with_duplicates_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_argmax_argmin_with_nan_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_argmax_min_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_argmax_to_float_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_avg_pool2d1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_avg_pool2d4_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_avg_pool2d8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_avg_pool2d_backward2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_avg_pool2d_backward_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_avg_pool3d_backward2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_avg_pool3d_backward3_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_avg_pool3d_backward4_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_avg_pool_errors_with_uint_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_batch_norm_2d_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bernoulli1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bitwise2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bitwise_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bmm2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_broadcast_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int16_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int16_int64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int16_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int16_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int32_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int64_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int64_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int64_int64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int64_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int8_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int8_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int8_int64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int8_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_int8_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_uint8_int64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_bucketize_int_uint8_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_buffer_copied_in_graph_with_different_shapes_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_buffer_use_after_remove_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_builtins_round_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_builtins_round_float_ndigits_zero_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_builtins_round_int_ndigits_pos_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_builtins_round_int_ndigits_zero_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_cat_empty_index_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_cat_inplace_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_cat_negative_dim_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_cat_of_loops_and_extern_kernel_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_cat_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_cat_unbacked_2d_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_cat_upcasting_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_chunk_recompiles_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_clamp_type_promotion_non_tensor_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_clone_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_compar_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_complex_memory_overlap_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_config_option_dont_assume_alignment_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_consecutive_split_cumprod_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_consecutive_split_cumsum_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_constant_pad_1d_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_constant_pad_fill_dtype_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_constant_pad_float64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_conv2d_backward_channels_last_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_conv3d_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_conv_bn_fuse_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_conv_shape_check_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_conv_with_as_strided_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_convolution5_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_cudnn_rnn_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_cummin_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_custom_op_1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_custom_op_2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_custom_op_3_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_custom_op_default_layout_constraint_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_custom_scan_op_compiled_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_custom_scan_op_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_custom_scan_would_split_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_data_type_propogation_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dense_mask_index_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_deterministic_codegen_on_graph_break_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_deterministic_codegen_with_suffix_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_device_assert_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_diagonal_copy_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dist_bf16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dist_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_div1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_div2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_div4_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_div7_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_div8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_div9_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_div_precision_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_div_softmax_symfloat_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_div_zero_dim_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dont_constant_fold_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dropout_deterministic_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dropout_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_bfloat16_float16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_bfloat16_int64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_bfloat16_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float16_bfloat16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float16_float16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float16_float32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float16_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float16_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float16_int64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float16_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float16_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float32_bfloat16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float32_float16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float32_float64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float32_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float64_float64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float64_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float64_int64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_float64_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int16_bfloat16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int16_float16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int16_float32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int16_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int16_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int16_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int32_float16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int32_float64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int32_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int32_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int64_bfloat16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int64_int16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int64_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int64_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int8_bfloat16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int8_float16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int8_float32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int8_float64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int8_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_int8_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_uint8_float16_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_uint8_float32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_uint8_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_dtypeview_uint8_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_embedding_bag_byte_unpack_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_embedding_bag_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_embedding_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_empty_strided_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_erfinv_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_exp_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_expanded_reduction_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_fallback_mutable_op_basic_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_fallback_mutable_op_list_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_fill2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_float32_to_int32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_float_index_expression_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_float_index_expression_type_promotion_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_floordiv_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_fmin_fmax_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_fmod_zero_dim_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_fractional_max_pool2d1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_fractional_max_pool2d2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_fractional_max_pool2d4_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_full_like_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_full_truncation_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_functionalize_rng_wrappers_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_fusing_write_into_disjoint_read_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_gather1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_gather2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_gelu_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_generated_code_has_alignment_assert_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_graph_partition_argmax_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_graph_partition_constant_tensor1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_graph_partition_misaligned_input_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_graph_partition_mutation_real_name_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_graph_partition_no_inputs_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_graph_partition_pad_dynamic_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_graph_partition_scalar_inputs_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_graph_partition_unbacked_symint_as_output_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_hardsigmoid_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_hardswish_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_horizonal_fusion2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index_dynamic_shapes_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index_propagation_device_assert_masked_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index_propagation_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index_propagation_flip_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index_propagation_nested_indirect_indexing_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index_put1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index_put3_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index_put_deterministic_fallback_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index_put_index_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index_remainder_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index_select_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_index_tensor_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_inductor_multiple_specializations_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_inplace_activations_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_inplace_resize_as_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_input_mutation2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_input_mutation4_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_int_input_dynamic_shapes_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_invalid_operand_issue1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_issue102546_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_large_grid_use_block_ptr_True_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_large_offset_pointwise_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_layer_norm_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_leaky_relu_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_lerp_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_lgamma_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_like_channels_last_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_like_rands_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_linear_float64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_linear_mixed_dtype_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_linspace1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_linspace2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_log1p_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_log_softmax_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_logaddexp_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_logcumsumexp_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_logcumsumexp_zero_dim_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_logsumexp_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_low_memory_max_pool_dilation_1_dim_2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_low_memory_max_pool_dilation_2_dim_2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_low_memory_max_pool_dilation_2_dim_3_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_masked_fill_promotion_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_masked_scatter_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_max_min_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_max_pool2d1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_max_pool2d3_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_max_pool2d4_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_max_pool2d6_dilation_2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_max_pool2d7_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_max_pool2d_with_indices_backward2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_max_pool2d_with_indices_backward3_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_max_pool2d_with_indices_backward4_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_max_pool2d_with_indices_backward6_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_min_max_reduction_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_misaligned_address_issue1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_mixed_mm2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_mixed_mm3_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_mm_mixed_dtype_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_mm_views_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_mul_softmax_symfloat_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_multi_gpu_device_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_multi_threading_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_multilayer_var_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_multilayer_var_lowp_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_mutable_custom_op_fixed_layout_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_mutations_loop_fusion_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_needs_contiguous_strides_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_neg_index_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_nll_loss_forward_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pad_single_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pattern_matcher_multi_user_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_permute2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_philox_rand_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_bessel_j0_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_bessel_j1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_bessel_y0_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_chebyshev_polynomial_v_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_erfc_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_erfcx_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_erfinv_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_gammainc_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_hermite_polynomial_h_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_hermite_polynomial_he_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_laguerre_polynomial_l_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_legendre_polynomial_p_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_log1p_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_log_ndtr_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_logit_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_modified_bessel_i0_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_modified_bessel_i1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_modified_bessel_k1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_multigammaln_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_ndtri_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_polygamma_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_round_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_scaled_modified_bessel_k1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_shifted_chebyshev_polynomial_u_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_shifted_chebyshev_polynomial_w_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_sinc_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_xlog1py_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pointwise_zeta_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_polar_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pow3_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pow_int_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_pow_symfloat_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_prepare_softmax_with_fast_math_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_profiler_mark_wrapper_call_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_rand_like_deterministic_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_randn_like_empty_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_randn_with_dtype_and_device_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_reduction1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_reduction2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_reduction4_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_reinterpret_dtypeview_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_remainder_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_remove_no_ops_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_remove_noop_clone_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_remove_noop_copy_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_remove_noop_view_default_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_repeat_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_repeat_interleave_2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_repeat_interleave_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_replication_pad_errors_with_bool_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_require_stride_expanded_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_resize_as_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_reuse_buffers_with_aliasing_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_round_correctness_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_round_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_scalar_input_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_scalar_output_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_scaled_dot_product_attention_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_scaled_dot_product_efficient_attention_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_scatter4_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_scatter5_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_scatter_add1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_scatter_add2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_scatter_reduce1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_scatter_reduce2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_scatter_reduce3_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sdpa_prefer_nd_tiling_True_use_block_ptr_False_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sdpa_prefer_nd_tiling_True_use_block_ptr_True_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sdpa_unaligned_mask_freezing_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_searchsorted_broadcast_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sgn_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sgn_extremal_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_shape_prop_torch_ones_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_should_pad_bench_for_bmm_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sign_dtype_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sin_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_single_elem_indirect_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_size_asserts_for_multi_output_fallback_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_slice4_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_slice_mutation1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_slice_mutation2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_slice_scatter3_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_slice_scatter5_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_slice_scatter_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_softmax_backward_data_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sort_bool_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sort_stable_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_special_polygamma_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_split_cumsum_index_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_split_cumsum_low_prec_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_split_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_split_failed_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_split_with_integer_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_split_with_unbacked_symints_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sqrt_dynamic_shapes_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_squeeze1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_squeeze2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_squeeze_varargs_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_stack_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_std_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_stride_preservation_with_stride_modifying_fx_pass_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_strided_inputs_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sum1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sum4_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sum_dtype_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_sum_keepdims_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_tanh_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_tensor2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_tmp_not_defined_issue3_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_to_device_constant_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_topk_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_transpose_add_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_transposed_propagates_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_uint_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_unbacked_floordiv_simplify_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_unspec_inputs_float32_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_unspec_inputs_int64_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_unspec_inputs_int8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_unspec_inputs_uint8_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_unsqueeze_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_unsqueeze_inplace_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_upsample_bilinear2d_a_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_upsample_cat_conv_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_upsample_nearest2d_backward_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_var_mean_tile_reduction_False_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_vdd_clamp_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_vectorized_ops_masked_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_vectorized_ops_masked_var_novec_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_vertical_fusion1_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_view_on_aliased_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_view_uint8_through_differing_bitwidths_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_views2_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_views5_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_views7_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_where_broadcast_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_xblock_divides_xnumel_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::DynamicShapesCpuTests::test_zero_dim_reductions_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_abs_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_arange_dynamic_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_arithmetic_constant_folding_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_constant_fold_uniform_value_dynamic_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_float_item_neginf_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_float_item_return_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_full_recompiles_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_full_symbolic_value_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_interpolate_ceil_eq_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_item_bool_nobreak_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_item_nobreak_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_item_to_inputs_kernel_nobreak_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_item_unbacked_stride_nobreak_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_item_zeros_nobreak_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_mark_unbacked_slice_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_math_ops_op10_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_math_ops_op1_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_math_ops_op4_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_math_ops_op5_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_math_ops_op6_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_math_ops_op7_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_math_ops_op8_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_math_ops_op9_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_meta_dynamic_shapes_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_multi_output_unbacked_custom_op_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_noops_tensor_repropagate_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_slice_scatter_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_symint_sum_list_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_unbacked_cat_backwards_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_unbacked_index_select_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_unbacked_matmul_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_unbacked_reduction_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_unspecialized_float_operations_cpu, test/inductor/test_torchinductor_dynamic_shapes.py::TestInductorDynamicCPU::test_unspecialized_float_softshrink_cpu
2025-07-17T07:18:53.4610350Z 
2025-07-17T07:18:55.4809840Z Running test_decomp 4/4 ... [2025-07-17 07:18:55.480802]
2025-07-17T07:18:55.4810560Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:18:55.4812630Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_decomp.py', '-m', 'not serial', '--shard-id=4', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:18:55.481083]
2025-07-17T07:20:27.8224040Z 
2025-07-17T07:20:27.8224700Z test_decomp 2/4 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_2.4_f57d76c5f51334c4_.log
2025-07-17T07:20:27.8652450Z Running 2281 items in this shard: test/test_decomp.py::TestDecompCPU::test_bernoulli_default_cpu, test/test_decomp.py::TestDecompCPU::test_cat_single_input_cpu, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmod___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive__native_batch_norm_legit_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__native_batch_norm_legit_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_lengths_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_offsets_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_offsets_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_int64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_argwhere_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_partial_views_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_partial_views_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_partial_views_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_partial_views_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_partial_views_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_scatter_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_scatter_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_asin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_asin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_asin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_asinh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_asinh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_asinh_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_block_diag_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_block_diag_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_block_diag_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_block_diag_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_bmm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_bmm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_bmm_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_bool_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_bool_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_bool_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_bool_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_bool_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_broadcast_tensors_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_broadcast_tensors_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_broadcast_tensors_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_broadcast_to_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_broadcast_to_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_broadcast_to_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_broadcast_to_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_broadcast_to_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_bucketize_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_bucketize_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_bucketize_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_bucketize_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_byte_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_byte_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_byte_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cartesian_prod_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cartesian_prod_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cartesian_prod_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_cat_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cauchy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cauchy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cdist_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cdist_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cdouble_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_cdouble_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_cdouble_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cdouble_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_ceil_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_ceil_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_ceil_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_ceil_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_cfloat_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cfloat_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cfloat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_chalf_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_char_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_char_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_cholesky_solve_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_cholesky_solve_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_chunk_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_chunk_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_chunk_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_chunk_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_max_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_min_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_clone_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_clone_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_clone_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_clone_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_clone_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_clone_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_column_stack_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_column_stack_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_column_stack_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_column_stack_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_column_stack_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_combinations_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_conj_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_conj_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_conj_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_conj_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_conj_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_conj_physical_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_conj_physical_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_constant_pad_nd_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_constant_pad_nd_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_constant_pad_nd_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_constant_pad_nd_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_contiguous_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_contiguous_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_contiguous_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_copysign_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_corrcoef_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_corrcoef_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cos_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cos_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cosh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_cosh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_cosh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cosh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cosh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_count_nonzero_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_count_nonzero_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_count_nonzero_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cov_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cov_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_cov_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cov_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cov_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cov_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_cross_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cross_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cummax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cummax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cummin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumprod_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumsum_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumsum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumsum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumulative_trapezoid_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumulative_trapezoid_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumulative_trapezoid_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumulative_trapezoid_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_deg2rad_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_deg2rad_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_deg2rad_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_deg2rad_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_deg2rad_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_deg2rad_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_diag_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_diag_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_diag_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_diag_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_diag_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_diag_embed_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagflat_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagflat_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagflat_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_scatter_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_scatter_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_scatter_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_diff_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_diff_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_diff_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_diff_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_digamma_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_digamma_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_digamma_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_digamma_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_dist_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_dist_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_floor_rounding_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_no_rounding_mode_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_no_rounding_mode_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_no_rounding_mode_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_no_rounding_mode_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_trunc_rounding_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_trunc_rounding_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_dot_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_dot_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_dot_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_dot_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_dot_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_double_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_double_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_double_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_double_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_double_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_double_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_double_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_dsplit_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_dsplit_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_dsplit_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_dsplit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_dsplit_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_dstack_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_dstack_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_dstack_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_einsum_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_einsum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_einsum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_like_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_like_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_like_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_like_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_like_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_permuted_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_permuted_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_permuted_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_strided_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_strided_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_strided_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_eq_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_eq_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_equal_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_equal_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_erf_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_erf_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_erf_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_erfc_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_erfc_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_erfc_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_erfinv_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_erfinv_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_exp2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_exp2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_exp2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_exp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_exp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_as_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_as_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_exponential_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_exponential_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftn_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftn_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftshift_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftshift_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftshift_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftshift_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftshift_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfft2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfft_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftn_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fill_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fill_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fill_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_flatten_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_flatten_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_flip_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_flip_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_flip_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fliplr_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fliplr_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fliplr_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fliplr_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_flipud_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_flipud_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_power_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_power_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_power_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_floor_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_floor_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_floor_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_floor_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_floor_divide_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmax_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmod_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmod_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmod_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_frac_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_frexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_full_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_full_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_full_like_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_full_like_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_full_like_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_full_like_cpu_uint32, test/test_decomp.py::TestDecompCPU::test_comprehensive_gather_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_gather_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_geometric_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_geqrf_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_geqrf_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_gradient_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_gradient_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_gradient_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_gradient_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_gradient_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_gradient_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_grid_sampler_2d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_gt_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_gt_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_gt_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_gt_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_half_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_half_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_heaviside_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_heaviside_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_heaviside_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_histc_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_histc_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_histogram_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_hsplit_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_hsplit_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_hsplit_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_hstack_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_hstack_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_i0_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_igamma_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_igammac_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_igammac_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_imag_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_add_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_add_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_add_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_add_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_fill_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_fill_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_fill_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_fill_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_put_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_put_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_amax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_amax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_amax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_amin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_amin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_amin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_mean_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_prod_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_prod_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_prod_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_prod_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_select_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_select_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_select_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_select_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_int_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_int_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_int_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_isclose_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_isclose_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_isfinite_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_isin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_isinf_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_isinf_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_isinf_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_isinf_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_isinf_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_isnan_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_isnan_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_isneginf_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_isneginf_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_isposinf_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_isreal_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_isreal_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_isreal_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_isreal_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_isreal_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_item_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_item_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_item_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_item_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_item_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_item_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_2inputs_2outputs_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_2inputs_2outputs_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_2inputs_2outputs_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_4inputs_with_extra_args_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_4inputs_with_extra_args_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_4inputs_with_extra_args_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_4inputs_with_extra_args_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_binary_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_binary_cpu_complex64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_lcm_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_ldexp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_ldexp_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_ldexp_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_ldexp_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_le_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_le_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_lerp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_lgamma_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_lgamma_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_lgamma_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cholesky_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cond_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cross_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cross_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cross_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cross_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_det_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_diagonal_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_diagonal_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eig_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eig_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eigh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eigvals_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eigvalsh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_householder_product_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_inv_ex_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_inv_ex_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_solve_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_solve_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_grad_oriented_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_ex_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_hermitian_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_hermitian_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_multi_dot_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_multi_dot_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_multi_dot_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_norm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_norm_subgradients_at_zero_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_norm_subgradients_at_zero_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_norm_subgradients_at_zero_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_singular_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_singular_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_slogdet_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_solve_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_solve_triangular_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_solve_triangular_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_svdvals_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorinv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorinv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorsolve_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vecdot_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_log2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_log2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_log2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_log2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_log_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_log_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_log_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_log_normal_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log_normal_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_log_softmax_with_dtype_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_log_softmax_with_dtype_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_log_softmax_with_dtype_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_log_softmax_with_dtype_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_log_softmax_with_dtype_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_logaddexp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_logaddexp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_logcumsumexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_logdet_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_logdet_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_and_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_and_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_and_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_and_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_and_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_not_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_not_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_not_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_or_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_or_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_xor_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_logit_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_logit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_logit_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_logit_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_logspace_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_logspace_tensor_overload_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_logspace_tensor_overload_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_logspace_tensor_overload_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_logsumexp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_logsumexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_logsumexp_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_long_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_long_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_long_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_long_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_lt_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_lt_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_lt_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_lu_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_lu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_lu_solve_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_lu_unpack_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_mH_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_mH_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_mH_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_mH_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_mH_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_mT_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_mT_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_mT_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_mT_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_amax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_amin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_amin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_amin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_amin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumprod_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumsum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumsum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_fill_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_fill_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_logaddexp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_logsumexp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_logsumexp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_normalize_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_normalize_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_prod_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_prod_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_scatter_cpu_complex64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_mean_unbiased_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_mean_unbiased_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_unbiased_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_vdot_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vdot_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_complex_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_complex_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_int8, test/test_decomp.py::TestDecompCPU::test_masked_fill_cpu, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick__softmax_backward_data_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick__upsample_bilinear2d_aa_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__upsample_bilinear2d_aa_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bernoulli_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_bernoulli_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_complex_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward__unsafe_masked_index_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_addr_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_alias_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_deg2rad_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_diag_embed_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_frac_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_index_fill_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_lerp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_logaddexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_logsumexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_masked_fill_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_mv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_nan_to_num_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_nn_functional_max_unpool2d_grad_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_nn_functional_max_unpool3d_grad_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_roll_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_rot90_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_sinc_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_split_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_split_with_sizes_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_std_mean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_std_mean_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_t_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_tril_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_unbind_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_unfold_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_cos_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_cos_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_cos_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_cos_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_cosh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_count_nonzero_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_count_nonzero_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_count_nonzero_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_cumprod_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_cumprod_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_cumprod_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_cumsum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_deg2rad_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_deg2rad_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_deg2rad_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_diag_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_diag_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_diag_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_diag_embed_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_diag_embed_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_diag_embed_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_diag_embed_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_diag_embed_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_dist_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_exponential_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_exponential_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float8_e4m3fn, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float8_e4m3fnuz, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float8_e5m2, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfftn_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfft2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_frexp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_frexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_gcd_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_grid_sampler_2d_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_grid_sampler_2d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_hypot_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_igammac_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_isneginf_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_isneginf_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_isneginf_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_isposinf_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_native_batch_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_native_layer_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_nextafter_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_elu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_embedding_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_gelu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_glu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_glu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardshrink_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardshrink_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardswish_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardswish_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_huber_loss_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_huber_loss_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_leaky_relu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_logsigmoid_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_logsigmoid_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_grad_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_grad_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mse_loss_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_prelu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_softplus_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_softshrink_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_norm_inf_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_norm_inf_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_norm_nuc_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_norm_nuc_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_normal_in_place_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_normal_number_mean_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_permute_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_permute_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_permute_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_permute_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_pow_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_pow_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_prod_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_prod_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_randn_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_renorm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_round_decimals_0_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_round_decimals_0_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_round_decimals_3_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_sinh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_sinh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sinh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_sinh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_sinh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_slice_scatter_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_slice_scatter_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_slice_scatter_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_slice_scatter_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_slice_scatter_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_special_entr_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_special_erfcx_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_special_erfcx_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_special_erfcx_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_special_erfcx_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_special_erfcx_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_special_i0e_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_special_i1_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_special_i1_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_special_i1e_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_special_i1e_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_special_i1e_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_special_i1e_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_special_i1e_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_special_log_ndtr_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_special_log_ndtr_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtr_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtri_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtri_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_special_xlog1py_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_special_xlog1py_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_special_xlog1py_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_special_xlog1py_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_special_zeta_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_special_zeta_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_std_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_unbiased_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_unbiased_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_unbiased_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_std_unbiased_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_std_unbiased_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_triu_indices_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_int64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_GRU_eval_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_GRU_train_mode_cpu_float64, test/test_decomp.py::DecompOneOffTestsCPU::test_threshold_backward_dtype_cpu, test/test_decomp.py::HasDecompTest::test_has_decomposition
2025-07-17T07:20:27.9063060Z 
2025-07-17T07:20:29.7598390Z Running inductor/test_triton_extension_backend 1/1 ... [2025-07-17 07:20:29.759642]
2025-07-17T07:20:29.7599280Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:20:29.7601530Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_triton_extension_backend.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:20:29.759925]
2025-07-17T07:20:32.2396320Z 
2025-07-17T07:20:32.2397890Z inductor/test_triton_extension_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_triton_extension_backend_1.1_cb5a75469d61015b_.log
2025-07-17T07:20:32.2398900Z 
2025-07-17T07:20:34.2142000Z Running inductor/test_extension_backend 1/1 ... [2025-07-17 07:20:34.213986]
2025-07-17T07:20:34.2143610Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:20:34.2145830Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_extension_backend.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:20:34.214319]
2025-07-17T07:20:34.7532940Z 
2025-07-17T07:20:34.7533460Z test_decomp 3/4 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_3.4_ee1cb4877af11fa7_.log
2025-07-17T07:20:34.7962700Z Running 2267 items in this shard: test/test_decomp.py::TestDecompCPU::test_arange_graph_cpu, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmod___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmod___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive__batch_norm_with_update_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_offsets_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__softmax_backward_data_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__softmax_backward_data_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive__softmax_backward_data_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive__upsample_bilinear2d_aa_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_abs_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_acos_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_acosh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcdiv_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcdiv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addr_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_allclose_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_allclose_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_amax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_aminmax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_aminmax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_angle_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_arange_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_arange_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_argwhere_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argwhere_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_argwhere_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_argwhere_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_partial_views_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_partial_views_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_partial_views_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_partial_views_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_partial_views_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_scatter_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_scatter_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_scatter_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_scatter_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_scatter_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_scatter_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_scatter_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_asin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_asin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_asin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_asinh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_atan2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_atan2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_atan2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_atan_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_atan_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_atanh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_atanh_cpu_complex64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_ceil_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_cfloat_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_chalf_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_chalf_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_chalf_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_chalf_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_chalf_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_char_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_char_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_char_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cholesky_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cholesky_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_chunk_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_chunk_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_chunk_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_max_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_max_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_max_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_min_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_clamp_min_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_clone_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_clone_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_column_stack_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_combinations_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_combinations_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_combinations_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_combinations_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_combinations_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_complex_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_conj_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_conj_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_conj_physical_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_conj_physical_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_constant_pad_nd_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_constant_pad_nd_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_constant_pad_nd_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_constant_pad_nd_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_constant_pad_nd_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_contiguous_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_contiguous_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_contiguous_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_copysign_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_copysign_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_copysign_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_corrcoef_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_corrcoef_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_cos_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cos_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_cosh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_count_nonzero_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_count_nonzero_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_count_nonzero_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_cov_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cov_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cov_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cross_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_cummax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cummax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_cummin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cummin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cummin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cummin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumprod_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumprod_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumprod_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumsum_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumsum_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumsum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumsum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumsum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumsum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumulative_trapezoid_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cumulative_trapezoid_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_deg2rad_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_deg2rad_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_diag_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_diag_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_diag_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_diag_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_diag_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_diag_embed_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_diag_embed_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagflat_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagflat_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagflat_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagflat_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagflat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagflat_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_scatter_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_scatter_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_diagonal_scatter_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_diff_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_diff_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_diff_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_dist_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_dist_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_dist_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_floor_rounding_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_floor_rounding_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_no_rounding_mode_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_no_rounding_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_no_rounding_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_no_rounding_mode_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_trunc_rounding_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_trunc_rounding_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_trunc_rounding_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_div_trunc_rounding_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_double_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_dsplit_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_dsplit_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_dsplit_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_dstack_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_dstack_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_dstack_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_einsum_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_einsum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_einsum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_einsum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_like_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_permuted_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_permuted_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_permuted_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_strided_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_strided_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_strided_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_empty_strided_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_eq_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_eq_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_eq_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_eq_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_equal_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_equal_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_equal_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_equal_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_equal_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_equal_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_erf_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_erf_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_erf_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_erf_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_erfc_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_erfc_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_exp2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_exp2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_exp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_exp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_exp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_exp_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_as_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_as_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_as_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_expand_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_exponential_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_float8_e4m3fn, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_float8_e5m2, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_float8_e5m2fnuz, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftshift_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftshift_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfft_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfft_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfftn_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_hfftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifftshift_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fill_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fill_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fill_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fill_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_flatten_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_flatten_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_flatten_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_flatten_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_flip_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_flip_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_flip_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_flip_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_flip_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fliplr_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fliplr_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fliplr_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_flipud_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_flipud_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_power_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_floor_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_floor_divide_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_floor_divide_cpu_float64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_gradient_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_grid_sampler_2d_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_grid_sampler_2d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_half_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_half_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_half_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_heaviside_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_heaviside_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_heaviside_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_histc_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_histogram_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_histogramdd_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_hsplit_cpu_complex32, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_int_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_int_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_isclose_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_isclose_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_isclose_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_isclose_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_isclose_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_isfinite_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_isfinite_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_isfinite_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_isfinite_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_isin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_isinf_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_isinf_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_isnan_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_isnan_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_isnan_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_isnan_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_isnan_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_isneginf_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_isneginf_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_isneginf_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_isposinf_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_isposinf_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_isreal_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_isreal_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_isreal_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_istft_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_item_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_item_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_item_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_2inputs_2outputs_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_2inputs_2outputs_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_2inputs_2outputs_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_2inputs_2outputs_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_2inputs_2outputs_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_4inputs_with_extra_args_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_binary_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_binary_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_binary_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_binary_return_by_ref_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_binary_return_by_ref_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_unary_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_unary_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_unary_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_unary_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_kron_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_kron_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_kron_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_kron_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_kthvalue_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_kthvalue_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_kthvalue_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_lcm_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_ldexp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_ldexp_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_ldexp_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_le_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_le_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_lerp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_lgamma_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_lgamma_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_lgamma_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cholesky_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cholesky_ex_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cond_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cond_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cross_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cross_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cross_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_diagonal_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_diagonal_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eig_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eigvals_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eigvals_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eigvalsh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_householder_product_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_householder_product_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_householder_product_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_inv_ex_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_factor_ex_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_ldl_solve_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_grad_oriented_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lstsq_grad_oriented_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_ex_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_ex_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_power_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_power_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_multi_dot_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_multi_dot_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_multi_dot_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_norm_subgradients_at_zero_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_norm_subgradients_at_zero_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_hermitian_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_singular_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_qr_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_qr_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_svd_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorsolve_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vecdot_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vector_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vector_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vector_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_tensor_overload_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_log2_cpu_bool, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_logaddexp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_logcumsumexp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_not_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_not_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_or_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_or_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_or_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_xor_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_xor_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_xor_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_logit_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_logspace_cpu_int16, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_matmul_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_matrix_exp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_matrix_exp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_binary_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_pool2d_with_indices_backward_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_no_dim_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_maximum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_maximum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_median_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_meshgrid_list_of_tensors_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_meshgrid_list_of_tensors_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_meshgrid_list_of_tensors_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_meshgrid_list_of_tensors_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_meshgrid_variadic_tensors_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_binary_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_binary_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_binary_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_no_dim_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_no_dim_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_no_dim_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_with_dim_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_with_dim_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_minimum_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_minimum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_minimum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_minimum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_minimum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_mm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_mm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_mm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_mm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_mm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_mm_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_mode_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_mode_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_movedim_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_movedim_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_movedim_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_movedim_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_msort_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_msort_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_msort_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_mul_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_mul_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_multinomial_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_multinomial_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_multinomial_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_mv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_mvlgamma_mvlgamma_p_1_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_mvlgamma_mvlgamma_p_1_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_mvlgamma_mvlgamma_p_3_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_mvlgamma_mvlgamma_p_3_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_mvlgamma_mvlgamma_p_3_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_mvlgamma_mvlgamma_p_5_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_nan_to_num_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nan_to_num_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nan_to_num_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nan_to_num_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmedian_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nanmedian_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_nansum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nansum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nansum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nansum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_narrow_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_narrow_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_narrow_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_native_batch_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_native_dropout_backward_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_native_dropout_backward_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_native_dropout_backward_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_native_dropout_backward_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_native_layer_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_native_layer_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_ne_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_ne_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_neg_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_neg_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_empty_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_empty_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_empty_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_empty_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_empty_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_empty_strided_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_empty_strided_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_empty_strided_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_empty_strided_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_empty_strided_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_full_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_ones_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_ones_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_ones_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_zeros_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_zeros_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_new_zeros_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nextafter_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_adaptive_avg_pool2d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_adaptive_max_pool2d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_alpha_dropout_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_avg_pool1d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_avg_pool3d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_avg_pool3d_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_batch_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_batch_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_bilinear_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_bilinear_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_bilinear_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_binary_cross_entropy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_binary_cross_entropy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_binary_cross_entropy_with_logits_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_binary_cross_entropy_with_logits_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_channel_shuffle_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_channel_shuffle_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_channel_shuffle_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_conv_transpose3d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_cross_entropy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_dropout3d_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_dropout3d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_dropout_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_elu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_embedding_bag_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_embedding_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_feature_alpha_dropout_with_train_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_feature_alpha_dropout_with_train_cpu_float32, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_take_along_dim_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_take_along_dim_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_take_along_dim_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_take_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_take_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_take_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_tan_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_tan_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_tan_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_tan_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_tanh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_tanh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_tanh_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_tanh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_tanh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_tanh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_tanh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_tanh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_tanh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_tensor_split_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_tensor_split_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_tensor_split_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_tensordot_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_tensordot_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_tile_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_tile_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_tile_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_tile_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_tile_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_tile_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_to_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_to_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_to_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_to_sparse_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_to_sparse_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_to_sparse_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_to_sparse_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_topk_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_topk_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_topk_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_topk_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_torch__scaled_mm_cpu_float8_e5m2fnuz, test/test_decomp.py::TestDecompCPU::test_comprehensive_torch_ops_aten__safe_softmax_default_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_torch_ops_aten__safe_softmax_default_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_torch_ops_aten__safe_softmax_default_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_trace_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_trace_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_transpose_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_transpose_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_transpose_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_transpose_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_transpose_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_transpose_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_transpose_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_trapezoid_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_trapz_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_tril_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_tril_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_tril_indices_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_triu_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_triu_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_triu_indices_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_triu_indices_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_trunc_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_trunc_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_trunc_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_trunc_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_unbind_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unbind_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unbind_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_unbind_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unbind_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unflatten_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unflatten_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unflatten_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unfold_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unfold_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unfold_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_unfold_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_unfold_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_unfold_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unfold_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unfold_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_uniform_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_consecutive_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_consecutive_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_consecutive_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_cpu_uint32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unravel_index_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unravel_index_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unravel_index_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_chunk_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_chunk_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_chunk_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_mean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_mean_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_mean_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_mean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_mean_unbiased_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_unbiased_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_unbiased_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vdot_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_real_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick__native_batch_norm_legit_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__native_batch_norm_legit_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_asinh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_cauchy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_complex_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_core_backward__unsafe_masked_index_put_accumulate_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_bernoulli_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_fill_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_nn_functional_binary_cross_entropy_with_logits_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_nn_functional_hardshrink_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_select_scatter_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_special_entr_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_special_log_ndtr_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_take_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_trace_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_zero__cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_cos_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_cos_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_cos_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_cos_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_cos_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_cos_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_cosh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_cosh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_cosh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_cosh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_cosh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_count_nonzero_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_cumprod_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_cumprod_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_cumsum_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_cumsum_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_cumsum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_cumsum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_deg2rad_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_deg2rad_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_deg2rad_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_deg2rad_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_deg2rad_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_diag_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_diag_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_diag_embed_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_diag_embed_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_diag_embed_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_diag_embed_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_diag_embed_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_diag_embed_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_floor_divide_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_frac_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_frexp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_gcd_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_grid_sampler_2d_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_igammac_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_isneginf_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_isneginf_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_isneginf_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_isposinf_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_isposinf_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_isposinf_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_log_normal_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log_normal_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log_softmax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log_softmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_int32, 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test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_native_batch_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_nextafter_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_with_logits_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_elu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_embedding_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_embedding_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_gelu_cpu_float32, 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test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mish_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mish_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mish_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mse_loss_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mse_loss_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_prelu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_prelu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_prelu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu6_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu_cpu_int32, 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test/test_decomp.py::TestDecompCPU::test_quick_norm_inf_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_norm_inf_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_norm_nuc_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_norm_nuc_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_normal_in_place_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_normal_number_mean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_permute_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_permute_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_permute_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_pow_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_pow_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_pow_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_pow_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_pow_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_prod_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_prod_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_randn_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_renorm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_int64, 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test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sign_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sinh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sinh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sinh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_slice_scatter_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_softmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_softmax_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_softmax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_softmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_special_entr_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_special_entr_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_special_entr_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_special_entr_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_special_erfcx_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_special_erfcx_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_special_i0e_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_special_i0e_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_special_i0e_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_special_i0e_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_special_i0e_cpu_int32, 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test/test_decomp.py::TestDecompCPU::test_quick_special_ndtri_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtri_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_special_xlog1py_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_special_zeta_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_special_zeta_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_special_zeta_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_special_zeta_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_complex128, 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test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_std_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_std_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_std_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_int32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_LSTM_train_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_LSTM_train_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_RNN_eval_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_RNN_eval_mode_cpu_float64, test/test_decomp.py::DecompOneOffTestsCPU::test_weight_norm_interface_cpu, test/test_decomp.py::HasDecompTest::test_aten_core_operators
2025-07-17T07:20:34.8375150Z 
2025-07-17T07:20:36.7641390Z Running inductor/test_kernel_benchmark 1/1 ... [2025-07-17 07:20:36.763924]
2025-07-17T07:20:36.7642210Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:20:36.7644970Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_kernel_benchmark.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:20:36.764254]
2025-07-17T07:20:36.9748180Z 
2025-07-17T07:20:36.9768710Z inductor/test_extension_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_extension_backend_1.1_089563949d27aaf3_.log
2025-07-17T07:20:36.9770330Z 
2025-07-17T07:20:39.0526460Z Running inductor/test_cpu_cpp_wrapper 1/1 ... [2025-07-17 07:20:39.052406]
2025-07-17T07:20:39.0527280Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:20:39.0530040Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_cpu_cpp_wrapper.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:20:39.052793]
2025-07-17T07:20:39.4980690Z 
2025-07-17T07:20:39.4982610Z inductor/test_kernel_benchmark 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_kernel_benchmark_1.1_e56c322e732898ce_.log
2025-07-17T07:20:39.4984820Z 
2025-07-17T07:20:41.4851530Z Running inductor/test_torchinductor_strided_blocks 1/1 ... [2025-07-17 07:20:41.484949]
2025-07-17T07:20:41.4852470Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:20:41.4855130Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor_strided_blocks.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:20:41.485294]
2025-07-17T07:20:42.1580790Z 
2025-07-17T07:20:42.1581400Z inductor/test_cpu_cpp_wrapper 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_cpp_wrapper_1.1_fbc6f46436b7c460_.log
2025-07-17T07:20:42.1581880Z 
2025-07-17T07:20:44.1667480Z Running inductor/test_pad_mm 1/1 ... [2025-07-17 07:20:44.166562]
2025-07-17T07:20:44.1668300Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:20:44.1670750Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_pad_mm.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:20:44.166885]
2025-07-17T07:20:44.2571730Z 
2025-07-17T07:20:44.2572890Z inductor/test_torchinductor_strided_blocks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_strided_blocks_1.1_aa6e0d637653dd3f_.log
2025-07-17T07:20:44.2573470Z 
2025-07-17T07:20:46.3312080Z Running inductor/test_torchinductor 2/2 ... [2025-07-17 07:20:46.330994]
2025-07-17T07:20:46.3312910Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:20:46.3315080Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor.py', '-m', 'not serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:20:46.331276]
2025-07-17T07:20:46.9622100Z 
2025-07-17T07:20:46.9622630Z inductor/test_pad_mm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_pad_mm_1.1_0397931b06a9d4d1_.log
2025-07-17T07:20:46.9623060Z 
2025-07-17T07:20:48.9805110Z Running test_file_check 1/1 ... [2025-07-17 07:20:48.980193]
2025-07-17T07:20:48.9806260Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:20:48.9808120Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_file_check.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:20:48.980507]
2025-07-17T07:20:52.2231790Z 
2025-07-17T07:20:52.2233020Z test_file_check 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_file_check_1.1_6a3097d5207a1b4a_.log
2025-07-17T07:20:52.2233780Z Running 2 items in this shard: test/test_file_check.py::TestFileCheck::test_all_python_api, test/test_file_check.py::TestFileCheck::test_not_run
2025-07-17T07:20:52.2234220Z 
2025-07-17T07:20:54.2319390Z Running export/test_tree_utils 1/1 ... [2025-07-17 07:20:54.231735]
2025-07-17T07:20:54.2320170Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:20:54.2322310Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_tree_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:20:54.232030]
2025-07-17T07:20:56.3957440Z 
2025-07-17T07:20:56.3958120Z export/test_tree_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_tree_utils_1.1_d03752c4dfe1fb49_.log
2025-07-17T07:20:56.3959100Z Running 2 items in this shard: test/export/test_tree_utils.py::TestTreeUtils::test_equivalence_check, test/export/test_tree_utils.py::TestTreeUtils::test_reorder_kwargs
2025-07-17T07:20:56.3959560Z 
2025-07-17T07:20:58.4169830Z Running inductor/test_indexing 1/1 ... [2025-07-17 07:20:58.416821]
2025-07-17T07:20:58.4170610Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:20:58.4173570Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_indexing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:20:58.417134]
2025-07-17T07:21:01.3040920Z 
2025-07-17T07:21:01.3042140Z inductor/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_indexing_1.1_9a269b448517f1b0_.log
2025-07-17T07:21:01.3047260Z Running 21 items in this shard: test/inductor/test_indexing.py::TestIndexingSimplification::test_expand_floor_div_applied, test/inductor/test_indexing.py::TestIndexingSimplification::test_expand_floor_div_skipped, test/inductor/test_indexing.py::TestIndexingSimplification::test_indexing_join, test/inductor/test_indexing.py::TestIndexingSimplification::test_indexing_simplification, test/inductor/test_indexing.py::TestIndexingSimplification::test_int8_unpack, test/inductor/test_indexing.py::TestIndexingSimplification::test_modular_indexing_pairs_merged, test/inductor/test_indexing.py::TestIndexingSimplification::test_modular_indexing_pairs_not_merged, test/inductor/test_indexing.py::TestIndexingSimplification::test_modular_indexing_positive, test/inductor/test_indexing.py::ExprPrinterTests::test_print_Min_Max, test/inductor/test_indexing.py::ExprPrinterTests::test_print_ceil, test/inductor/test_indexing.py::ExprPrinterTests::test_print_floor, test/inductor/test_indexing.py::ExprPrinterTests::test_print_floor_div, test/inductor/test_indexing.py::ExprPrinterTests::test_print_integer, test/inductor/test_indexing.py::ExprPrinterTests::test_print_mod, test/inductor/test_indexing.py::ExprPrinterTests::test_print_mod_index, test/inductor/test_indexing.py::ExprPrinterTests::test_print_pow, test/inductor/test_indexing.py::ExprPrinterTests::test_print_python_mod, test/inductor/test_indexing.py::ExprPrinterTests::test_print_round, test/inductor/test_indexing.py::ExprPrinterTests::test_print_round_decimal_ndigits_-1, test/inductor/test_indexing.py::ExprPrinterTests::test_print_round_decimal_ndigits_0, test/inductor/test_indexing.py::ExprPrinterTests::test_print_round_decimal_ndigits_1
2025-07-17T07:21:01.3051860Z 
2025-07-17T07:21:03.3009470Z Running dynamo/test_buffers_override 1/1 ... [2025-07-17 07:21:03.300671]
2025-07-17T07:21:03.3010310Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:21:03.3012540Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_buffers_override.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:21:03.300972]
2025-07-17T07:21:08.4597790Z 
2025-07-17T07:21:08.4598920Z dynamo/test_buffers_override 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_buffers_override_1.1_7fed5ca2338d8785_.log
2025-07-17T07:21:08.4599900Z Running 2 items in this shard: test/dynamo/test_buffers_override.py::TestBuffersOverride::test_buffers_override, test/dynamo/test_buffers_override.py::TestBuffersOverride::test_named_buffers_override
2025-07-17T07:21:08.4600440Z 
2025-07-17T07:21:10.4659350Z Running test_appending_byte_serializer 1/1 ... [2025-07-17 07:21:10.465746]
2025-07-17T07:21:10.4660200Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:21:10.4662580Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_appending_byte_serializer.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:21:10.466055]
2025-07-17T07:21:12.6771430Z 
2025-07-17T07:21:12.6772600Z test_appending_byte_serializer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_appending_byte_serializer_1.1_1593773c137136fb_.log
2025-07-17T07:21:12.6773910Z Running 3 items in this shard: test/test_appending_byte_serializer.py::TestAppendingByteSerializer::test_checksum, test/test_appending_byte_serializer.py::TestAppendingByteSerializer::test_write_and_read_class, test/test_appending_byte_serializer.py::TestAppendingByteSerializer::test_write_and_read_int
2025-07-17T07:21:12.6774760Z 
2025-07-17T07:21:14.7079130Z Running dynamo/test_resume 1/1 ... [2025-07-17 07:21:14.707735]
2025-07-17T07:21:14.7079940Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:21:14.7082240Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_resume.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:21:14.708033]
2025-07-17T07:21:17.0557900Z 
2025-07-17T07:21:17.0558970Z dynamo/test_resume 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_resume_1.1_8f70c3ab49f1b883_.log
2025-07-17T07:21:17.0559640Z Running 1 items in this shard: test/dynamo/test_resume.py::ResumeFunctionTests::test_freevars
2025-07-17T07:21:17.0559910Z 
2025-07-17T07:21:19.0827520Z Running inductor/test_aot_inductor 1/1 ... [2025-07-17 07:21:19.082537]
2025-07-17T07:21:19.0828340Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:21:19.0830650Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_aot_inductor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:21:19.082830]
2025-07-17T07:27:37.3536600Z 
2025-07-17T07:27:37.3537150Z test_decomp 4/4 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_4.4_ffb8ed9188971a78_.log
2025-07-17T07:27:37.4003690Z Running 2270 items in this shard: test/test_decomp.py::TestDecompCPU::test_batch_norm_unflatten_weight_bias_cpu, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_H_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___getitem___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___radd___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rand___cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmod___cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int8, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_corrcoef_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_corrcoef_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cos_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cos_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cos_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cos_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cos_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cosh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cosh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cosh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cosh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_count_nonzero_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_count_nonzero_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_count_nonzero_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_count_nonzero_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_cov_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_cross_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_cross_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cross_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cross_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cross_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cross_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_cummax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cummin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_cummin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_cummin_cpu_uint8, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_expm1_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_exponential_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_eye_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftshift_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftshift_cpu_bool, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fill_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fill_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fill_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_flatten_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_flatten_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_flatten_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_flip_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fliplr_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fliplr_cpu_int16, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_floor_divide_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_floor_divide_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmin_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmod_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmod_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fmod_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_frexp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_full_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_full_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_full_like_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_full_like_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_gather_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_gather_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_gather_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_gather_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_gather_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_gather_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_gather_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_gcd_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_gcd_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_ge_cpu_int16, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_solve_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_solve_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_hermitian_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_multi_dot_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_multi_dot_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_norm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_norm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_norm_cpu_float64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_long_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_long_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_lt_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_lt_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_lt_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_lu_solve_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_mH_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_mH_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_mH_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_mT_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_mT_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_mT_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_amax_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_hinge_embedding_loss_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_huber_loss_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_huber_loss_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_interpolate_area_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_interpolate_bicubic_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_interpolate_bicubic_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_interpolate_bilinear_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_interpolate_bilinear_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_nn_functional_interpolate_nearest_cpu_float16, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_unfold_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unfold_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_uniform_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_uniform_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_uniform_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_consecutive_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_consecutive_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_consecutive_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_cpu_uint64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_unravel_index_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_chunk_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsafe_split_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_unsqueeze_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_mean_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_mean_unbiased_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_unbiased_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_vdot_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_vdot_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_vdot_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_vdot_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vdot_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_vdot_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_complex_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zero__cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_like_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick__batch_norm_with_update_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__batch_norm_with_update_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick__native_batch_norm_legit_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick__native_batch_norm_legit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_put_accumulate_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick__upsample_bilinear2d_aa_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_abs_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addcmul_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_alias_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_arange_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_atan_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_baddbmm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_bernoulli_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_left_shift_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_not_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_or_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_right_shift_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_xor_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_block_diag_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_cat_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_cauchy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ceil_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_clone_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_complex_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_addcdiv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_block_diag_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_clamp_max_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_clamp_min_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_dot_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_expand_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_linalg_cross_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_logaddexp2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_logit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_mvlgamma_mvlgamma_p_1_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_nn_functional_hardswish_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_nn_functional_max_unpool2d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_nn_functional_max_unpool3d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_nn_functional_softshrink_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_nn_functional_unfold_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_norm_fro_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_norm_inf_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_rad2deg_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_rsub_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_sgn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_split_list_args_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_std_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_sum_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_t_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_transpose_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_triu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_cosh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_cosh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_cosh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_cosh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_count_nonzero_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_count_nonzero_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_count_nonzero_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_count_nonzero_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_count_nonzero_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_cumprod_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_cumprod_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_cumsum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_cumsum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_deg2rad_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_deg2rad_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_diag_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_diag_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_diag_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_diag_embed_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_diagonal_scatter_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_dist_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_erf_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_erfc_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_erfinv_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_exp2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_exponential_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_exponential_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_float8_e5m2fnuz, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_fftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_hfftn_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft2_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfft_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfftn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfftn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfftn_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_rfft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fill_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_flip_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_floor_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fmax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fmod_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_frac_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_frac_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_gcd_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_ge_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_heaviside_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_hypot_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_hypot_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_igamma_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_igammac_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_index_add_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_isin_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_isneginf_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_isneginf_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_isposinf_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_isposinf_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_isposinf_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_isposinf_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_isposinf_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_lcm_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_lerp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_lgamma_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_cross_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_tensor_overload_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_log10_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_log1p_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log_normal_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log_softmax_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp2_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logical_xor_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_logsumexp_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_lt_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_mean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_minimum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mul_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_1_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_5_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_native_batch_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_native_layer_norm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_empty_strided_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_new_zeros_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_nextafter_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_with_logits_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_elu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_embedding_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_glu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardshrink_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardsigmoid_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardsigmoid_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardsigmoid_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardtanh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_huber_loss_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_logsigmoid_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_grad_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool2d_grad_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_max_unpool3d_grad_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mish_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_mse_loss_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_relu_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_rrelu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_silu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_softshrink_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_softshrink_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_unfold_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_unfold_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_unfold_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_norm_fro_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_norm_fro_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_norm_fro_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_norm_inf_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_normal_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_normal_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_normal_in_place_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_ones_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_permute_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_polar_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_pow_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_prod_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_prod_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_rad2deg_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_randn_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_randn_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_randn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_reciprocal_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_remainder_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_renorm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_renorm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_renorm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_repeat_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_roll_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_round_decimals_0_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_rsqrt_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_rsqrt_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_rsqrt_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_rsqrt_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_rsqrt_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_rsqrt_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_select_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_select_scatter_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_sgn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_sinh_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sinh_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_slice_scatter_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_slice_scatter_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_special_entr_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_special_entr_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_special_entr_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_special_erfcx_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_special_i0e_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_special_i1_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_special_i1_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_special_i1_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_special_i1_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_special_i1e_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_special_log_ndtr_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_special_log_ndtr_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtr_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtr_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtr_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_special_ndtri_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_special_xlog1py_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_special_xlog1py_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_special_xlog1py_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_special_zeta_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_special_zeta_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_split_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_std_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_unbiased_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_unbiased_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_std_unbiased_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_std_unbiased_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_std_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_sum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_tanh_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_transpose_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_transpose_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_tril_indices_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_triu_indices_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_trunc_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_unfold_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_uniform_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unsafe_split_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_var_mean_unbiased_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_var_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_zero__cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_float64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_GRU_eval_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_RNN_train_mode_cpu_float32, test/test_decomp.py::DecompOneOffTestsCPU::test_contiguous_softmax_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_exponential_non_inf_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_native_layer_norm_cpu_decomp_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_sdpa_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_decomp.py::DecompOneOffTestsCPU::test_sdpa_nn_functional_scaled_dot_product_attention_cpu_float64
2025-07-17T07:27:37.4432340Z 
2025-07-17T07:27:37.7736600Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading
2025-07-17T07:27:37.7737140Z Uploading artifacts took 0.00 seconds
2025-07-17T07:27:42.3482360Z Running inductor/test_combo_kernels 1/1 ... [2025-07-17 07:27:42.347996]
2025-07-17T07:27:42.3482740Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:27:42.3484750Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_combo_kernels.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:27:42.348364]
2025-07-17T07:27:46.3526300Z 
2025-07-17T07:27:46.3526930Z inductor/test_combo_kernels 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_combo_kernels_1.1_45c90fabd4439954_.log
2025-07-17T07:27:46.3532810Z Running 20 items in this shard: test/inductor/test_combo_kernels.py::ComboKernelTests::test_2d_blocking_partitioning, test/inductor/test_combo_kernels.py::ComboKernelTests::test_activation_functions, test/inductor/test_combo_kernels.py::ComboKernelTests::test_mutated_args, test/inductor/test_combo_kernels.py::ComboKernelTests::test_reduce_functions, test/inductor/test_combo_kernels.py::ComboKernelTests::test_reduce_split, test/inductor/test_combo_kernels.py::ComboKernelBenchmarkTests::test_2d_blocking_benchmark, test/inductor/test_combo_kernels.py::ComboKernelBenchmarkTests::test_activation_benchmark, test/inductor/test_combo_kernels.py::ComboKernelBenchmarkTests::test_mutated_benchmark, test/inductor/test_combo_kernels.py::ComboKernelBenchmarkTests::test_persistent_reduction_no_x_dim, test/inductor/test_combo_kernels.py::ComboKernelBenchmarkTests::test_reduce_benchmark, test/inductor/test_combo_kernels.py::ComboKernelBenchmarkTests::test_round_robin_dispatch, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_2d_blocking, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_2d_blocking_round_robin, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_activations, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_activations_no_autotune, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_mutated, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_persistent_reduction_mixed_x_dim_cuda, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_persistent_reduction_no_x_dim, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_persistent_reduction_no_x_dim_2, test/inductor/test_combo_kernels.py::ComboKernelDynamicShapesTests::test_dynamic_shapes_reduce
2025-07-17T07:27:46.3538230Z 
2025-07-17T07:27:48.3813830Z Running torch_np/test_dtype 1/1 ... [2025-07-17 07:27:48.381167]
2025-07-17T07:27:48.3814690Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:27:48.3817000Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'torch_np/test_dtype.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:27:48.381467]
2025-07-17T07:27:50.6394540Z 
2025-07-17T07:27:50.6395050Z torch_np/test_dtype 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_dtype_1.1_11705d7e8a80906a_.log
2025-07-17T07:27:50.6404860Z Running 44 items in this shard: test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'bool_', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'complex128', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'complex64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'float16', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'float32', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'float64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'int16', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'int32', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'int64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'int8', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'uint16', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'uint32', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'uint64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_'uint8', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_bool, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'bool_', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'complex128', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'complex64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'float16', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'float32', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'float64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'int16', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'int32', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'int64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'int8', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'uint16', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'uint32', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'uint64', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.'uint8', test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.bool_, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.complex128, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.complex64, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.dtype('bool'), test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.float16, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.float32, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.float64, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.int16, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.int32, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.int64, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.int8, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.uint16, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.uint32, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.uint64, test/torch_np/test_dtype.py::TestConvertDType::test_convert_np_dtypes_numpy.uint8
2025-07-17T07:27:50.6414180Z 
2025-07-17T07:27:52.6776440Z Running inductor/test_metrics 1/1 ... [2025-07-17 07:27:52.677431]
2025-07-17T07:27:52.6777310Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:27:52.6779330Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_metrics.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:27:52.677737]
2025-07-17T07:27:55.2773590Z 
2025-07-17T07:27:55.2774660Z inductor/test_metrics 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_metrics_1.1_550c12fb0b58f2a3_.log
2025-07-17T07:27:55.2775160Z 
2025-07-17T07:27:57.3484770Z Running test_proxy_tensor 1/1 ... [2025-07-17 07:27:57.348251]
2025-07-17T07:27:57.3485560Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:27:57.3487340Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_proxy_tensor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:27:57.348542]
2025-07-17T07:28:09.6697410Z 
2025-07-17T07:28:09.6698870Z inductor/test_torchinductor 2/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_2.2_c9fe31e3bb1c0c84_.log
2025-07-17T07:28:09.6898650Z Running 868 items in this shard: test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_broadcast1_broadcast3, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_broadcast1_dense, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_broadcast1_double, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_broadcast1_transposed, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_broadcast2_dense, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_broadcast2_double, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_broadcast2_int, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_broadcast2_strided, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_broadcast3_broadcast1, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_broadcast3_broadcast2, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_broadcast3_broadcast3, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_broadcast3_double, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_broadcast3_int, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_dense_broadcast3, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_dense_dense, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_dense_double, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_double_broadcast1, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_double_double, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_double_int, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_double_strided, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_int_broadcast1, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_int_broadcast3, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_int_dense, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_int_int, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_int_transposed, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_strided_broadcast1, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_strided_broadcast2, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_strided_dense, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_strided_double, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_strided_strided, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_strided_transposed, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_transposed_broadcast2, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_transposed_int, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_transposed_strided, test/inductor/test_torchinductor.py::SweepInputsCpuTest::test_cpu_transposed_transposed, test/inductor/test_torchinductor.py::CpuTests::test_AllenaiLongformerBase_repro_cpu, test/inductor/test_torchinductor.py::CpuTests::test__dyn_quant_pack_4bit_weight_cpu, test/inductor/test_torchinductor.py::CpuTests::test__unsafe_masked_index_put_accumulate_cpu, test/inductor/test_torchinductor.py::CpuTests::test_adaptive_avg_pool1d_argmax_cpu, test/inductor/test_torchinductor.py::CpuTests::test_adaptive_avg_pool_errors_with_long_cpu, test/inductor/test_torchinductor.py::CpuTests::test_adaptive_avg_pool_with_output_size_0_cpu, test/inductor/test_torchinductor.py::CpuTests::test_add_complex3_cpu, test/inductor/test_torchinductor.py::CpuTests::test_add_complex4_cpu, test/inductor/test_torchinductor.py::CpuTests::test_add_complex_cpu, test/inductor/test_torchinductor.py::CpuTests::test_add_const_float_cpu, test/inductor/test_torchinductor.py::CpuTests::test_adding_tensor_offsets_cpu, test/inductor/test_torchinductor.py::CpuTests::test_addmm_cpu, test/inductor/test_torchinductor.py::CpuTests::test_addmv_cpu, test/inductor/test_torchinductor.py::CpuTests::test_alexnet_prefix_cpu, test/inductor/test_torchinductor.py::CpuTests::test_any_cpu, test/inductor/test_torchinductor.py::CpuTests::test_aoti_eager_dtype_device_layout_cpu, test/inductor/test_torchinductor.py::CpuTests::test_aoti_eager_support_out_cpu, test/inductor/test_torchinductor.py::CpuTests::test_aoti_eager_support_str_cpu, test/inductor/test_torchinductor.py::CpuTests::test_aoti_eager_with_persistent_cache_cpu, test/inductor/test_torchinductor.py::CpuTests::test_aoti_eager_with_scalar_cpu, test/inductor/test_torchinductor.py::CpuTests::test_arange3_cpu, test/inductor/test_torchinductor.py::CpuTests::test_arange4_cpu, test/inductor/test_torchinductor.py::CpuTests::test_argmax_argmin3_cpu, test/inductor/test_torchinductor.py::CpuTests::test_argmax_argmin_with_duplicates_cpu, 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test/inductor/test_torchinductor.py::CpuTests::test_batch_norm_2d_2_cpu, test/inductor/test_torchinductor.py::CpuTests::test_bernoulli1_cpu, test/inductor/test_torchinductor.py::CpuTests::test_bernoulli2_cpu, test/inductor/test_torchinductor.py::CpuTests::test_bfloat16_to_int16_cpu, test/inductor/test_torchinductor.py::CpuTests::test_bitwise2_cpu, test/inductor/test_torchinductor.py::CpuTests::test_bitwise_cpu, test/inductor/test_torchinductor.py::CpuTests::test_bmm1_cpu, test/inductor/test_torchinductor.py::CpuTests::test_bmm2_cpu, test/inductor/test_torchinductor.py::CpuTests::test_bool_cpu, test/inductor/test_torchinductor.py::CpuTests::test_bucketize_computed_offsets_cpu, test/inductor/test_torchinductor.py::CpuTests::test_bucketize_default_kwargs_cpu, test/inductor/test_torchinductor.py::CpuTests::test_bucketize_int_int16_int64_cpu, test/inductor/test_torchinductor.py::CpuTests::test_bucketize_int_int16_int8_cpu, 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test/inductor/test_torchinductor.py::GPUTests::test_roll_mps, test/inductor/test_torchinductor.py::GPUTests::test_round_correctness_mps, test/inductor/test_torchinductor.py::GPUTests::test_rsqrt_dynamic_shapes_mps, test/inductor/test_torchinductor.py::GPUTests::test_scalar_cpu_tensor_arg_mps, test/inductor/test_torchinductor.py::GPUTests::test_scaled_dot_product_attention_mps, test/inductor/test_torchinductor.py::GPUTests::test_scatter1_mps, test/inductor/test_torchinductor.py::GPUTests::test_scatter2_mps, test/inductor/test_torchinductor.py::GPUTests::test_scatter3_mps, test/inductor/test_torchinductor.py::GPUTests::test_scatter4_mps, test/inductor/test_torchinductor.py::GPUTests::test_scatter6_mps, test/inductor/test_torchinductor.py::GPUTests::test_scatter_add1_mps, test/inductor/test_torchinductor.py::GPUTests::test_scatter_add3_mps, test/inductor/test_torchinductor.py::GPUTests::test_sdpa_prefer_nd_tiling_False_use_block_ptr_True_mps, test/inductor/test_torchinductor.py::GPUTests::test_searchsorted_broadcast_mps, test/inductor/test_torchinductor.py::GPUTests::test_setitem_with_int_parameter_mps, test/inductor/test_torchinductor.py::GPUTests::test_sgn_extremal_mps, test/inductor/test_torchinductor.py::GPUTests::test_sigmoid_mps, test/inductor/test_torchinductor.py::GPUTests::test_signbit_mps, test/inductor/test_torchinductor.py::GPUTests::test_simplify_loops_mps, test/inductor/test_torchinductor.py::GPUTests::test_single_elem_indirect_mps, test/inductor/test_torchinductor.py::GPUTests::test_single_elem_mps, test/inductor/test_torchinductor.py::GPUTests::test_slice3_mps, test/inductor/test_torchinductor.py::GPUTests::test_slice_mutation1_mps, test/inductor/test_torchinductor.py::GPUTests::test_slice_mutation2_mps, test/inductor/test_torchinductor.py::GPUTests::test_slice_scatter3_mps, test/inductor/test_torchinductor.py::GPUTests::test_slice_scatter5_mps, test/inductor/test_torchinductor.py::GPUTests::test_softmax_backward_data_mps, test/inductor/test_torchinductor.py::GPUTests::test_split_cumprod_low_prec_mps, test/inductor/test_torchinductor.py::GPUTests::test_split_cumprod_mps, test/inductor/test_torchinductor.py::GPUTests::test_split_cumsum_mps, test/inductor/test_torchinductor.py::GPUTests::test_split_reduction_dynamic_shape_mps, test/inductor/test_torchinductor.py::GPUTests::test_split_with_integer_mps, test/inductor/test_torchinductor.py::GPUTests::test_squeeze1_mps, test/inductor/test_torchinductor.py::GPUTests::test_squeeze2_mps, test/inductor/test_torchinductor.py::GPUTests::test_stride_preservation_with_stride_modifying_fx_pass_mps, test/inductor/test_torchinductor.py::GPUTests::test_strided_inputs_mps, test/inductor/test_torchinductor.py::GPUTests::test_sum3_mps, test/inductor/test_torchinductor.py::GPUTests::test_sum4_mps, test/inductor/test_torchinductor.py::GPUTests::test_sum_dtype_mps, test/inductor/test_torchinductor.py::GPUTests::test_sum_int_mps, test/inductor/test_torchinductor.py::GPUTests::test_tan_mps, test/inductor/test_torchinductor.py::GPUTests::test_tensor2_mps, test/inductor/test_torchinductor.py::GPUTests::test_tensor_index_put_slice_mps, test/inductor/test_torchinductor.py::GPUTests::test_tmp_not_defined_issue2_mps, test/inductor/test_torchinductor.py::GPUTests::test_tmp_not_defined_issue3_mps, test/inductor/test_torchinductor.py::GPUTests::test_to_device_constant_mps, test/inductor/test_torchinductor.py::GPUTests::test_to_device_mps, test/inductor/test_torchinductor.py::GPUTests::test_to_dtype_mps, test/inductor/test_torchinductor.py::GPUTests::test_to_memory_format_mps, test/inductor/test_torchinductor.py::GPUTests::test_topk_mps, test/inductor/test_torchinductor.py::GPUTests::test_transpose_mps, test/inductor/test_torchinductor.py::GPUTests::test_transposed_propagates_mps, test/inductor/test_torchinductor.py::GPUTests::test_uint4x2_mixed_mm_mps, test/inductor/test_torchinductor.py::GPUTests::test_unbacked_floordiv_simplify_errors_mps, test/inductor/test_torchinductor.py::GPUTests::test_unspec_inputs_float16_mps, test/inductor/test_torchinductor.py::GPUTests::test_unspec_inputs_float32_mps, test/inductor/test_torchinductor.py::GPUTests::test_unspec_inputs_float64_mps, test/inductor/test_torchinductor.py::GPUTests::test_unspec_inputs_int16_mps, test/inductor/test_torchinductor.py::GPUTests::test_unspec_inputs_int64_mps, test/inductor/test_torchinductor.py::GPUTests::test_unspec_inputs_uint8_mps, test/inductor/test_torchinductor.py::GPUTests::test_unsqueeze_inplace_mps, test/inductor/test_torchinductor.py::GPUTests::test_unsqueeze_mps, test/inductor/test_torchinductor.py::GPUTests::test_upsample_bilinear2d_a_mps, test/inductor/test_torchinductor.py::GPUTests::test_upsample_bilinear2d_b_mps, test/inductor/test_torchinductor.py::GPUTests::test_upsample_nearest3d_mps, test/inductor/test_torchinductor.py::GPUTests::test_var_correction_mps, test/inductor/test_torchinductor.py::GPUTests::test_vdd_clamp_mps, test/inductor/test_torchinductor.py::GPUTests::test_vectorized_ops_masked_mps, test/inductor/test_torchinductor.py::GPUTests::test_view_as_complex_mps, test/inductor/test_torchinductor.py::GPUTests::test_view_detach_mps, test/inductor/test_torchinductor.py::GPUTests::test_views1_mps, test/inductor/test_torchinductor.py::GPUTests::test_views2_mps, test/inductor/test_torchinductor.py::GPUTests::test_views6_mps, test/inductor/test_torchinductor.py::GPUTests::test_views7_mps, test/inductor/test_torchinductor.py::GPUTests::test_weight_norm_bwd_mps, test/inductor/test_torchinductor.py::GPUTests::test_where_with_logical_op_mps, test/inductor/test_torchinductor.py::GPUTests::test_xblock_divides_xnumel_mps, test/inductor/test_torchinductor.py::GPUTests::test_zero_element_mutation_mps, test/inductor/test_torchinductor.py::GPUTests::test_zeros_mps
2025-07-17T07:28:09.7085590Z 
2025-07-17T07:28:12.0187610Z Running inductor/test_gpu_cpp_wrapper 1/1 ... [2025-07-17 07:28:12.018541]
2025-07-17T07:28:12.0188650Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:28:12.0191050Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_gpu_cpp_wrapper.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:28:12.018860]
2025-07-17T07:28:14.9777890Z 
2025-07-17T07:28:14.9779200Z inductor/test_gpu_cpp_wrapper 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_gpu_cpp_wrapper_1.1_c8bf87402e3c9c1b_.log
2025-07-17T07:28:14.9779800Z 
2025-07-17T07:28:17.0023750Z Running inductor/test_torchinductor_opinfo 2/14 ... [2025-07-17 07:28:17.002137]
2025-07-17T07:28:17.0024750Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:28:17.0026380Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor_opinfo.py', '-m', 'not serial', '--shard-id=2', '--num-shards=14', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:28:17.002437]
2025-07-17T07:33:36.2033330Z 
2025-07-17T07:33:36.2034020Z test_proxy_tensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_proxy_tensor_1.1_70e8a98e19c81ed5_.log
2025-07-17T07:33:36.3315910Z Running 3611 items in this shard: test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_allclose, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_amp_cache, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_constant_blowup, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_constant_proxy_tensor_mut, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_constant_random, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_constant_unbind, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_decomp_of_capture, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_decomposition_interpreter, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_empty_like_doesnt_burn_in_defaults, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_inplace_metadata, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_isolated_graphmodule, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_make_fx_model_double_param, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_make_fx_model_fwd_bwd, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_make_fx_model_fwd_bwd_wgtupdate, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_make_fx_overloads, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_make_fx_reentrant_dispatch, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_make_fx_simple, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_mode_tracing_factory_function, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_partial_decomp, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_pickle_issue89626, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_pr_86917, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_pre_dispatch_functionalization, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_pre_dispatch_functionalization_view_op, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_pre_dispatch_linear, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_pre_dispatch_mode_stack, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_pre_dispatch_no_grad, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_proxy_tensor, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_proxy_tensor_mode_with_decomp_table_preserves_proxy, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_resnet18_backward_trace, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_scalar_device, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_strides, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_tensor_constants, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_trace_subclasses, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_val_metadata_mutation, test/test_proxy_tensor.py::TestGenericProxyTensorReal::test_varargs, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_allclose, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_amp_cache, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_constant_blowup, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_constant_proxy_tensor_mut, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_constant_random, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_constant_unbind, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_decomp_of_capture, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_decomposition_interpreter, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_empty_like_doesnt_burn_in_defaults, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_inplace_metadata, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_isolated_graphmodule, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_make_fx_model_double_param, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_make_fx_model_fwd_bwd, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_make_fx_model_fwd_bwd_wgtupdate, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_make_fx_overloads, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_make_fx_reentrant_dispatch, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_make_fx_simple, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_mode_tracing_factory_function, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_partial_decomp, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_pickle_issue89626, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_pr_86917, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_pre_dispatch_functionalization, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_pre_dispatch_functionalization_view_op, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_pre_dispatch_linear, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_pre_dispatch_mode_stack, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_pre_dispatch_no_grad, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_proxy_tensor, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_proxy_tensor_mode_with_decomp_table_preserves_proxy, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_resnet18_backward_trace, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_scalar_device, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_strides, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_tensor_constants, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_trace_subclasses, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_val_metadata_mutation, test/test_proxy_tensor.py::TestGenericProxyTensorFake::test_varargs, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_allclose, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_amp_cache, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_constant_blowup, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_constant_proxy_tensor_mut, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_constant_random, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_constant_unbind, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_decomp_of_capture, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_decomposition_interpreter, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_empty_like_doesnt_burn_in_defaults, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_inplace_metadata, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_isolated_graphmodule, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_make_fx_model_double_param, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_make_fx_model_fwd_bwd, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_make_fx_model_fwd_bwd_wgtupdate, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_make_fx_overloads, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_make_fx_reentrant_dispatch, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_make_fx_simple, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_mode_tracing_factory_function, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_partial_decomp, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_pickle_issue89626, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_pr_86917, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_pre_dispatch_functionalization, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_pre_dispatch_functionalization_view_op, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_pre_dispatch_linear, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_pre_dispatch_mode_stack, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_pre_dispatch_no_grad, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_proxy_tensor, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_proxy_tensor_mode_with_decomp_table_preserves_proxy, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_resnet18_backward_trace, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_scalar_device, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_strides, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_tensor_constants, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_trace_subclasses, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_val_metadata_mutation, test/test_proxy_tensor.py::TestGenericProxyTensorSymbolic::test_varargs, test/test_proxy_tensor.py::TestRealProxyTensor::test_error_on_data_dependent_ops, test/test_proxy_tensor.py::TestFakeProxyTensor::test_alias, test/test_proxy_tensor.py::TestFakeProxyTensor::test_fake_tensor_mode, test/test_proxy_tensor.py::TestFakeProxyTensor::test_free_fake, test/test_proxy_tensor.py::TestFakeProxyTensor::test_fused_adam, test/test_proxy_tensor.py::TestFakeProxyTensor::test_issue82547, test/test_proxy_tensor.py::TestFakeProxyTensor::test_meta, test/test_proxy_tensor.py::TestFakeProxyTensor::test_use_fake_and_tensor, test/test_proxy_tensor.py::TestSymbolicTracing::test_adv_index_batch, test/test_proxy_tensor.py::TestSymbolicTracing::test_arange_unbacked_output_size, test/test_proxy_tensor.py::TestSymbolicTracing::test_binary_broadcast, test/test_proxy_tensor.py::TestSymbolicTracing::test_boolean_index, test/test_proxy_tensor.py::TestSymbolicTracing::test_broadcast_shapes, test/test_proxy_tensor.py::TestSymbolicTracing::test_cat, test/test_proxy_tensor.py::TestSymbolicTracing::test_constant_specialization, test/test_proxy_tensor.py::TestSymbolicTracing::test_cpu_scalar_cuda, test/test_proxy_tensor.py::TestSymbolicTracing::test_cumsum_unbacked, test/test_proxy_tensor.py::TestSymbolicTracing::test_debug_interpreter, test/test_proxy_tensor.py::TestSymbolicTracing::test_deduped_shape, test/test_proxy_tensor.py::TestSymbolicTracing::test_dynamic_pointwise_scalar, test/test_proxy_tensor.py::TestSymbolicTracing::test_elementwise_meta_with_sym_numbers, test/test_proxy_tensor.py::TestSymbolicTracing::test_expand, test/test_proxy_tensor.py::TestSymbolicTracing::test_fake_tensor_as_size, test/test_proxy_tensor.py::TestSymbolicTracing::test_guard_lowerbound_range_refinement, test/test_proxy_tensor.py::TestSymbolicTracing::test_guard_lowerbound_range_refinement_multivariate, test/test_proxy_tensor.py::TestSymbolicTracing::test_guard_upperbound_range_refinement, test/test_proxy_tensor.py::TestSymbolicTracing::test_guard_upperbound_range_refinement_multivariate, test/test_proxy_tensor.py::TestSymbolicTracing::test_guards_equal, test/test_proxy_tensor.py::TestSymbolicTracing::test_int_input, test/test_proxy_tensor.py::TestSymbolicTracing::test_invalidate_nonzero, test/test_proxy_tensor.py::TestSymbolicTracing::test_invalidate_nonzero_propagate_real_tensors, test/test_proxy_tensor.py::TestSymbolicTracing::test_item, test/test_proxy_tensor.py::TestSymbolicTracing::test_item_to_constructor, test/test_proxy_tensor.py::TestSymbolicTracing::test_make_fx_with_custom_tracer_preserving_nn_module_stack, test/test_proxy_tensor.py::TestSymbolicTracing::test_mega_guard, test/test_proxy_tensor.py::TestSymbolicTracing::test_metadata, test/test_proxy_tensor.py::TestSymbolicTracing::test_metadata_fresh, test/test_proxy_tensor.py::TestSymbolicTracing::test_mod_gcd_unbacked, test/test_proxy_tensor.py::TestSymbolicTracing::test_multiply_shape, test/test_proxy_tensor.py::TestSymbolicTracing::test_neg_shape, test/test_proxy_tensor.py::TestSymbolicTracing::test_new_empty, test/test_proxy_tensor.py::TestSymbolicTracing::test_non_deduped_shape, test/test_proxy_tensor.py::TestSymbolicTracing::test_non_symint_size_spec, test/test_proxy_tensor.py::TestSymbolicTracing::test_nonidentity_transitive_guards, test/test_proxy_tensor.py::TestSymbolicTracing::test_reflect_r_over_x, test/test_proxy_tensor.py::TestSymbolicTracing::test_repeat_interleave, test/test_proxy_tensor.py::TestSymbolicTracing::test_repeat_interleave_unbacked_output_size, test/test_proxy_tensor.py::TestSymbolicTracing::test_reshape_divisibility_unbacked, test/test_proxy_tensor.py::TestSymbolicTracing::test_resize_from_zero, test/test_proxy_tensor.py::TestSymbolicTracing::test_return_symint, test/test_proxy_tensor.py::TestSymbolicTracing::test_rmethod, test/test_proxy_tensor.py::TestSymbolicTracing::test_setitem_symint, test/test_proxy_tensor.py::TestSymbolicTracing::test_size_with_tensor, test/test_proxy_tensor.py::TestSymbolicTracing::test_split_unbacked_sizes, test/test_proxy_tensor.py::TestSymbolicTracing::test_sqrt_size, test/test_proxy_tensor.py::TestSymbolicTracing::test_sym_storage_offset, test/test_proxy_tensor.py::TestSymbolicTracing::test_symbolic_repeat_interleave, test/test_proxy_tensor.py::TestSymbolicTracing::test_symint_to_tensor, test/test_proxy_tensor.py::TestSymbolicTracing::test_tensor_symfloat, test/test_proxy_tensor.py::TestSymbolicTracing::test_unary, test/test_proxy_tensor.py::TestSymbolicTracing::test_unbacked_batch_resnet, test/test_proxy_tensor.py::TestSymbolicTracing::test_unbacked_slice, test/test_proxy_tensor.py::TestSymbolicTracing::test_unbacked_unification, test/test_proxy_tensor.py::TestSymbolicTracing::test_unbacked_unify_dependency_violation, test/test_proxy_tensor.py::TestSymbolicTracing::test_unbacked_unify_guard, test/test_proxy_tensor.py::TestSymbolicTracing::test_unbacked_unify_guard_transitivity, test/test_proxy_tensor.py::TestSymbolicTracing::test_view_divisibility_unbacked, test/test_proxy_tensor.py::TestSymbolicTracing::test_view_divisibility_unbacked_relatively_prime, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_H_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_NumpyCatCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_NumpyCubeCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_NumpyMulCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_NumpyMulScalarCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_NumpyNMSCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_NumpyNonzeroCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_NumpySortCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_NumpySplitCopyCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_NumpyTakeCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_NumpyViewCopyCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_T_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive___getitem___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive___radd___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive___rdiv___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive___rmatmul___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive___rmod___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive___rmul___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive___rpow___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive___rsub___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive__batch_norm_with_update_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive__chunk_cat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive__native_batch_norm_legit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive__segment_reduce_lengths_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive__segment_reduce_offsets_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive__softmax_backward_data_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive__unsafe_masked_index_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive__unsafe_masked_index_put_accumulate_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive__upsample_bilinear2d_aa_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_abs_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_acos_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_acosh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_addbmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_addcdiv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_addcmul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_addmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_addmm_decomposed_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_addmv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_addr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_alias_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_all_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_allclose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_aminmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_angle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_any_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_arange_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_argmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_argmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_argsort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_argwhere_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_as_strided_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_as_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_as_strided_partial_views_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_as_strided_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_asin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_asinh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_atan2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_atan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_atanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_atleast_1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_atleast_2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_atleast_3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_baddbmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_bernoulli_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_bfloat16_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_block_diag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_bmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_bool_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_broadcast_shapes_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_broadcast_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_broadcast_to_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_bucketize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_byte_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cartesian_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cauchy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cdist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cdouble_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_ceil_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cfloat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_chalf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_char_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cholesky_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cholesky_inverse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cholesky_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_chunk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_clamp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_clamp_max_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_clamp_min_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_clone_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_column_stack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_combinations_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_complex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cond_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_conj_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_conj_physical_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_constant_pad_nd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_contiguous_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_copysign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_corrcoef_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cos_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cosh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_count_nonzero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cov_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cross_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cummax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cummin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cumprod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cumsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_cumulative_trapezoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_deg2rad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_diag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_diag_embed_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_diagflat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_diagonal_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_diagonal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_diagonal_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_diff_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_digamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_dist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_div_floor_rounding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_div_no_rounding_mode_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_div_trunc_rounding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_dot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_double_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_dsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_dstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_einsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_empty_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_empty_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_empty_permuted_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_empty_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_eq_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_equal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_erf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_erfc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_erfinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_exp2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_exp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_expand_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_expand_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_expand_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_expm1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_exponential_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_eye_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_fft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_fft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_fftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_fftshift_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_hfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_hfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_hfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_ifft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_ifft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_ifftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_ifftshift_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_ihfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_ihfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_ihfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_irfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_irfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_irfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_rfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_rfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fft_rfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_flatten_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_flex_attention_backward_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_flex_attention_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_flip_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fliplr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_flipud_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_float_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_float_power_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_floor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_floor_divide_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_fmod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_frac_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_frexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_full_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_full_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_gather_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_ge_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_geometric_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_geqrf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_gradient_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_grid_sampler_2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_gt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_half_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_heaviside_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_histc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_histogram_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_histogramdd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_hsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_hstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_hypot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_i0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_igamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_igammac_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_index_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_index_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_index_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_index_put_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_index_reduce_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_index_reduce_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_index_reduce_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_index_reduce_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_index_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_inner_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_int_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_invoke_quant_packed_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_invoke_quant_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_invoke_subgraph_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_isclose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_isfinite_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_isin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_isinf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_isnan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_isneginf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_isposinf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_isreal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_item_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_jiterator_2inputs_2outputs_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_jiterator_4inputs_with_extra_args_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_jiterator_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_jiterator_binary_return_by_ref_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_jiterator_unary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_kron_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_kthvalue_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_ldexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_le_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_lerp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_lgamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_cholesky_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_cholesky_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_cond_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_cross_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_det_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_diagonal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_eig_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_eigh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_eigvals_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_eigvalsh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_householder_product_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_inv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_inv_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_ldl_factor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_ldl_factor_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_ldl_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_lstsq_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_lstsq_grad_oriented_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_lu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_lu_factor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_lu_factor_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_lu_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_matrix_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_matrix_power_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_matrix_rank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_matrix_rank_hermitian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_multi_dot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_norm_subgradients_at_zero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_pinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_pinv_hermitian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_pinv_singular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_qr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_slogdet_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_solve_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_solve_triangular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_svd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_svdvals_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_tensorinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_tensorsolve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_vander_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_vecdot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linalg_vector_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linspace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_linspace_tensor_overload_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_log10_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_log1p_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_log2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_log_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_log_normal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_log_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_log_softmax_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_logaddexp2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_logaddexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_logcumsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_logdet_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_logical_and_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_logical_not_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_logical_or_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_logical_xor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_logit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_logspace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_logspace_tensor_overload_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_logsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_long_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_lt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_lu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_lu_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_lu_unpack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_mH_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_mT_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_map_nested_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_map_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_map_triple_nested_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_argmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_argmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_cumprod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_cumsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_log_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_logaddexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_logsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_median_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_normalize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_softmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_std_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_masked_var_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_matmul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_matrix_exp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_max_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_max_pool2d_with_indices_backward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_max_reduction_no_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_max_reduction_with_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_maximum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_median_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_meshgrid_list_of_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_meshgrid_variadic_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_min_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_min_reduction_no_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_min_reduction_with_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_minimum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_mm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_mode_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_movedim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_msort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_mul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_multinomial_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_mv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nan_to_num_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nanmean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nanmedian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nanquantile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nansum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_narrow_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_narrow_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_native_batch_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_native_dropout_backward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_native_layer_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_ne_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_neg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_new_empty_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_new_empty_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_new_full_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_new_ones_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_new_zeros_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nextafter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_alpha_dropout_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_avg_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_avg_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_avg_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_batch_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_binary_cross_entropy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_celu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_channel_shuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_conv1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_conv2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_conv3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_conv_transpose1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_conv_transpose2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_conv_transpose3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_cosine_embedding_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_cosine_similarity_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_cross_entropy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_ctc_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_dropout2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_dropout3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_dropout_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_elu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_embedding_bag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_embedding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_fractional_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_fractional_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_gaussian_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_gelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_glu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_grid_sample_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_group_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_hardshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_hardsigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_hardswish_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_hardtanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_hinge_embedding_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_huber_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_instance_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_interpolate_area_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_interpolate_bicubic_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_interpolate_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_interpolate_linear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_interpolate_nearest_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_interpolate_trilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_kl_div_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_l1_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_layer_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_leaky_relu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_linear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_local_response_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_logsigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_margin_ranking_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_max_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_max_unpool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_max_unpool1d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_max_unpool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_max_unpool2d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_max_unpool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_max_unpool3d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_mish_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_mse_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_multi_head_attention_forward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_multi_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_multilabel_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_normalize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_pad_circular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_pad_constant_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_pad_reflect_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_pad_replicate_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_pad_replicate_negative_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_pairwise_distance_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_pdist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_pixel_shuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_pixel_unshuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_poisson_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_prelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_relu6_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_relu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_rms_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_rrelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_selu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_silu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_smooth_l1_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_soft_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_softmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_softmin_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_softplus_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_softshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_softsign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_tanhshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_threshold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_triplet_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_unfold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_upsample_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nn_functional_upsample_nearest_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nonzero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_nonzero_static_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_norm_fro_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_norm_inf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_norm_nuc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_normal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_normal_in_place_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_normal_number_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_ones_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_ones_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_ormqr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_outer_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_pca_lowrank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_permute_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_permute_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_pinverse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_polar_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_polygamma_polygamma_n_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_polygamma_polygamma_n_1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_polygamma_polygamma_n_2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_polygamma_polygamma_n_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_polygamma_polygamma_n_4_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_positive_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_pow_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_put_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_qr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_quantile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_rad2deg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_rand_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_randint_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_randint_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_randn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_randn_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_ravel_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_real_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_reciprocal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_remainder_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_renorm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_repeat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_repeat_interleave_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_reshape_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_reshape_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_resize__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_resize_as__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_resolve_conj_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_resolve_neg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_roll_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_rot90_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_round_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_round_decimals_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_round_decimals_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_round_decimals_neg_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_rsqrt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_rsub_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_scalar_tensor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_scan_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_scatter_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_scatter_reduce_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_scatter_reduce_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_scatter_reduce_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_scatter_reduce_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_scatter_reduce_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_searchsorted_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_select_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_sgn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_short_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_sigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_sign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_signal_windows_bartlett_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_signal_windows_blackman_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_signal_windows_cosine_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_signal_windows_exponential_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_signal_windows_gaussian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_signal_windows_general_cosine_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_signal_windows_general_hamming_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_signal_windows_hamming_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_signal_windows_hann_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_signal_windows_kaiser_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_signal_windows_nuttall_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_signbit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_sin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_sinc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_sinh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_slice_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_slice_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_softmax_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_sort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_sparse_mm_reduce_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_sparse_sampled_addmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_airy_ai_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_bessel_j0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_bessel_j1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_bessel_y0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_bessel_y1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_chebyshev_polynomial_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_chebyshev_polynomial_u_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_chebyshev_polynomial_v_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_chebyshev_polynomial_w_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_entr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_erfcx_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_hermite_polynomial_h_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_hermite_polynomial_he_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_i0e_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_i1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_i1e_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_laguerre_polynomial_l_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_legendre_polynomial_p_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_log_ndtr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_modified_bessel_i0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_modified_bessel_i1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_modified_bessel_k0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_modified_bessel_k1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_ndtr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_ndtri_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_scaled_modified_bessel_k0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_scaled_modified_bessel_k1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_spherical_bessel_j0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_xlog1py_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_special_zeta_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_split_list_args_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_split_with_sizes_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_split_with_sizes_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_sqrt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_square_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_squeeze_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_squeeze_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_squeeze_multiple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_stack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_std_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_std_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_std_mean_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_std_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_stft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_sub_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_sum_to_size_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_svd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_svd_lowrank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_t_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_take_along_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_take_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_tan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_tanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_tensor_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_tensordot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_tile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_to_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_to_sparse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_topk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_trace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_transpose_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_transpose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_trapezoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_trapz_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_triangular_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_tril_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_triu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_true_divide_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_trunc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_unbind_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_unbind_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_unflatten_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_unfold_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_unfold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_uniform_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_unique_consecutive_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_unique_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_unsafe_chunk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_unsafe_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_unsqueeze_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_unsqueeze_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_var_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_var_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_var_mean_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_var_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_vdot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_view_as_complex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_view_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_view_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_view_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_vsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_vstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_where_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_while_loop_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_xlogy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_zero__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_zeros_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_exhaustive_zeros_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_H_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_NumpyCatCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_NumpyCubeCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_NumpyMulCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_NumpyMulScalarCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_NumpyNMSCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_NumpyNonzeroCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_NumpySortCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_NumpySplitCopyCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_NumpyTakeCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_NumpyViewCopyCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_T_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive___getitem___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive___radd___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive___rdiv___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive___rmatmul___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive___rmod___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive___rmul___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive___rpow___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive___rsub___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive__batch_norm_with_update_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive__chunk_cat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive__native_batch_norm_legit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive__segment_reduce_lengths_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive__segment_reduce_offsets_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive__softmax_backward_data_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive__unsafe_masked_index_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive__unsafe_masked_index_put_accumulate_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive__upsample_bilinear2d_aa_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_abs_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_acos_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_acosh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_addbmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_addcdiv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_addcmul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_addmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_addmm_decomposed_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_addmv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_addr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_alias_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_all_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_allclose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_aminmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_angle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_any_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_arange_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_argmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_argmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_argsort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_argwhere_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_as_strided_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_as_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_as_strided_partial_views_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_as_strided_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_asin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_asinh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_atan2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_atan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_atanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_atleast_1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_atleast_2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_atleast_3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_baddbmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_bernoulli_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_bfloat16_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_block_diag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_bmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_bool_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_broadcast_shapes_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_broadcast_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_broadcast_to_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_bucketize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_byte_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cartesian_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cauchy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cdist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cdouble_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_ceil_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cfloat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_chalf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_char_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cholesky_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cholesky_inverse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cholesky_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_chunk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_clamp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_clamp_max_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_clamp_min_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_clone_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_column_stack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_combinations_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_complex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cond_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_conj_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_conj_physical_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_constant_pad_nd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_contiguous_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_copysign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_corrcoef_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cos_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cosh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_count_nonzero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cov_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cross_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cummax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cummin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cumprod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cumsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_cumulative_trapezoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_deg2rad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_diag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_diag_embed_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_diagflat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_diagonal_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_diagonal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_diagonal_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_diff_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_digamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_dist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_div_floor_rounding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_div_no_rounding_mode_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_div_trunc_rounding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_dot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_double_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_dsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_dstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_einsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_empty_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_empty_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_empty_permuted_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_empty_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_eq_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_equal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_erf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_erfc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_erfinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_exp2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_exp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_expand_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_expand_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_expand_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_expm1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_exponential_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_eye_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_fft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_fft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_fftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_fftshift_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_hfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_hfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_hfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_ifft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_ifft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_ifftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_ifftshift_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_ihfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_ihfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_ihfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_irfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_irfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_irfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_rfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_rfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fft_rfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_flatten_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_flex_attention_backward_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_flex_attention_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_flip_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fliplr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_flipud_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_float_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_float_power_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_floor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_floor_divide_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_fmod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_frac_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_frexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_full_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_full_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_gather_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_ge_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_geometric_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_geqrf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_gradient_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_grid_sampler_2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_gt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_half_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_heaviside_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_histc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_histogram_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_histogramdd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_hsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_hstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_hypot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_i0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_igamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_igammac_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_index_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_index_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_index_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_index_put_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_index_reduce_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_index_reduce_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_index_reduce_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_index_reduce_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_index_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_inner_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_int_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_invoke_quant_packed_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_invoke_quant_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_invoke_subgraph_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_isclose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_isfinite_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_isin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_isinf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_isnan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_isneginf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_isposinf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_isreal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_item_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_jiterator_2inputs_2outputs_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_jiterator_4inputs_with_extra_args_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_jiterator_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_jiterator_binary_return_by_ref_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_jiterator_unary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_kron_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_kthvalue_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_ldexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_le_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_lerp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_lgamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_cholesky_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_cholesky_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_cond_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_cross_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_det_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_diagonal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_eig_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_eigh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_eigvals_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_eigvalsh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_householder_product_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_inv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_inv_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_ldl_factor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_ldl_factor_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_ldl_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_lstsq_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_lstsq_grad_oriented_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_lu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_lu_factor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_lu_factor_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_lu_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_matrix_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_matrix_power_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_matrix_rank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_matrix_rank_hermitian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_multi_dot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_norm_subgradients_at_zero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_pinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_pinv_hermitian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_pinv_singular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_qr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_slogdet_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_solve_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_solve_triangular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_svd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_svdvals_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_tensorinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_tensorsolve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_vander_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_vecdot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linalg_vector_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linspace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_linspace_tensor_overload_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_log10_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_log1p_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_log2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_log_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_log_normal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_log_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_log_softmax_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_logaddexp2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_logaddexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_logcumsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_logdet_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_logical_and_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_logical_not_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_logical_or_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_logical_xor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_logit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_logspace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_logspace_tensor_overload_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_logsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_long_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_lt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_lu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_lu_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_lu_unpack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_mH_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_mT_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_map_nested_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_map_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_map_triple_nested_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_argmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_argmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_cumprod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_cumsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_log_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_logaddexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_logsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_median_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_normalize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_softmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_std_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_masked_var_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_matmul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_matrix_exp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_max_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_max_pool2d_with_indices_backward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_max_reduction_no_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_max_reduction_with_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_maximum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_median_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_meshgrid_list_of_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_meshgrid_variadic_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_min_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_min_reduction_no_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_min_reduction_with_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_minimum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_mm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_mode_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_movedim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_msort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_mul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_multinomial_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_mv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nan_to_num_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nanmean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nanmedian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nanquantile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nansum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_narrow_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_narrow_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_native_batch_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_native_dropout_backward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_native_layer_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_ne_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_neg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_new_empty_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_new_empty_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_new_full_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_new_ones_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_new_zeros_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nextafter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_alpha_dropout_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_avg_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_avg_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_avg_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_batch_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_binary_cross_entropy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_celu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_channel_shuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_conv1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_conv2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_conv3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_conv_transpose1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_conv_transpose2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_conv_transpose3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_cosine_embedding_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_cosine_similarity_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_cross_entropy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_ctc_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_dropout2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_dropout3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_dropout_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_elu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_embedding_bag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_embedding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_fractional_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_fractional_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_gaussian_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_gelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_glu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_grid_sample_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_group_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_hardshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_hardsigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_hardswish_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_hardtanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_hinge_embedding_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_huber_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_instance_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_interpolate_area_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_interpolate_bicubic_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_interpolate_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_interpolate_linear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_interpolate_nearest_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_interpolate_trilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_kl_div_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_l1_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_layer_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_leaky_relu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_linear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_local_response_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_logsigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_margin_ranking_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_max_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_max_unpool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_max_unpool1d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_max_unpool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_max_unpool2d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_max_unpool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_max_unpool3d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_mish_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_mse_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_multi_head_attention_forward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_multi_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_multilabel_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_normalize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_pad_circular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_pad_constant_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_pad_reflect_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_pad_replicate_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_pad_replicate_negative_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_pairwise_distance_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_pdist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_pixel_shuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_pixel_unshuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_poisson_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_prelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_relu6_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_relu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_rms_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_rrelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_selu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_silu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_smooth_l1_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_soft_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_softmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_softmin_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_softplus_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_softshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_softsign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_tanhshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_threshold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_triplet_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_unfold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_upsample_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nn_functional_upsample_nearest_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nonzero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_nonzero_static_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_norm_fro_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_norm_inf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_norm_nuc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_normal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_normal_in_place_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_normal_number_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_ones_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_ones_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_ormqr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_outer_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_pca_lowrank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_permute_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_permute_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_pinverse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_polar_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_polygamma_polygamma_n_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_polygamma_polygamma_n_1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_polygamma_polygamma_n_2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_polygamma_polygamma_n_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_polygamma_polygamma_n_4_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_positive_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_pow_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_put_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_qr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_quantile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_rad2deg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_rand_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_randint_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_randint_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_randn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_randn_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_ravel_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_real_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_reciprocal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_remainder_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_renorm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_repeat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_repeat_interleave_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_reshape_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_reshape_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_resize__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_resize_as__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_resolve_conj_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_resolve_neg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_roll_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_rot90_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_round_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_round_decimals_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_round_decimals_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_round_decimals_neg_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_rsqrt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_rsub_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_scalar_tensor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_scan_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_scatter_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_scatter_reduce_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_scatter_reduce_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_scatter_reduce_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_scatter_reduce_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_scatter_reduce_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_searchsorted_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_select_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_sgn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_short_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_sigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_sign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_signal_windows_bartlett_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_signal_windows_blackman_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_signal_windows_cosine_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_signal_windows_exponential_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_signal_windows_gaussian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_signal_windows_general_cosine_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_signal_windows_general_hamming_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_signal_windows_hamming_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_signal_windows_hann_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_signal_windows_kaiser_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_signal_windows_nuttall_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_signbit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_sin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_sinc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_sinh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_slice_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_slice_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_softmax_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_sort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_sparse_mm_reduce_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_sparse_sampled_addmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_airy_ai_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_bessel_j0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_bessel_j1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_bessel_y0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_bessel_y1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_chebyshev_polynomial_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_chebyshev_polynomial_u_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_chebyshev_polynomial_v_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_chebyshev_polynomial_w_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_entr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_erfcx_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_hermite_polynomial_h_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_hermite_polynomial_he_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_i0e_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_i1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_i1e_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_laguerre_polynomial_l_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_legendre_polynomial_p_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_log_ndtr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_modified_bessel_i0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_modified_bessel_i1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_modified_bessel_k0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_modified_bessel_k1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_ndtr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_ndtri_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_scaled_modified_bessel_k0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_scaled_modified_bessel_k1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_spherical_bessel_j0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_xlog1py_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_special_zeta_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_split_list_args_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_split_with_sizes_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_split_with_sizes_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_sqrt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_square_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_squeeze_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_squeeze_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_squeeze_multiple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_stack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_std_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_std_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_std_mean_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_std_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_stft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_sub_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_sum_to_size_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_svd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_svd_lowrank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_t_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_take_along_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_take_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_tan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_tanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_tensor_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_tensordot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_tile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_to_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_to_sparse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_topk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_trace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_transpose_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_transpose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_trapezoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_trapz_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_triangular_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_tril_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_triu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_true_divide_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_trunc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_unbind_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_unbind_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_unflatten_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_unfold_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_unfold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_uniform_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_unique_consecutive_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_unique_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_unsafe_chunk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_unsafe_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_unsqueeze_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_unsqueeze_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_var_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_var_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_var_mean_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_var_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_vdot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_view_as_complex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_view_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_view_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_view_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_vsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_vstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_where_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_while_loop_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_xlogy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_zero__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_zeros_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_fake_exhaustive_zeros_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_H_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_NumpyCatCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_NumpyCubeCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_NumpyMulCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_NumpyMulScalarCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_NumpyNMSCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_NumpyNonzeroCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_NumpySortCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_NumpySplitCopyCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_NumpyTakeCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_NumpyViewCopyCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_T_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive___getitem___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive___radd___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive___rdiv___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive___rmatmul___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive___rmod___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive___rmul___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive___rpow___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive___rsub___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive__batch_norm_with_update_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive__chunk_cat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive__native_batch_norm_legit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive__segment_reduce_lengths_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive__segment_reduce_offsets_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive__softmax_backward_data_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive__unsafe_masked_index_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive__unsafe_masked_index_put_accumulate_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive__upsample_bilinear2d_aa_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_abs_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_acos_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_acosh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_addbmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_addcdiv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_addcmul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_addmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_addmm_decomposed_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_addmv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_addr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_alias_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_all_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_allclose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_aminmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_angle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_any_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_arange_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_argmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_argmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_argsort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_argwhere_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_as_strided_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_as_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_as_strided_partial_views_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_as_strided_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_asin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_asinh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_atan2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_atan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_atanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_atleast_1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_atleast_2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_atleast_3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_baddbmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_bernoulli_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_bfloat16_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_block_diag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_bmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_bool_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_broadcast_shapes_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_broadcast_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_broadcast_to_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_bucketize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_byte_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cartesian_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cauchy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cdist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cdouble_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_ceil_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cfloat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_chalf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_char_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cholesky_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cholesky_inverse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cholesky_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_chunk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_clamp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_clamp_max_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_clamp_min_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_clone_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_column_stack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_combinations_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_complex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cond_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_conj_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_conj_physical_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_constant_pad_nd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_contiguous_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_copysign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_corrcoef_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cos_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cosh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_count_nonzero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cov_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cross_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cummax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cummin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cumprod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cumsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_cumulative_trapezoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_deg2rad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_diag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_diag_embed_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_diagflat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_diagonal_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_diagonal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_diagonal_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_diff_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_digamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_dist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_div_floor_rounding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_div_no_rounding_mode_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_div_trunc_rounding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_dot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_double_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_dsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_dstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_einsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_empty_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_empty_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_empty_permuted_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_empty_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_eq_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_equal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_erf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_erfc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_erfinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_exp2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_exp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_expand_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_expand_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_expand_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_expm1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_exponential_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_eye_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_fft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_fft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_fftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_fftshift_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_hfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_hfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_hfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_ifft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_ifft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_ifftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_ifftshift_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_ihfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_ihfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_ihfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_irfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_irfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_irfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_rfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_rfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fft_rfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_flatten_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_flex_attention_backward_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_flex_attention_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_flip_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fliplr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_flipud_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_float_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_float_power_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_floor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_floor_divide_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_fmod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_frac_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_frexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_full_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_full_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_gather_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_ge_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_geometric_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_geqrf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_gradient_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_grid_sampler_2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_gt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_half_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_heaviside_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_histc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_histogram_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_histogramdd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_hsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_hstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_hypot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_i0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_igamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_igammac_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_index_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_index_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_index_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_index_put_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_index_reduce_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_index_reduce_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_index_reduce_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_index_reduce_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_index_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inner_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_H_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_NumpyCatCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_NumpyCubeCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_NumpyMulCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_NumpyMulScalarCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_NumpyNMSCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_NumpyNonzeroCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_NumpySortCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_NumpySplitCopyCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_NumpyTakeCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_NumpyViewCopyCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_T_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace___getitem___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace___radd___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace___rdiv___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace___rmatmul___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace___rmod___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace___rmul___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace___rpow___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace___rsub___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace__batch_norm_with_update_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace__chunk_cat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace__native_batch_norm_legit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace__segment_reduce_lengths_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace__segment_reduce_offsets_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace__softmax_backward_data_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace__unsafe_masked_index_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace__unsafe_masked_index_put_accumulate_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace__upsample_bilinear2d_aa_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_abs_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_acos_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_acosh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_addbmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_addcdiv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_addcmul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_addmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_addmm_decomposed_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_addmv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_addr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_alias_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_all_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_allclose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_aminmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_angle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_any_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_arange_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_argmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_argmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_argsort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_argwhere_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_as_strided_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_as_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_as_strided_partial_views_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_as_strided_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_asin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_asinh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_atan2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_atan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_atanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_atleast_1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_atleast_2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_atleast_3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_baddbmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_bernoulli_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_bfloat16_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_block_diag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_bmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_bool_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_broadcast_shapes_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_broadcast_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_broadcast_to_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_bucketize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_byte_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cartesian_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cauchy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cdist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cdouble_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_ceil_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cfloat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_chalf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_char_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cholesky_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cholesky_inverse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cholesky_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_chunk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_clamp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_clamp_max_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_clamp_min_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_clone_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_column_stack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_combinations_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_complex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_conj_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_conj_physical_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_constant_pad_nd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_contiguous_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_copysign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_corrcoef_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cos_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cosh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_count_nonzero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cov_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cross_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cummax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cummin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cumprod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cumsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_cumulative_trapezoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_deg2rad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_diag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_diag_embed_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_diagflat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_diagonal_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_diagonal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_diagonal_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_diff_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_digamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_dist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_div_floor_rounding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_div_no_rounding_mode_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_div_trunc_rounding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_dot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_double_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_dsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_dstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_einsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_empty_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_empty_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_empty_permuted_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_empty_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_eq_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_equal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_erf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_erfc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_erfinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_exp2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_exp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_expand_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_expand_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_expand_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_expm1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_exponential_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_eye_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_fft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_fft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_fftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_fftshift_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_hfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_hfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_hfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_ifft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_ifft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_ifftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_ifftshift_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_ihfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_ihfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_ihfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_irfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_irfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_irfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_rfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_rfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fft_rfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_flatten_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_flip_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fliplr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_flipud_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_float_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_float_power_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_floor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_floor_divide_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_fmod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_frac_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_frexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_full_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_full_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_gather_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_ge_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_geometric_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_geqrf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_gradient_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_grid_sampler_2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_gt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_half_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_heaviside_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_histc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_histogram_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_histogramdd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_hsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_hstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_hypot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_i0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_igamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_igammac_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_index_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_index_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_index_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_index_put_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_index_reduce_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_index_reduce_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_index_reduce_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_index_reduce_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_index_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_inner_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_int_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_isclose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_isfinite_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_isin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_isinf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_isnan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_isneginf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_isposinf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_isreal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_item_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_jiterator_2inputs_2outputs_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_jiterator_4inputs_with_extra_args_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_jiterator_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_jiterator_binary_return_by_ref_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_jiterator_unary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_kron_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_kthvalue_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_ldexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_le_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_lerp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_lgamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_cholesky_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_cholesky_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_cond_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_cross_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_det_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_diagonal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_eig_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_eigh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_eigvals_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_eigvalsh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_householder_product_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_inv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_inv_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_ldl_factor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_ldl_factor_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_ldl_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_lstsq_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_lstsq_grad_oriented_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_lu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_lu_factor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_lu_factor_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_lu_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_matrix_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_matrix_power_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_matrix_rank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_matrix_rank_hermitian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_multi_dot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_norm_subgradients_at_zero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_pinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_pinv_hermitian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_pinv_singular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_qr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_slogdet_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_solve_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_solve_triangular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_svd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_svdvals_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_tensorinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_tensorsolve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_vander_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_vecdot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linalg_vector_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linspace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_linspace_tensor_overload_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_log10_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_log1p_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_log2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_log_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_log_normal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_log_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_log_softmax_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_logaddexp2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_logaddexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_logcumsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_logdet_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_logical_and_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_logical_not_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_logical_or_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_logical_xor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_logit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_logspace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_logspace_tensor_overload_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_logsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_long_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_lt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_lu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_lu_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_lu_unpack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_mH_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_mT_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_argmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_argmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_cumprod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_cumsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_log_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_logaddexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_logsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_median_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_normalize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_softmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_std_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_masked_var_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_matmul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_matrix_exp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_max_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_max_pool2d_with_indices_backward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_max_reduction_no_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_max_reduction_with_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_maximum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_median_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_meshgrid_list_of_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_meshgrid_variadic_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_min_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_min_reduction_no_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_min_reduction_with_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_minimum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_mm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_mode_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_movedim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_msort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_mul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_multinomial_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_mv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nan_to_num_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nanmean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nanmedian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nanquantile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nansum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_narrow_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_narrow_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_native_batch_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_native_dropout_backward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_native_layer_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_ne_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_neg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_new_empty_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_new_empty_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_new_full_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_new_ones_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_new_zeros_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nextafter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_alpha_dropout_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_avg_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_avg_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_avg_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_batch_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_binary_cross_entropy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_celu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_channel_shuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_conv1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_conv2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_conv3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_conv_transpose1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_conv_transpose2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_conv_transpose3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_cosine_embedding_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_cosine_similarity_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_cross_entropy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_ctc_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_dropout2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_dropout3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_dropout_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_elu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_embedding_bag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_embedding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_fractional_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_fractional_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_gaussian_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_gelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_glu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_grid_sample_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_group_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_hardshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_hardsigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_hardswish_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_hardtanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_hinge_embedding_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_huber_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_instance_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_interpolate_area_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_interpolate_bicubic_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_interpolate_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_interpolate_linear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_interpolate_nearest_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_interpolate_trilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_kl_div_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_l1_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_layer_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_leaky_relu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_linear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_local_response_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_logsigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_margin_ranking_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_max_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_max_unpool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_max_unpool1d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_max_unpool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_max_unpool2d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_max_unpool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_max_unpool3d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_mish_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_mse_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_multi_head_attention_forward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_multi_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_multilabel_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_normalize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_pad_circular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_pad_constant_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_pad_reflect_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_pad_replicate_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_pad_replicate_negative_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_pairwise_distance_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_pdist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_pixel_shuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_pixel_unshuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_poisson_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_prelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_relu6_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_relu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_rms_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_rrelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_selu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_silu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_smooth_l1_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_soft_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_softmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_softmin_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_softplus_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_softshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_softsign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_tanhshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_threshold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_triplet_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_unfold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_upsample_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nn_functional_upsample_nearest_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nonzero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_nonzero_static_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_norm_fro_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_norm_inf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_norm_nuc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_normal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_normal_in_place_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_normal_number_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_ones_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_ones_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_ormqr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_outer_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_pca_lowrank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_permute_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_permute_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_pinverse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_polar_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_polygamma_polygamma_n_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_polygamma_polygamma_n_1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_polygamma_polygamma_n_2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_polygamma_polygamma_n_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_polygamma_polygamma_n_4_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_positive_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_pow_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_put_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_qr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_quantile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_rad2deg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_rand_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_randint_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_randint_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_randn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_randn_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_ravel_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_real_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_reciprocal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_remainder_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_renorm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_repeat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_repeat_interleave_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_reshape_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_reshape_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_resize__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_resize_as__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_resolve_conj_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_resolve_neg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_roll_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_rot90_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_round_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_round_decimals_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_round_decimals_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_round_decimals_neg_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_rsqrt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_rsub_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_scalar_tensor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_scatter_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_scatter_reduce_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_scatter_reduce_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_scatter_reduce_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_scatter_reduce_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_scatter_reduce_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_searchsorted_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_select_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_sgn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_short_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_sigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_sign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_signal_windows_bartlett_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_signal_windows_blackman_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_signal_windows_cosine_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_signal_windows_exponential_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_signal_windows_gaussian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_signal_windows_general_cosine_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_signal_windows_general_hamming_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_signal_windows_hamming_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_signal_windows_hann_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_signal_windows_kaiser_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_signal_windows_nuttall_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_signbit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_sin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_sinc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_sinh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_slice_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_slice_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_softmax_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_sort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_sparse_mm_reduce_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_sparse_sampled_addmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_airy_ai_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_bessel_j0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_bessel_j1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_bessel_y0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_bessel_y1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_chebyshev_polynomial_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_chebyshev_polynomial_u_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_chebyshev_polynomial_v_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_chebyshev_polynomial_w_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_entr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_erfcx_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_hermite_polynomial_h_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_hermite_polynomial_he_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_i0e_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_i1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_i1e_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_laguerre_polynomial_l_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_legendre_polynomial_p_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_log_ndtr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_modified_bessel_i0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_modified_bessel_i1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_modified_bessel_k0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_modified_bessel_k1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_ndtr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_ndtri_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_scaled_modified_bessel_k0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_scaled_modified_bessel_k1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_spherical_bessel_j0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_xlog1py_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_special_zeta_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_split_list_args_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_split_with_sizes_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_split_with_sizes_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_sqrt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_square_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_squeeze_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_squeeze_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_squeeze_multiple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_stack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_std_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_std_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_std_mean_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_std_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_stft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_sub_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_sum_to_size_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_svd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_svd_lowrank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_t_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_take_along_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_take_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_tan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_tanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_tensor_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_tensordot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_tile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_to_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_to_sparse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_topk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_trace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_transpose_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_transpose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_trapezoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_trapz_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_triangular_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_tril_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_triu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_true_divide_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_trunc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_unbind_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_unbind_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_unflatten_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_unfold_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_unfold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_uniform_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_unique_consecutive_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_unique_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_unsafe_chunk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_unsafe_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_unsqueeze_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_unsqueeze_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_var_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_var_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_var_mean_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_var_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_vdot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_view_as_complex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_view_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_view_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_view_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_vsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_vstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_where_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_xlogy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_zero__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_zeros_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_inplace_zeros_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_int_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_invoke_quant_packed_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_invoke_quant_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_invoke_subgraph_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_isclose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_isfinite_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_isin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_isinf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_isnan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_isneginf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_isposinf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_isreal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_item_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_jiterator_2inputs_2outputs_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_jiterator_4inputs_with_extra_args_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_jiterator_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_jiterator_binary_return_by_ref_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_jiterator_unary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_kron_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_kthvalue_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_ldexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_le_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_lerp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_lgamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_cholesky_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_cholesky_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_cond_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_cross_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_det_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_diagonal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_eig_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_eigh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_eigvals_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_eigvalsh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_householder_product_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_inv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_inv_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_ldl_factor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_ldl_factor_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_ldl_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_lstsq_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_lstsq_grad_oriented_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_lu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_lu_factor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_lu_factor_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_lu_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_matrix_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_matrix_power_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_matrix_rank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_matrix_rank_hermitian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_multi_dot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_norm_subgradients_at_zero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_pinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_pinv_hermitian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_pinv_singular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_qr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_slogdet_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_solve_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_solve_triangular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_svd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_svdvals_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_tensorinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_tensorsolve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_vander_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_vecdot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linalg_vector_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linspace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_linspace_tensor_overload_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_log10_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_log1p_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_log2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_log_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_log_normal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_log_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_log_softmax_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_logaddexp2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_logaddexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_logcumsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_logdet_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_logical_and_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_logical_not_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_logical_or_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_logical_xor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_logit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_logspace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_logspace_tensor_overload_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_logsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_long_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_lt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_lu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_lu_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_lu_unpack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_mH_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_mT_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_map_nested_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_map_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_map_triple_nested_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_argmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_argmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_cumprod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_cumsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_log_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_logaddexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_logsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_median_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_normalize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_softmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_std_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_masked_var_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_matmul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_matrix_exp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_max_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_max_pool2d_with_indices_backward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_max_reduction_no_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_max_reduction_with_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_maximum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_median_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_meshgrid_list_of_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_meshgrid_variadic_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_min_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_min_reduction_no_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_min_reduction_with_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_minimum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_mm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_mode_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_movedim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_msort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_mul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_multinomial_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_mv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nan_to_num_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nanmean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nanmedian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nanquantile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nansum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_narrow_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_narrow_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_native_batch_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_native_dropout_backward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_native_layer_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_ne_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_neg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_new_empty_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_new_empty_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_new_full_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_new_ones_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_new_zeros_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nextafter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_alpha_dropout_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_avg_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_avg_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_avg_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_batch_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_binary_cross_entropy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_celu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_channel_shuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_conv1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_conv2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_conv3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_conv_transpose1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_conv_transpose2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_conv_transpose3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_cosine_embedding_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_cosine_similarity_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_cross_entropy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_ctc_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_dropout2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_dropout3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_dropout_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_elu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_embedding_bag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_embedding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_fractional_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_fractional_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_gaussian_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_gelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_glu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_grid_sample_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_group_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_hardshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_hardsigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_hardswish_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_hardtanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_hinge_embedding_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_huber_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_instance_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_interpolate_area_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_interpolate_bicubic_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_interpolate_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_interpolate_linear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_interpolate_nearest_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_interpolate_trilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_kl_div_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_l1_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_layer_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_leaky_relu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_linear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_local_response_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_logsigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_margin_ranking_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_max_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_max_unpool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_max_unpool1d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_max_unpool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_max_unpool2d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_max_unpool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_max_unpool3d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_mish_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_mse_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_multi_head_attention_forward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_multi_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_multilabel_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_normalize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_pad_circular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_pad_constant_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_pad_reflect_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_pad_replicate_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_pad_replicate_negative_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_pairwise_distance_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_pdist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_pixel_shuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_pixel_unshuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_poisson_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_prelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_relu6_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_relu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_rms_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_rrelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_selu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_silu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_smooth_l1_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_soft_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_softmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_softmin_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_softplus_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_softshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_softsign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_tanhshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_threshold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_triplet_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_unfold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_upsample_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nn_functional_upsample_nearest_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nonzero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_nonzero_static_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_norm_fro_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_norm_inf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_norm_nuc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_normal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_normal_in_place_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_normal_number_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_ones_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_ones_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_ormqr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_H_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_NumpyCatCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_NumpyCubeCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_NumpyMulCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_NumpyMulScalarCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_NumpyNMSCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_NumpyNonzeroCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_NumpySortCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_NumpySplitCopyCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_NumpyTakeCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_NumpyViewCopyCustomOp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_T_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out___getitem___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out___radd___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out___rdiv___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out___rmatmul___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out___rmod___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out___rmul___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out___rpow___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out___rsub___cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out__batch_norm_with_update_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out__chunk_cat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out__native_batch_norm_legit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out__segment_reduce_lengths_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out__segment_reduce_offsets_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out__softmax_backward_data_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out__unsafe_masked_index_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out__unsafe_masked_index_put_accumulate_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out__upsample_bilinear2d_aa_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_abs_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_acos_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_acosh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_addbmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_addcdiv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_addcmul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_addmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_addmm_decomposed_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_addmv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_addr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_alias_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_all_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_allclose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_aminmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_angle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_any_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_arange_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_argmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_argmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_argsort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_argwhere_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_as_strided_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_as_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_as_strided_partial_views_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_as_strided_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_asin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_asinh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_atan2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_atan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_atanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_atleast_1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_atleast_2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_atleast_3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_baddbmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_bernoulli_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_bfloat16_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_block_diag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_bmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_bool_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_broadcast_shapes_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_broadcast_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_broadcast_to_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_bucketize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_byte_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cartesian_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cauchy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cdist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cdouble_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_ceil_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cfloat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_chalf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_char_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cholesky_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cholesky_inverse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cholesky_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_chunk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_clamp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_clamp_max_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_clamp_min_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_clone_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_column_stack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_combinations_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_complex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_conj_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_conj_physical_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_constant_pad_nd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_contiguous_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_copysign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_corrcoef_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cos_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cosh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_count_nonzero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cov_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cross_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cummax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cummin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cumprod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cumsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_cumulative_trapezoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_deg2rad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_diag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_diag_embed_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_diagflat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_diagonal_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_diagonal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_diagonal_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_diff_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_digamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_dist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_div_floor_rounding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_div_no_rounding_mode_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_div_trunc_rounding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_dot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_double_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_dsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_dstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_einsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_empty_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_empty_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_empty_permuted_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_empty_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_eq_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_equal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_erf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_erfc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_erfinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_exp2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_exp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_expand_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_expand_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_expand_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_expm1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_exponential_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_eye_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_fft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_fft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_fftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_fftshift_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_hfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_hfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_hfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_ifft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_ifft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_ifftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_ifftshift_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_ihfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_ihfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_ihfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_irfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_irfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_irfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_rfft2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_rfft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fft_rfftn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_flatten_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_flip_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fliplr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_flipud_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_float_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_float_power_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_floor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_floor_divide_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_fmod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_frac_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_frexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_full_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_full_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_gather_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_ge_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_geometric_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_geqrf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_gradient_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_grid_sampler_2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_gt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_half_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_heaviside_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_histc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_histogram_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_histogramdd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_hsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_hstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_hypot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_i0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_igamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_igammac_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_index_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_index_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_index_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_index_put_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_index_reduce_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_index_reduce_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_index_reduce_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_index_reduce_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_index_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_inner_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_int_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_isclose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_isfinite_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_isin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_isinf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_isnan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_isneginf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_isposinf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_isreal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_item_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_jiterator_2inputs_2outputs_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_jiterator_4inputs_with_extra_args_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_jiterator_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_jiterator_binary_return_by_ref_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_jiterator_unary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_kron_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_kthvalue_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_ldexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_le_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_lerp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_lgamma_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_cholesky_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_cholesky_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_cond_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_cross_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_det_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_diagonal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_eig_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_eigh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_eigvals_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_eigvalsh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_householder_product_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_inv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_inv_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_ldl_factor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_ldl_factor_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_ldl_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_lstsq_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_lstsq_grad_oriented_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_lu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_lu_factor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_lu_factor_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_lu_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_matrix_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_matrix_power_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_matrix_rank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_matrix_rank_hermitian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_multi_dot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_norm_subgradients_at_zero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_pinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_pinv_hermitian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_pinv_singular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_qr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_slogdet_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_solve_ex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_solve_triangular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_svd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_svdvals_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_tensorinv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_tensorsolve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_vander_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_vecdot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linalg_vector_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linspace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_linspace_tensor_overload_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_log10_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_log1p_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_log2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_log_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_log_normal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_log_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_log_softmax_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_logaddexp2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_logaddexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_logcumsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_logdet_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_logical_and_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_logical_not_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_logical_or_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_logical_xor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_logit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_logspace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_logspace_tensor_overload_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_logsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_long_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_lt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_lu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_lu_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_lu_unpack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_mH_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_mT_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_argmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_argmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_cumprod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_cumsum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_fill_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_log_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_logaddexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_logsumexp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_median_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_normalize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_softmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_std_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_masked_var_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_matmul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_matrix_exp_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_max_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_max_pool2d_with_indices_backward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_max_reduction_no_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_max_reduction_with_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_maximum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_median_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_meshgrid_list_of_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_meshgrid_variadic_tensors_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_min_binary_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_min_reduction_no_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_min_reduction_with_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_minimum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_mm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_mode_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_movedim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_msort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_mul_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_multinomial_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_mv_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nan_to_num_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nanmean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nanmedian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nanquantile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nansum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_narrow_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_narrow_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_native_batch_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_native_dropout_backward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_native_layer_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_ne_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_neg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_new_empty_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_new_empty_strided_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_new_full_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_new_ones_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_new_zeros_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nextafter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_alpha_dropout_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_avg_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_avg_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_avg_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_batch_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_binary_cross_entropy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_celu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_channel_shuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_conv1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_conv2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_conv3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_conv_transpose1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_conv_transpose2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_conv_transpose3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_cosine_embedding_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_cosine_similarity_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_cross_entropy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_ctc_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_dropout2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_dropout3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_dropout_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_elu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_embedding_bag_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_embedding_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_fractional_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_fractional_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_gaussian_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_gelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_glu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_grid_sample_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_group_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_hardshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_hardsigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_hardswish_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_hardtanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_hinge_embedding_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_huber_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_instance_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_interpolate_area_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_interpolate_bicubic_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_interpolate_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_interpolate_linear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_interpolate_nearest_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_interpolate_trilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_kl_div_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_l1_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_layer_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_leaky_relu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_linear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_local_response_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_logsigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_margin_ranking_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_max_pool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_max_pool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_max_pool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_max_unpool1d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_max_unpool1d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_max_unpool2d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_max_unpool2d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_max_unpool3d_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_max_unpool3d_grad_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_mish_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_mse_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_multi_head_attention_forward_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_multi_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_multilabel_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_normalize_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_pad_circular_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_pad_constant_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_pad_reflect_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_pad_replicate_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_pad_replicate_negative_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_pairwise_distance_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_pdist_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_pixel_shuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_pixel_unshuffle_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_poisson_nll_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_prelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_relu6_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_relu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_rms_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_rrelu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_selu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_silu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_smooth_l1_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_soft_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_softmin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_softmin_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_softplus_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_softshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_softsign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_tanhshrink_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_threshold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_triplet_margin_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_unfold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_upsample_bilinear_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nn_functional_upsample_nearest_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nonzero_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_nonzero_static_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_norm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_norm_fro_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_norm_inf_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_norm_nuc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_normal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_normal_in_place_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_normal_number_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_ones_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_ones_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_ormqr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_outer_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_pca_lowrank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_permute_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_permute_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_pinverse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_polar_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_polygamma_polygamma_n_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_polygamma_polygamma_n_1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_polygamma_polygamma_n_2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_polygamma_polygamma_n_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_polygamma_polygamma_n_4_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_positive_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_pow_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_put_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_qr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_quantile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_rad2deg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_rand_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_randint_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_randint_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_randn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_randn_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_ravel_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_real_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_reciprocal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_remainder_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_renorm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_repeat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_repeat_interleave_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_reshape_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_reshape_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_resize__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_resize_as__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_resolve_conj_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_resolve_neg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_roll_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_rot90_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_round_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_round_decimals_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_round_decimals_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_round_decimals_neg_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_rsqrt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_rsub_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_scalar_tensor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_scatter_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_scatter_reduce_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_scatter_reduce_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_scatter_reduce_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_scatter_reduce_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_scatter_reduce_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_searchsorted_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_select_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_sgn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_short_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_sigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_sign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_signal_windows_bartlett_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_signal_windows_blackman_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_signal_windows_cosine_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_signal_windows_exponential_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_signal_windows_gaussian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_signal_windows_general_cosine_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_signal_windows_general_hamming_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_signal_windows_hamming_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_signal_windows_hann_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_signal_windows_kaiser_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_signal_windows_nuttall_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_signbit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_sin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_sinc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_sinh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_slice_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_slice_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_softmax_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_sort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_sparse_mm_reduce_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_sparse_sampled_addmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_airy_ai_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_bessel_j0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_bessel_j1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_bessel_y0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_bessel_y1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_chebyshev_polynomial_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_chebyshev_polynomial_u_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_chebyshev_polynomial_v_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_chebyshev_polynomial_w_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_entr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_erfcx_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_hermite_polynomial_h_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_hermite_polynomial_he_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_i0e_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_i1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_i1e_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_laguerre_polynomial_l_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_legendre_polynomial_p_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_log_ndtr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_modified_bessel_i0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_modified_bessel_i1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_modified_bessel_k0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_modified_bessel_k1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_ndtr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_ndtri_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_scaled_modified_bessel_k0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_scaled_modified_bessel_k1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_spherical_bessel_j0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_xlog1py_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_special_zeta_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_split_list_args_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_split_with_sizes_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_split_with_sizes_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_sqrt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_square_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_squeeze_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_squeeze_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_squeeze_multiple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_stack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_std_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_std_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_std_mean_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_std_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_stft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_sub_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_sum_to_size_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_svd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_svd_lowrank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_t_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_take_along_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_take_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_tan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_tanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_tensor_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_tensordot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_tile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_to_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_to_sparse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_topk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_trace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_transpose_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_transpose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_trapezoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_trapz_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_triangular_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_tril_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_triu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_true_divide_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_trunc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_unbind_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_unbind_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_unflatten_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_unfold_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_unfold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_uniform_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_unique_consecutive_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_unique_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_unsafe_chunk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_unsafe_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_unsqueeze_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_unsqueeze_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_var_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_var_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_var_mean_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_var_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_vdot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_view_as_complex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_view_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_view_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_view_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_vsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_vstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_where_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_xlogy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_zero__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_zeros_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_out_zeros_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_outer_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_pca_lowrank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_permute_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_permute_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_pinverse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_polar_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_polygamma_polygamma_n_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_polygamma_polygamma_n_1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_polygamma_polygamma_n_2_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_polygamma_polygamma_n_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_polygamma_polygamma_n_4_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_positive_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_pow_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_put_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_qr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_quantile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_rad2deg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_rand_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_randint_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_randint_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_randn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_randn_like_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_ravel_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_real_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_reciprocal_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_remainder_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_renorm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_repeat_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_repeat_interleave_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_reshape_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_reshape_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_resize__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_resize_as__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_resolve_conj_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_resolve_neg_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_roll_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_rot90_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_round_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_round_decimals_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_round_decimals_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_round_decimals_neg_3_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_rsqrt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_rsub_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_scalar_tensor_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_scan_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_scatter_add_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_scatter_reduce_amax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_scatter_reduce_amin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_scatter_reduce_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_scatter_reduce_prod_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_scatter_reduce_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_searchsorted_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_select_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_select_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_sgn_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_short_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_sigmoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_sign_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_signal_windows_bartlett_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_signal_windows_blackman_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_signal_windows_cosine_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_signal_windows_exponential_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_signal_windows_gaussian_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_signal_windows_general_cosine_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_signal_windows_general_hamming_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_signal_windows_hamming_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_signal_windows_hann_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_signal_windows_kaiser_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_signal_windows_nuttall_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_signbit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_sin_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_sinc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_sinh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_slice_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_slice_scatter_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_softmax_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_softmax_with_dtype_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_sort_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_sparse_mm_reduce_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_sparse_sampled_addmm_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_airy_ai_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_bessel_j0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_bessel_j1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_bessel_y0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_bessel_y1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_chebyshev_polynomial_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_chebyshev_polynomial_u_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_chebyshev_polynomial_v_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_chebyshev_polynomial_w_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_entr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_erfcx_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_hermite_polynomial_h_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_hermite_polynomial_he_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_i0e_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_i1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_i1e_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_laguerre_polynomial_l_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_legendre_polynomial_p_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_log_ndtr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_modified_bessel_i0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_modified_bessel_i1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_modified_bessel_k0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_modified_bessel_k1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_ndtr_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_ndtri_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_scaled_modified_bessel_k0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_scaled_modified_bessel_k1_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_spherical_bessel_j0_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_xlog1py_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_special_zeta_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_split_list_args_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_split_with_sizes_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_split_with_sizes_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_sqrt_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_square_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_squeeze_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_squeeze_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_squeeze_multiple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_stack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_std_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_std_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_std_mean_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_std_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_stft_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_sub_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_sum_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_sum_to_size_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_svd_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_svd_lowrank_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_t_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_t_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_take_along_dim_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_take_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_tan_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_tanh_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_tensor_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_tensordot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_tile_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_to_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_to_sparse_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_topk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_trace_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_transpose_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_transpose_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_trapezoid_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_trapz_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_triangular_solve_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_tril_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_triu_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_true_divide_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_trunc_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_unbind_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_unbind_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_unflatten_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_unfold_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_unfold_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_uniform_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_unique_consecutive_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_unique_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_unsafe_chunk_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_unsafe_split_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_unsqueeze_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_unsqueeze_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_var_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_var_mean_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_var_mean_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_var_unbiased_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_vdot_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_view_as_complex_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_view_as_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_view_copy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_view_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_vsplit_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_vstack_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_where_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_while_loop_simple_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_xlogy_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_zero__cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_zeros_cpu_float32, test/test_proxy_tensor.py::TestProxyTensorOpInfoCPU::test_make_fx_symbolic_exhaustive_zeros_like_cpu_float32
2025-07-17T07:33:40.3566610Z 
2025-07-17T07:33:40.3567000Z Running inductor/test_torchinductor_opinfo 6/14 ... [2025-07-17 07:33:40.356530]
2025-07-17T07:33:40.3567480Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:33:40.3569300Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor_opinfo.py', '-m', 'not serial', '--shard-id=6', '--num-shards=14', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:33:40.356824]
2025-07-17T07:35:31.1571720Z 
2025-07-17T07:35:31.1572270Z inductor/test_aot_inductor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_1.1_9fc6b3235273d352_.log
2025-07-17T07:35:31.1861240Z Running 833 items in this shard: test/inductor/test_aot_inductor.py::AOTInductorLoggingTest::test_shape_env_reuse, test/inductor/test_aot_inductor.py::TestAOTInductorConfig::test_compile_standalone_package_cpp_already_true, test/inductor/test_aot_inductor.py::TestAOTInductorConfig::test_compile_standalone_package_cpp_false_raises, test/inductor/test_aot_inductor.py::TestAOTInductorConfig::test_compile_standalone_sets_package_cpp, test/inductor/test_aot_inductor.py::TestAOTInductorConfig::test_no_compile_standalone, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test__int_mm_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test__weight_int4pack_mm_m_32_n_64_q_group_32_num_groups_1_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test__weight_int4pack_mm_m_32_n_64_q_group_32_num_groups_2_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test__weight_int4pack_mm_m_32_n_64_q_group_64_num_groups_1_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test__weight_int4pack_mm_m_32_n_64_q_group_64_num_groups_2_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test__weight_int4pack_mm_with_scales_and_zeros_m_32_n_64_q_group_32_num_groups_1_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test__weight_int4pack_mm_with_scales_and_zeros_m_32_n_64_q_group_32_num_groups_2_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test__weight_int4pack_mm_with_scales_and_zeros_m_32_n_64_q_group_64_num_groups_1_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test__weight_int4pack_mm_with_scales_and_zeros_m_32_n_64_q_group_64_num_groups_2_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_add_complex_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_addmm_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_addmm_multiple_dynamic_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aliased_buffer_reuse_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_amp_fallback_random_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aot_inductor_consts_cpp_build_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aoti_constant_tensor_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aoti_constant_tensor_name_collision_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aoti_debug_printer_codegen_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aoti_debug_printer_cpp_kernel_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aoti_debug_printer_fp8_dtype_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aoti_debug_printer_sym_inputs_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aoti_debug_printer_user_defined_triton_kernel_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aoti_debug_printing_model_inputs_codegen_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aoti_profiler_enable_kernel_profile_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aoti_profiler_enable_kernel_profile_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aoti_runtime_asserts_backed_symint_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_aoti_runtime_asserts_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_assert_async_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_assert_tensor_meta_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_autotune_with_constant_folding_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_autotuning_args_reuse_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_backward_no_op_logging_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_bmm_multiple_dynamic_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_bool_input_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_boolean_indexing_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_buffer_mutation_1_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_buffer_mutation_2_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_buffer_mutation_3_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_buffer_mutation_4_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_buffer_mutation_and_force_mmap_weights_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_buffer_reuse_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_clamp_decomposition_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_composed_dynamic_size_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_mismatched_branch_output_dynamic_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_mismatched_branch_output_dynamic_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_nested_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_non_tensor_predicates_dynamic_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_non_tensor_predicates_dynamic_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_share_predicte_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_simple_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_symint_input_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_unbacked_symint_closure_dynamic_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_unbacked_symint_closure_dynamic_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_use_buffers_from_outer_scope_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_with_multiple_outputs_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_with_outer_code_before_after_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_with_parameters_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_cond_with_reinterpret_view_inputs_outputs_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_consecutive_compiles_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_constant_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_constant_folding_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_constant_folding_with_update_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_constant_original_fqn_and_dtype_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_constant_type_propagation_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_conv3d_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_conv_freezing_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_convolution_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_deconv_freezing_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_dup_unbacked_sym_decl_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_dup_unbacked_sym_decl_with_refinement_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_duplicate_constant_folding_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_duplicated_params_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_dynamic_cat_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_dynamic_scalar_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_dynamic_smem_above_default_limit_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_embedding_bag_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_empty_cat_dtype_promotion_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_empty_constant_folding_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_empty_graph_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_extract_constants_map_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_fake_tensor_device_validation_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_fallback_kernel_with_symexpr_output_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_fallback_mem_leak_fix_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_fft_c2c_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_fill__fallback_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_foreach_multiple_dynamic_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_fp8_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_fp8_view_of_param_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_fqn_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_free_inactive_buffer_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_freezing_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_fx_gm_return_tuple_validation_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_index_put_fallback_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_index_put_with_none_index_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_inf_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_input_codegen_with_sympy_expr_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_int_list_input_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_issue_140766_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_large_dynamic_dim_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_large_grid_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_large_mmaped_weights_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_large_weight_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_linear_dynamic_maxautotune_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_linear_freezing_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_load_package_multiple_gpus_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_masked_select_dynamic_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_misaligned_input_1_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_misaligned_input_2_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_misc_1_max_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_misc_1_max_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_missing_cubin_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_missing_output_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_model_modified_weights_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_multi_device_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_multiple_output_alias_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_nan_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_narrow_fallback_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_nested_tensor_from_jagged_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_no_args_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_non_contiguous_output_alias_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_non_default_gpu_device_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_non_tensor_input_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_none_args_aot_codegen_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_normal_functional_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_on_gpu_device1_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_output_misaligned_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_output_path_1_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_output_path_2_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_pad_fallback_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_poi_multiple_dynamic_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_profile_benchmark_harness_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_proxy_executor_abs_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_proxy_executor_hann_cpu, 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test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_repeated_user_defined_triton_kernel_embed_kernel_binary_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_replicate_on_devices_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_return_constant_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_return_view_constant_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_reuse_kernel_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_reuse_kernel_dynamic_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_run_with_grad_enabled_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_runtime_checks_complex_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_runtime_checks_cpu, 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test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_sdpa_2_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_sdpa_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_seq_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_shifted_constraint_ranges_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_simple_dynamic_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_simple_embed_kernel_binary_False_max_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_simple_embed_kernel_binary_False_max_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_simple_embed_kernel_binary_True_max_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_simple_embed_kernel_binary_True_max_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_simple_multi_arch_embed_kernel_binary_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_simple_split_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_size_from_multi_output_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_size_with_unbacked_add_and_mul_expr_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_size_with_unbacked_add_expr_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_size_with_unbacked_add_expr_transitive_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_small_constant_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_so_without_weight_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_stft_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_stride_with_unbacked_expr_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_subclasses_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_sym_i64_input_codegen_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_symbool_item_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_symfloat_item_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_symint_item_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_sympy_cpp_printer_min_max_minmax0_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_sympy_cpp_printer_min_max_minmax1_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_torchvision_transforms_functional_tensor_resize_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_autotuning_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_dynamic_launcher_grid_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_dynamic_launcher_grid_infer_from_tensor_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_dynamic_grid_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_dynamic_shape_with_div_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_equal_to_1_arg_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_equal_to_1_float_arg_dynamic_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_equal_to_1_float_arg_dynamic_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_extern_kernel_arg_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_1_num_dims_1_dynamic_False_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_1_num_dims_1_dynamic_False_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_1_num_dims_1_dynamic_True_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_1_num_dims_1_dynamic_True_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_1_num_dims_2_dynamic_False_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_1_num_dims_2_dynamic_False_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_1_num_dims_2_dynamic_True_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_1_num_dims_2_dynamic_True_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_2_num_dims_1_dynamic_False_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_2_num_dims_1_dynamic_False_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_2_num_dims_1_dynamic_True_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_2_num_dims_1_dynamic_True_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_2_num_dims_2_dynamic_False_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_2_num_dims_2_dynamic_False_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_2_num_dims_2_dynamic_True_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_2_num_dims_2_dynamic_True_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_3_num_dims_1_dynamic_False_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_3_num_dims_1_dynamic_False_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_3_num_dims_1_dynamic_True_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_3_num_dims_1_dynamic_True_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_3_num_dims_2_dynamic_False_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_3_num_dims_2_dynamic_False_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_3_num_dims_2_dynamic_True_autotune_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_grid_type_3_num_dims_2_dynamic_True_autotune_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_multi_output_arg_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_on_device_tma_dynamic_False_tma_version_new_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_on_device_tma_dynamic_False_tma_version_old_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_on_device_tma_dynamic_True_tma_version_new_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_on_device_tma_dynamic_True_tma_version_old_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_reinterpret_view_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_reinterpret_view_mem_leak_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_sympy_expr_arg_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_sympy_fn_like_arg_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_tma_descriptor_1d_dynamic_False_tma_version_new_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_tma_descriptor_1d_dynamic_False_tma_version_old_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_tma_descriptor_1d_dynamic_True_tma_version_new_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_tma_descriptor_1d_dynamic_True_tma_version_old_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_tma_descriptor_2d_dynamic_False_tma_version_new_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_tma_descriptor_2d_dynamic_False_tma_version_old_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_tma_descriptor_2d_dynamic_True_tma_version_new_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_tma_descriptor_2d_dynamic_True_tma_version_old_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_unbacked_symint_in_grid_dynamic_False_autotuning_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_unbacked_symint_in_grid_dynamic_False_autotuning_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_unbacked_symint_in_grid_dynamic_True_autotuning_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_unbacked_symint_in_grid_dynamic_True_autotuning_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_weird_param_order_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_with_none_input_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_kernel_with_none_inputs_and_equal_to_1_arg_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_mutated_autotuning_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_triton_next_power_of_2_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_unbacked_equals_input_size_runtime_assertion_mark_unbacked_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_unbacked_equals_input_size_runtime_assertion_mark_unbacked_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_update_constant_buffer_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_update_inactive_constant_buffer_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_update_user_managed_buffer_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_using_model_name_for_files_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_view_outputs_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_weight_on_disk_legacy_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_nested_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_simple_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_with_conv_dynamic_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_with_conv_dynamic_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_with_mixed_device_dynamic_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_with_mixed_device_dynamic_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_with_outer_buffers_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_with_outer_code_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_with_parameters_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_with_pytree_inputs_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_with_sym_expr_cond_dynamic_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_with_sym_expr_cond_dynamic_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_with_unbacked_symint_closure_dynamic_False_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_while_loop_with_unbacked_symint_closure_dynamic_True_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_with_cudagraphs_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_with_no_triton_profiler_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_with_offset_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_with_profiler_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_zero_grid_with_backed_symbols_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_zero_grid_with_unbacked_symbols_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_zero_size_buffer_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleCpu::test_zero_size_weight_cpu, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test__int_mm_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test__weight_int4pack_mm_m_32_n_64_q_group_32_num_groups_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test__weight_int4pack_mm_m_32_n_64_q_group_32_num_groups_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test__weight_int4pack_mm_m_32_n_64_q_group_64_num_groups_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test__weight_int4pack_mm_m_32_n_64_q_group_64_num_groups_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test__weight_int4pack_mm_with_scales_and_zeros_m_32_n_64_q_group_32_num_groups_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test__weight_int4pack_mm_with_scales_and_zeros_m_32_n_64_q_group_32_num_groups_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test__weight_int4pack_mm_with_scales_and_zeros_m_32_n_64_q_group_64_num_groups_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test__weight_int4pack_mm_with_scales_and_zeros_m_32_n_64_q_group_64_num_groups_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_add_complex_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_addmm_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_addmm_multiple_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aliased_buffer_reuse_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_amp_fallback_random_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aot_inductor_consts_cpp_build_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aoti_constant_tensor_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aoti_constant_tensor_name_collision_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aoti_debug_printer_codegen_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aoti_debug_printer_cpp_kernel_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aoti_debug_printer_fp8_dtype_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aoti_debug_printer_sym_inputs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aoti_debug_printer_user_defined_triton_kernel_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aoti_debug_printing_model_inputs_codegen_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aoti_profiler_enable_kernel_profile_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aoti_profiler_enable_kernel_profile_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aoti_runtime_asserts_backed_symint_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_aoti_runtime_asserts_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_assert_async_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_assert_tensor_meta_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_autotune_with_constant_folding_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_autotuning_args_reuse_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_backward_no_op_logging_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_bmm_multiple_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_bool_input_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_boolean_indexing_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_buffer_mutation_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_buffer_mutation_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_buffer_mutation_3_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_buffer_mutation_4_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_buffer_mutation_and_force_mmap_weights_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_buffer_reuse_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_clamp_decomposition_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_composed_dynamic_size_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_mismatched_branch_output_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_mismatched_branch_output_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_nested_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_non_tensor_predicates_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_non_tensor_predicates_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_share_predicte_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_simple_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_symint_input_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_unbacked_symint_closure_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_unbacked_symint_closure_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_use_buffers_from_outer_scope_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_with_multiple_outputs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_with_outer_code_before_after_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_with_parameters_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_cond_with_reinterpret_view_inputs_outputs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_consecutive_compiles_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_constant_folding_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_constant_folding_with_update_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_constant_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_constant_original_fqn_and_dtype_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_constant_type_propagation_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_conv3d_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_conv_freezing_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_convolution_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_deconv_freezing_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_dup_unbacked_sym_decl_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_dup_unbacked_sym_decl_with_refinement_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_duplicate_constant_folding_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_duplicated_params_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_dynamic_cat_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_dynamic_scalar_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_dynamic_smem_above_default_limit_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_embedding_bag_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_empty_cat_dtype_promotion_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_empty_constant_folding_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_empty_graph_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_extract_constants_map_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_fake_tensor_device_validation_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_fallback_kernel_with_symexpr_output_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_fallback_mem_leak_fix_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_fft_c2c_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_fill__fallback_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_foreach_multiple_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_fp8_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_fp8_view_of_param_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_fqn_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_free_inactive_buffer_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_freezing_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_fx_gm_return_tuple_validation_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_index_put_fallback_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_index_put_with_none_index_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_inf_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_input_codegen_with_sympy_expr_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_int_list_input_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_issue_140766_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_large_dynamic_dim_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_large_grid_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_large_mmaped_weights_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_large_weight_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_linear_dynamic_maxautotune_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_linear_freezing_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_load_package_multiple_gpus_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_masked_select_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_misaligned_input_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_misaligned_input_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_misc_1_max_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_misc_1_max_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_missing_cubin_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_missing_output_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_model_modified_weights_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_multi_device_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_multiple_output_alias_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_nan_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_narrow_fallback_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_nested_tensor_from_jagged_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_no_args_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_non_contiguous_output_alias_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_non_default_gpu_device_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_non_tensor_input_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_none_args_aot_codegen_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_normal_functional_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_on_gpu_device1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_output_misaligned_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_output_path_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_output_path_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_pad_fallback_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_poi_multiple_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_profile_benchmark_harness_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_proxy_executor_abs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_proxy_executor_hann_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_proxy_executor_permute_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_proxy_executor_squeeze_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_pytree_inputs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_quanatized_int8_linear_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_quantized_linear_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_repeat_interleave_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_repeat_output_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_repeated_calling_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_repeated_user_defined_triton_kernel_embed_kernel_binary_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_repeated_user_defined_triton_kernel_embed_kernel_binary_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_replicate_on_devices_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_return_constant_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_return_view_constant_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_reuse_kernel_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_reuse_kernel_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_run_with_grad_enabled_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_runtime_checks_complex_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_runtime_checks_device_type_failed_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_runtime_checks_dtype_failed_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_runtime_checks_fp8_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_runtime_checks_large_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_runtime_checks_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_runtime_checks_shape_failed_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_same_backing_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_scaled_dot_product_efficient_attention_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_scatter_fallback_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_scatter_reduce_fallback_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_sdpa_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_sdpa_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_seq_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_shifted_constraint_ranges_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_simple_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_simple_embed_kernel_binary_False_max_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_simple_embed_kernel_binary_False_max_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_simple_embed_kernel_binary_True_max_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_simple_embed_kernel_binary_True_max_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_simple_multi_arch_embed_kernel_binary_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_simple_split_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_size_from_multi_output_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_size_with_unbacked_add_and_mul_expr_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_size_with_unbacked_add_expr_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_size_with_unbacked_add_expr_transitive_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_small_constant_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_so_without_weight_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_stft_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_stride_with_unbacked_expr_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_subclasses_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_sym_i64_input_codegen_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_symbool_item_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_symfloat_item_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_symint_item_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_sympy_cpp_printer_min_max_minmax0_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_sympy_cpp_printer_min_max_minmax1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_torchvision_transforms_functional_tensor_resize_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_autotuning_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_dynamic_launcher_grid_infer_from_tensor_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_dynamic_launcher_grid_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_dynamic_grid_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_dynamic_shape_with_div_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_equal_to_1_arg_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_equal_to_1_float_arg_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_equal_to_1_float_arg_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_extern_kernel_arg_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_1_num_dims_1_dynamic_False_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_1_num_dims_1_dynamic_False_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_1_num_dims_1_dynamic_True_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_1_num_dims_1_dynamic_True_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_1_num_dims_2_dynamic_False_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_1_num_dims_2_dynamic_False_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_1_num_dims_2_dynamic_True_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_1_num_dims_2_dynamic_True_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_2_num_dims_1_dynamic_False_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_2_num_dims_1_dynamic_False_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_2_num_dims_1_dynamic_True_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_2_num_dims_1_dynamic_True_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_2_num_dims_2_dynamic_False_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_2_num_dims_2_dynamic_False_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_2_num_dims_2_dynamic_True_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_2_num_dims_2_dynamic_True_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_3_num_dims_1_dynamic_False_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_3_num_dims_1_dynamic_False_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_3_num_dims_1_dynamic_True_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_3_num_dims_1_dynamic_True_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_3_num_dims_2_dynamic_False_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_3_num_dims_2_dynamic_False_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_3_num_dims_2_dynamic_True_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_grid_type_3_num_dims_2_dynamic_True_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_multi_output_arg_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_on_device_tma_dynamic_False_tma_version_new_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_on_device_tma_dynamic_False_tma_version_old_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_on_device_tma_dynamic_True_tma_version_new_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_on_device_tma_dynamic_True_tma_version_old_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_reinterpret_view_mem_leak_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_reinterpret_view_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_sympy_expr_arg_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_sympy_fn_like_arg_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_tma_descriptor_1d_dynamic_False_tma_version_new_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_tma_descriptor_1d_dynamic_False_tma_version_old_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_tma_descriptor_1d_dynamic_True_tma_version_new_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_tma_descriptor_1d_dynamic_True_tma_version_old_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_tma_descriptor_2d_dynamic_False_tma_version_new_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_tma_descriptor_2d_dynamic_False_tma_version_old_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_tma_descriptor_2d_dynamic_True_tma_version_new_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_tma_descriptor_2d_dynamic_True_tma_version_old_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_unbacked_symint_in_grid_dynamic_False_autotuning_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_unbacked_symint_in_grid_dynamic_False_autotuning_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_unbacked_symint_in_grid_dynamic_True_autotuning_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_unbacked_symint_in_grid_dynamic_True_autotuning_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_weird_param_order_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_with_none_input_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_kernel_with_none_inputs_and_equal_to_1_arg_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_mutated_autotuning_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_triton_next_power_of_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_unbacked_equals_input_size_runtime_assertion_mark_unbacked_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_unbacked_equals_input_size_runtime_assertion_mark_unbacked_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_update_constant_buffer_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_update_inactive_constant_buffer_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_update_user_managed_buffer_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_using_model_name_for_files_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_view_outputs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_weight_on_disk_legacy_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_nested_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_simple_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_with_conv_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_with_conv_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_with_mixed_device_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_with_mixed_device_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_with_outer_buffers_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_with_outer_code_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_with_parameters_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_with_pytree_inputs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_with_sym_expr_cond_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_with_sym_expr_cond_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_with_unbacked_symint_closure_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_while_loop_with_unbacked_symint_closure_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_with_cudagraphs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_with_no_triton_profiler_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_with_offset_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_with_profiler_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_zero_grid_with_backed_symbols_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_zero_grid_with_unbacked_symbols_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_zero_size_buffer_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleGpu::test_zero_size_weight_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test__int_mm_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test__weight_int4pack_mm_m_32_n_64_q_group_32_num_groups_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test__weight_int4pack_mm_m_32_n_64_q_group_32_num_groups_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test__weight_int4pack_mm_m_32_n_64_q_group_64_num_groups_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test__weight_int4pack_mm_m_32_n_64_q_group_64_num_groups_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test__weight_int4pack_mm_with_scales_and_zeros_m_32_n_64_q_group_32_num_groups_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test__weight_int4pack_mm_with_scales_and_zeros_m_32_n_64_q_group_32_num_groups_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test__weight_int4pack_mm_with_scales_and_zeros_m_32_n_64_q_group_64_num_groups_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test__weight_int4pack_mm_with_scales_and_zeros_m_32_n_64_q_group_64_num_groups_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_add_complex_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_addmm_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_addmm_multiple_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aliased_buffer_reuse_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_amp_fallback_random_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aot_inductor_consts_cpp_build_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aoti_constant_tensor_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aoti_constant_tensor_name_collision_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aoti_debug_printer_codegen_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aoti_debug_printer_cpp_kernel_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aoti_debug_printer_fp8_dtype_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aoti_debug_printer_sym_inputs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aoti_debug_printer_user_defined_triton_kernel_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aoti_debug_printing_model_inputs_codegen_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aoti_profiler_enable_kernel_profile_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aoti_profiler_enable_kernel_profile_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aoti_runtime_asserts_backed_symint_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_aoti_runtime_asserts_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_assert_async_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_assert_tensor_meta_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_autotune_with_constant_folding_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_autotuning_args_reuse_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_backward_no_op_logging_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_bmm_multiple_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_bool_input_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_boolean_indexing_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_buffer_mutation_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_buffer_mutation_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_buffer_mutation_3_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_buffer_mutation_4_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_buffer_mutation_and_force_mmap_weights_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_buffer_reuse_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_clamp_decomposition_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_composed_dynamic_size_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_mismatched_branch_output_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_mismatched_branch_output_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_nested_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_non_tensor_predicates_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_non_tensor_predicates_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_share_predicte_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_simple_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_symint_input_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_unbacked_symint_closure_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_unbacked_symint_closure_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_use_buffers_from_outer_scope_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_with_multiple_outputs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_with_outer_code_before_after_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_with_parameters_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_cond_with_reinterpret_view_inputs_outputs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_consecutive_compiles_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_constant_folding_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_constant_folding_with_update_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_constant_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_constant_original_fqn_and_dtype_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_constant_type_propagation_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_conv3d_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_conv_freezing_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_convolution_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_deconv_freezing_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_dup_unbacked_sym_decl_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_dup_unbacked_sym_decl_with_refinement_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_duplicate_constant_folding_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_duplicated_params_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_dynamic_cat_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_dynamic_scalar_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_dynamic_smem_above_default_limit_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_embedding_bag_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_empty_cat_dtype_promotion_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_empty_constant_folding_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_empty_graph_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_extract_constants_map_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_fake_tensor_device_validation_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_fallback_kernel_with_symexpr_output_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_fallback_mem_leak_fix_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_fft_c2c_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_fill__fallback_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_foreach_multiple_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_fp8_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_fp8_view_of_param_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_fqn_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_free_inactive_buffer_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_freezing_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_fx_gm_return_tuple_validation_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_index_put_fallback_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_index_put_with_none_index_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_inf_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_input_codegen_with_sympy_expr_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_int_list_input_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_issue_140766_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_large_dynamic_dim_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_large_grid_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_large_mmaped_weights_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_large_weight_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_linear_dynamic_maxautotune_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_linear_freezing_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_load_package_multiple_gpus_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_masked_select_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_misaligned_input_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_misaligned_input_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_misc_1_max_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_misc_1_max_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_missing_cubin_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_missing_output_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_model_modified_weights_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_multi_device_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_multiple_output_alias_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_nan_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_narrow_fallback_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_nested_tensor_from_jagged_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_no_args_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_non_contiguous_output_alias_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_non_default_gpu_device_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_non_tensor_input_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_none_args_aot_codegen_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_normal_functional_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_on_gpu_device1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_output_misaligned_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_output_path_1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_output_path_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_pad_fallback_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_poi_multiple_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_profile_benchmark_harness_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_proxy_executor_abs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_proxy_executor_hann_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_proxy_executor_permute_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_proxy_executor_squeeze_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_pytree_inputs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_quanatized_int8_linear_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_quantized_linear_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_repeat_interleave_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_repeat_output_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_repeated_calling_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_repeated_user_defined_triton_kernel_embed_kernel_binary_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_repeated_user_defined_triton_kernel_embed_kernel_binary_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_replicate_on_devices_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_return_constant_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_return_view_constant_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_reuse_kernel_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_reuse_kernel_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_run_with_grad_enabled_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_runtime_checks_complex_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_runtime_checks_device_type_failed_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_runtime_checks_dtype_failed_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_runtime_checks_fp8_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_runtime_checks_large_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_runtime_checks_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_runtime_checks_shape_failed_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_same_backing_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_scaled_dot_product_efficient_attention_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_scatter_fallback_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_scatter_reduce_fallback_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_sdpa_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_sdpa_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_seq_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_shifted_constraint_ranges_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_simple_dynamic_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_simple_embed_kernel_binary_False_max_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_simple_embed_kernel_binary_False_max_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_simple_embed_kernel_binary_True_max_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_simple_embed_kernel_binary_True_max_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_simple_multi_arch_embed_kernel_binary_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_simple_split_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_size_from_multi_output_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_size_with_unbacked_add_and_mul_expr_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_size_with_unbacked_add_expr_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_size_with_unbacked_add_expr_transitive_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_small_constant_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_so_without_weight_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_stft_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_stride_with_unbacked_expr_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_subclasses_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_sym_i64_input_codegen_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_symbool_item_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_symfloat_item_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_symint_item_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_sympy_cpp_printer_min_max_minmax0_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_sympy_cpp_printer_min_max_minmax1_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_torchvision_transforms_functional_tensor_resize_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_autotuning_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_dynamic_launcher_grid_infer_from_tensor_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_dynamic_launcher_grid_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_dynamic_grid_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_dynamic_shape_with_div_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_equal_to_1_arg_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_equal_to_1_float_arg_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_equal_to_1_float_arg_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_extern_kernel_arg_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_1_num_dims_1_dynamic_False_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_1_num_dims_1_dynamic_False_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_1_num_dims_1_dynamic_True_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_1_num_dims_1_dynamic_True_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_1_num_dims_2_dynamic_False_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_1_num_dims_2_dynamic_False_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_1_num_dims_2_dynamic_True_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_1_num_dims_2_dynamic_True_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_2_num_dims_1_dynamic_False_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_2_num_dims_1_dynamic_False_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_2_num_dims_1_dynamic_True_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_2_num_dims_1_dynamic_True_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_2_num_dims_2_dynamic_False_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_2_num_dims_2_dynamic_False_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_2_num_dims_2_dynamic_True_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_2_num_dims_2_dynamic_True_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_3_num_dims_1_dynamic_False_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_3_num_dims_1_dynamic_False_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_3_num_dims_1_dynamic_True_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_3_num_dims_1_dynamic_True_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_3_num_dims_2_dynamic_False_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_3_num_dims_2_dynamic_False_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_3_num_dims_2_dynamic_True_autotune_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_grid_type_3_num_dims_2_dynamic_True_autotune_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_multi_output_arg_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_on_device_tma_dynamic_False_tma_version_new_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_on_device_tma_dynamic_False_tma_version_old_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_on_device_tma_dynamic_True_tma_version_new_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_on_device_tma_dynamic_True_tma_version_old_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_reinterpret_view_mem_leak_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_reinterpret_view_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_sympy_expr_arg_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_sympy_fn_like_arg_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_tma_descriptor_1d_dynamic_False_tma_version_new_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_tma_descriptor_1d_dynamic_False_tma_version_old_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_tma_descriptor_1d_dynamic_True_tma_version_new_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_tma_descriptor_1d_dynamic_True_tma_version_old_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_tma_descriptor_2d_dynamic_False_tma_version_new_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_tma_descriptor_2d_dynamic_False_tma_version_old_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_tma_descriptor_2d_dynamic_True_tma_version_new_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_tma_descriptor_2d_dynamic_True_tma_version_old_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_unbacked_symint_in_grid_dynamic_False_autotuning_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_unbacked_symint_in_grid_dynamic_False_autotuning_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_unbacked_symint_in_grid_dynamic_True_autotuning_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_unbacked_symint_in_grid_dynamic_True_autotuning_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_weird_param_order_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_with_none_input_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_kernel_with_none_inputs_and_equal_to_1_arg_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_mutated_autotuning_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_triton_next_power_of_2_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_unbacked_equals_input_size_runtime_assertion_mark_unbacked_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_unbacked_equals_input_size_runtime_assertion_mark_unbacked_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_update_constant_buffer_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_update_inactive_constant_buffer_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_update_user_managed_buffer_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_using_model_name_for_files_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_view_outputs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_weight_on_disk_legacy_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_nested_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_simple_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_with_conv_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_with_conv_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_with_mixed_device_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_with_mixed_device_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_with_outer_buffers_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_with_outer_code_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_with_parameters_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_with_pytree_inputs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_with_sym_expr_cond_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_with_sym_expr_cond_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_with_unbacked_symint_closure_dynamic_False_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_while_loop_with_unbacked_symint_closure_dynamic_True_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_with_cudagraphs_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_with_no_triton_profiler_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_with_offset_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_with_profiler_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_zero_grid_with_backed_symbols_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_zero_grid_with_unbacked_symbols_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_zero_size_buffer_mps, test/inductor/test_aot_inductor.py::AOTInductorTestABICompatibleMps::test_zero_size_weight_mps
2025-07-17T07:35:31.2097680Z 
2025-07-17T07:35:33.2656780Z Running inductor/test_torchinductor_opinfo 7/14 ... [2025-07-17 07:35:33.265319]
2025-07-17T07:35:33.2658670Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:35:33.2663500Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor_opinfo.py', '-m', 'not serial', '--shard-id=7', '--num-shards=14', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:35:33.265821]
2025-07-17T07:36:18.6049050Z 
2025-07-17T07:36:18.6050050Z inductor/test_torchinductor_opinfo 2/14 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_opinfo_2.14_48e01ec5afbe521e_.log
2025-07-17T07:36:18.6124600Z Running 249 items in this shard: test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_T_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_T_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___rand___cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___rsub___cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive__chunk_cat_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_add_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addmm_decomposed_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_argwhere_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_argwhere_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_as_strided_copy_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_as_strided_partial_views_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_asin_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_asinh_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atan_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atanh_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_bitwise_and_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_bitwise_not_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_bitwise_right_shift_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_bmm_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_broadcast_tensors_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_broadcast_to_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_broadcast_to_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_bucketize_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_byte_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cat_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cdouble_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_char_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_clamp_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_complex_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_conj_physical_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_contiguous_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cosh_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_count_nonzero_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cov_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cross_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cummin_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cumprod_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cumsum_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cumsum_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diag_embed_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diagonal_scatter_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_digamma_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_dot_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_double_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_empty_like_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_empty_strided_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_eq_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_eq_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_erf_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_exp2_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expand_as_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expand_as_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expand_copy_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expand_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expand_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expm1_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_exponential_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_fftn_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_hfft2_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_hfft_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_ifft_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_ihfft_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_ihfftn_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_rfft_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_rfftn_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fliplr_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fmax_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fmin_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fmin_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_full_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_full_like_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_geometric_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_grid_sampler_2d_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_heaviside_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_histc_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_hsplit_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_hstack_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_i0_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_igammac_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_copy_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_reduce_amax_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_reduce_mean_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_reduce_mean_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_reduce_prod_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_reduce_prod_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_select_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_inner_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_int_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_int_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_isnan_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_jiterator_4inputs_with_extra_args_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_jiterator_binary_return_by_ref_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_kron_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_le_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_lgamma_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_lgamma_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_linalg_cross_cpu_float64, 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test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unfold_copy_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unsafe_split_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unsqueeze_copy_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unsqueeze_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unsqueeze_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_view_as_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_view_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_vstack_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_where_cpu_float32
2025-07-17T07:36:18.6195490Z 
2025-07-17T07:36:20.6351170Z Running inductor/test_torchinductor_opinfo 11/14 ... [2025-07-17 07:36:20.634885]
2025-07-17T07:36:20.6353310Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:36:20.6359260Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchinductor_opinfo.py', '-m', 'not serial', '--shard-id=11', '--num-shards=14', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:36:20.635201]
2025-07-17T07:43:02.2216290Z 
2025-07-17T07:43:02.2217320Z inductor/test_torchinductor_opinfo 6/14 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_opinfo_6.14_3b0b72390afaf633_.log
2025-07-17T07:43:02.2295420Z Running 263 items in this shard: test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_H_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_T_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___getitem___cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___radd___cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___rand___cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___rmatmul___cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___rmul___cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___rpow___cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive__segment_reduce_lengths_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive__segment_reduce_lengths_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive__segment_reduce_offsets_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive__unsafe_masked_index_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addcmul_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addmm_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_all_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_all_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_amax_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_angle_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_argsort_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_as_strided_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_as_strided_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atan2_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atan_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atanh_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atleast_1d_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atleast_1d_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atleast_2d_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atleast_2d_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_bitwise_not_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_bmm_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_broadcast_to_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cartesian_prod_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cartesian_prod_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cfloat_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_chalf_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_char_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_char_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cholesky_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cholesky_inverse_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_chunk_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_clamp_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_clamp_min_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_combinations_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_constant_pad_nd_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_contiguous_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cos_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cos_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cosh_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cosh_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_count_nonzero_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_count_nonzero_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cross_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cross_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cumprod_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cumsum_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cumulative_trapezoid_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cumulative_trapezoid_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_deg2rad_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diag_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diag_embed_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diagflat_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diagflat_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diagonal_copy_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diagonal_scatter_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diagonal_scatter_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diagonal_scatter_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diff_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_double_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_dstack_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_empty_like_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_empty_permuted_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_eq_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_erf_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_erf_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_erfinv_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_exp2_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expand_as_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expand_as_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expand_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expm1_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_fftn_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_ifftn_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_irfft_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_irfftn_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_rfft_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_rfftn_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fill_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_flatten_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_flatten_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_flip_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_flip_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_flip_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fliplr_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fliplr_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_float_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_float_power_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_full_like_cpu_uint16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_gather_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_ge_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_ge_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_geometric_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_gt_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_histogram_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_hsplit_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_add_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_copy_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_put_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_reduce_mean_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_reduce_prod_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_inner_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_isin_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_isposinf_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_item_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_item_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_item_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_jiterator_2inputs_2outputs_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_jiterator_binary_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_jiterator_binary_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_kthvalue_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_lcm_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_ldexp_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_le_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_lerp_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_linalg_cholesky_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_linalg_eigvals_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_linalg_lu_factor_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_linalg_vecdot_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_log2_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_logical_and_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_logical_not_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_logical_or_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_logspace_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_logspace_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_logspace_tensor_overload_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_logspace_tensor_overload_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_mH_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_masked_amax_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_masked_argmin_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_masked_cumsum_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_masked_cumsum_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_matrix_exp_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_max_binary_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_max_reduction_no_dim_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_maximum_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_maximum_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_mean_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_min_reduction_with_dim_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_minimum_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_mm_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_mm_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_mul_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_mv_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nansum_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_narrow_copy_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_native_dropout_backward_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_ne_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_neg_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_new_full_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_new_ones_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_adaptive_max_pool1d_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_celu_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_conv1d_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_conv2d_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_conv_transpose3d_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_cross_entropy_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_gaussian_nll_loss_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_gelu_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_group_norm_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_hardtanh_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_interpolate_area_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_interpolate_nearest-exact_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_interpolate_nearest_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_max_pool1d_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_mse_loss_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_mse_loss_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_multi_margin_loss_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_nll_loss_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pad_circular_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pad_reflect_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pad_replicate_negative_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pairwise_distance_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pairwise_distance_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pixel_unshuffle_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_prelu_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_relu6_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_relu_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_rms_norm_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_triplet_margin_loss_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_triplet_margin_with_distance_loss_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_upsample_bilinear_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_ones_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_outer_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_permute_copy_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_polar_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_polygamma_polygamma_n_1_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_pow_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_rad2deg_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_randint_like_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_reshape_as_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_resize__cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_rot90_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_round_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_round_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_round_decimals_0_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_scatter_add_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_scatter_reduce_amax_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_scatter_reduce_amin_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_scatter_reduce_prod_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_scatter_reduce_sum_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_scatter_reduce_sum_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_searchsorted_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_short_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_sign_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_sin_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_sinh_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_airy_ai_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_bessel_j0_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_bessel_j0_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_bessel_j1_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_bessel_y0_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_chebyshev_polynomial_u_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_chebyshev_polynomial_v_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_hermite_polynomial_he_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_hermite_polynomial_he_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_i1_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_polygamma_special_polygamma_n_0_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_scaled_modified_bessel_k0_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_scaled_modified_bessel_k1_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_shifted_chebyshev_polynomial_t_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_shifted_chebyshev_polynomial_u_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_zeta_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_split_list_args_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_sqrt_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_std_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_std_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_sub_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_sum_to_size_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_take_along_dim_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_take_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_take_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_tan_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_tile_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_to_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_topk_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_trace_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_trapz_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_true_divide_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unbind_copy_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unbind_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unflatten_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unique_consecutive_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unique_consecutive_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unique_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unravel_index_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unsqueeze_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_var_unbiased_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_vdot_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_vdot_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_view_as_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_vsplit_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_xlogy_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_xlogy_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_zeros_cpu_bool
2025-07-17T07:43:02.2371070Z 
2025-07-17T07:43:04.8659480Z Running inductor/test_static_cuda_launcher 1/1 ... [2025-07-17 07:43:04.865727]
2025-07-17T07:43:04.8660550Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:43:04.8662010Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_static_cuda_launcher.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:43:04.866038]
2025-07-17T07:43:07.5699390Z 
2025-07-17T07:43:07.5700330Z inductor/test_static_cuda_launcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_static_cuda_launcher_1.1_340e0b5e4a50d73e_.log
2025-07-17T07:43:07.5705430Z Running 18 items in this shard: test/inductor/test_static_cuda_launcher.py::TestStaticCudaLauncher::test_basic, test/inductor/test_static_cuda_launcher.py::TestStaticCudaLauncher::test_basic_1arg, test/inductor/test_static_cuda_launcher.py::TestStaticCudaLauncher::test_constexpr, test/inductor/test_static_cuda_launcher.py::TestStaticCudaLauncher::test_floats, test/inductor/test_static_cuda_launcher.py::TestStaticCudaLauncher::test_high_shared_mem, test/inductor/test_static_cuda_launcher.py::TestStaticCudaLauncher::test_implied_constant, test/inductor/test_static_cuda_launcher.py::TestStaticCudaLauncher::test_kernel_empty_tensor, test/inductor/test_static_cuda_launcher.py::TestStaticCudaLauncher::test_kernel_many_args, test/inductor/test_static_cuda_launcher.py::TestStaticCudaLauncher::test_kernel_no_args, test/inductor/test_static_cuda_launcher.py::TestStaticCudaLauncher::test_signed_integers, test/inductor/test_static_cuda_launcher.py::TestStaticCudaLauncher::test_too_high_shared_mem, test/inductor/test_static_cuda_launcher.py::TestStaticCudaLauncher::test_unsigned_integers, test/inductor/test_static_cuda_launcher.py::TestStaticTritonCompileResult::test_any, test/inductor/test_static_cuda_launcher.py::TestStaticTritonCompileResult::test_basic_compile, test/inductor/test_static_cuda_launcher.py::TestStaticTritonCompileResult::test_disable_static_cuda_launcher, test/inductor/test_static_cuda_launcher.py::TestStaticTritonCompileResult::test_empty_tensor, test/inductor/test_static_cuda_launcher.py::TestStaticTritonCompileResult::test_incompatible_code, test/inductor/test_static_cuda_launcher.py::TestStaticTritonCompileResult::test_static_launch_user_defined_triton_kernels
2025-07-17T07:43:07.5710060Z 
2025-07-17T07:43:09.5971760Z Running inductor/test_utils 1/1 ... [2025-07-17 07:43:09.595854]
2025-07-17T07:43:09.5973130Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:43:09.5979880Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:43:09.596156]
2025-07-17T07:43:11.8152410Z 
2025-07-17T07:43:11.8154310Z inductor/test_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_utils_1.1_684152f528b3dc32_.log
2025-07-17T07:43:11.8156300Z Running 7 items in this shard: test/inductor/test_utils.py::TestUtilsCPU::testSympySubs_cpu, test/inductor/test_utils.py::TestUtilsCPU::test_flops_fx_cpu, test/inductor/test_utils.py::TestUtilsCPU::test_get_device_tflops_cpu_bfloat16, test/inductor/test_utils.py::TestUtilsCPU::test_get_device_tflops_cpu_float16, test/inductor/test_utils.py::TestUtilsCPU::test_get_device_tflops_cpu_float32, test/inductor/test_utils.py::TestUtilsCPU::test_sympy_str_cpu, test/inductor/test_utils.py::TestUtilsCPU::test_zip_schema_cpu
2025-07-17T07:43:11.8157730Z 
2025-07-17T07:43:13.8069680Z Running dynamo/test_subgraphs 1/1 ... [2025-07-17 07:43:13.806758]
2025-07-17T07:43:13.8070140Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:43:13.8071450Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_subgraphs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:43:13.807044]
2025-07-17T07:43:19.5502400Z 
2025-07-17T07:43:19.5503210Z dynamo/test_subgraphs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_subgraphs_1.1_8de083fc190c00cb_.log
2025-07-17T07:43:19.5511550Z Running 44 items in this shard: test/dynamo/test_subgraphs.py::SubGraphTests::test_capi_call1, test/dynamo/test_subgraphs.py::SubGraphTests::test_capi_call2, test/dynamo/test_subgraphs.py::SubGraphTests::test_capi_call3, test/dynamo/test_subgraphs.py::SubGraphTests::test_control_flow1, test/dynamo/test_subgraphs.py::SubGraphTests::test_control_flow2, test/dynamo/test_subgraphs.py::SubGraphTests::test_control_flow3, test/dynamo/test_subgraphs.py::SubGraphTests::test_control_flow4, test/dynamo/test_subgraphs.py::SubGraphTests::test_control_flow5, test/dynamo/test_subgraphs.py::SubGraphTests::test_dynamic_duck_size, test/dynamo/test_subgraphs.py::SubGraphTests::test_dynamic_getitem, test/dynamo/test_subgraphs.py::SubGraphTests::test_dynamic_kwarg, test/dynamo/test_subgraphs.py::SubGraphTests::test_dynamic_order_dependence, test/dynamo/test_subgraphs.py::SubGraphTests::test_dynamic_zero_inference, test/dynamo/test_subgraphs.py::SubGraphTests::test_enumerate_not_break_graph, test/dynamo/test_subgraphs.py::SubGraphTests::test_extended_args, test/dynamo/test_subgraphs.py::SubGraphTests::test_graph_break_on_item, test/dynamo/test_subgraphs.py::SubGraphTests::test_indirect_unsupported1, test/dynamo/test_subgraphs.py::SubGraphTests::test_indirect_unsupported2, test/dynamo/test_subgraphs.py::SubGraphTests::test_indirect_unsupported3, test/dynamo/test_subgraphs.py::SubGraphTests::test_multigraph, test/dynamo/test_subgraphs.py::SubGraphTests::test_no_graph_break_on_item, test/dynamo/test_subgraphs.py::SubGraphTests::test_pop_after_resume, test/dynamo/test_subgraphs.py::SubGraphTests::test_restore_range, test/dynamo/test_subgraphs.py::SubGraphTests::test_restore_range_iter, test/dynamo/test_subgraphs.py::SubGraphTests::test_restore_state, test/dynamo/test_subgraphs.py::SubGraphTests::test_resume1, test/dynamo/test_subgraphs.py::SubGraphTests::test_resume2, test/dynamo/test_subgraphs.py::SubGraphTests::test_resume3, test/dynamo/test_subgraphs.py::SubGraphTests::test_resume4, test/dynamo/test_subgraphs.py::SubGraphTests::test_resume5, test/dynamo/test_subgraphs.py::SubGraphTests::test_resume_freevars, test/dynamo/test_subgraphs.py::SubGraphTests::test_resume_paths_join, test/dynamo/test_subgraphs.py::SubGraphTests::test_resume_tuple_iterator, test/dynamo/test_subgraphs.py::SubGraphTests::test_resume_with_no_grad1, test/dynamo/test_subgraphs.py::SubGraphTests::test_resume_with_no_grad2, test/dynamo/test_subgraphs.py::SubGraphTests::test_resume_with_no_grad3, test/dynamo/test_subgraphs.py::SubGraphTests::test_stack_state1, test/dynamo/test_subgraphs.py::SubGraphTests::test_stack_state2, test/dynamo/test_subgraphs.py::SubGraphTests::test_start1, test/dynamo/test_subgraphs.py::SubGraphTests::test_start2, test/dynamo/test_subgraphs.py::SubGraphTests::test_start3, test/dynamo/test_subgraphs.py::SubGraphTests::test_start4, test/dynamo/test_subgraphs.py::SubGraphTests::test_tuple_iterator_mutate, test/dynamo/test_subgraphs.py::SubGraphTests::test_tuple_iterator_return
2025-07-17T07:43:19.5519280Z 
2025-07-17T07:43:21.5505710Z Running dynamo/test_reconstruct 1/1 ... [2025-07-17 07:43:21.550407]
2025-07-17T07:43:21.5506520Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:43:21.5508530Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_reconstruct.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:43:21.550708]
2025-07-17T07:43:24.7848570Z 
2025-07-17T07:43:24.7849180Z dynamo/test_reconstruct 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_reconstruct_1.1_e0fbea578ee22c4e_.log
2025-07-17T07:43:24.7853290Z Running 16 items in this shard: test/dynamo/test_reconstruct.py::ReconstructTest::test_ConstDict_clear_reconstruct, test/dynamo/test_reconstruct.py::ReconstructTest::test_ConstDict_del_reconstruct, test/dynamo/test_reconstruct.py::ReconstructTest::test_ConstDict_get_reconstruct, test/dynamo/test_reconstruct.py::ReconstructTest::test_ConstDict_optimize_reconstruct, test/dynamo/test_reconstruct.py::ReconstructTest::test_ConstDict_pop_reconstruct, test/dynamo/test_reconstruct.py::ReconstructTest::test_ConstDict_popitem_reconstruct, test/dynamo/test_reconstruct.py::ReconstructTest::test_ConstDict_popitem_reconstruct_graph_break, test/dynamo/test_reconstruct.py::ReconstructTest::test_create_dict_reconstruct, test/dynamo/test_reconstruct.py::ReconstructTest::test_functional_call_reconstruct, test/dynamo/test_reconstruct.py::ReconstructTest::test_functional_call_reconstruct_2, test/dynamo/test_reconstruct.py::ReconstructTest::test_graph_break_in_wrapped_nested_function, test/dynamo/test_reconstruct.py::ReconstructTest::test_graph_break_in_wrapped_skipped_function, test/dynamo/test_reconstruct.py::ReconstructTest::test_graph_break_in_wrapped_user_function, test/dynamo/test_reconstruct.py::ReconstructTest::test_graph_break_in_wrapped_user_method, test/dynamo/test_reconstruct.py::ReconstructTest::test_tma_experimental_reconstruct, test/dynamo/test_reconstruct.py::ReconstructTest::test_tma_stable_reconstruct
2025-07-17T07:43:24.7857040Z 
2025-07-17T07:43:26.7845730Z Running inductor/test_subgraph_choice 1/1 ... [2025-07-17 07:43:26.784346]
2025-07-17T07:43:26.7846590Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:43:26.7848010Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_subgraph_choice.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:43:26.784663]
2025-07-17T07:43:29.3075230Z 
2025-07-17T07:43:29.3075960Z inductor/test_subgraph_choice 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_subgraph_choice_1.1_169747e6774b3a7d_.log
2025-07-17T07:43:29.3076460Z 
2025-07-17T07:43:31.3713480Z Running dynamo/test_dicts 1/1 ... [2025-07-17 07:43:31.371144]
2025-07-17T07:43:31.3714270Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:43:31.3716000Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_dicts.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:43:31.371447]
2025-07-17T07:43:37.2780540Z 
2025-07-17T07:43:37.2782160Z dynamo/test_dicts 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_dicts_1.1_b3e3ca62e51d4d63_.log
2025-07-17T07:43:37.2799990Z Running 105 items in this shard: test/dynamo/test_dicts.py::DictTests::test_builtin_ior_, test/dynamo/test_dicts.py::DictTests::test_builtin_or_with_diff_keys, test/dynamo/test_dicts.py::DictTests::test_builtin_or_with_invalid_types, test/dynamo/test_dicts.py::DictTests::test_builtin_or_with_same_keys, test/dynamo/test_dicts.py::DictTests::test_contains_dunder_dict, test/dynamo/test_dicts.py::DictTests::test_contains_module_dunder_dict, test/dynamo/test_dicts.py::DictTests::test_custom_iter_dict, test/dynamo/test_dicts.py::DictTests::test_custom_keys_iter_dict, test/dynamo/test_dicts.py::DictTests::test_dict_construction_from_mapping_proxy, test/dynamo/test_dicts.py::DictTests::test_dict_contains, test/dynamo/test_dicts.py::DictTests::test_dict_copy_alias, test/dynamo/test_dicts.py::DictTests::test_dict_guard_on_keys_order, test/dynamo/test_dicts.py::DictTests::test_dict_guard_on_keys_order2, test/dynamo/test_dicts.py::DictTests::test_dict_iter, test/dynamo/test_dicts.py::DictTests::test_dict_keys_binop_op_and_, test/dynamo/test_dicts.py::DictTests::test_dict_keys_binop_op_or_, test/dynamo/test_dicts.py::DictTests::test_dict_keys_binop_op_sub, test/dynamo/test_dicts.py::DictTests::test_dict_keys_binop_op_xor, test/dynamo/test_dicts.py::DictTests::test_dict_keys_inplace_binop_op_iand, test/dynamo/test_dicts.py::DictTests::test_dict_keys_inplace_binop_op_ior, test/dynamo/test_dicts.py::DictTests::test_dict_keys_inplace_binop_op_isub, test/dynamo/test_dicts.py::DictTests::test_dict_keys_inplace_binop_op_ixor, test/dynamo/test_dicts.py::DictTests::test_dict_list_values, test/dynamo/test_dicts.py::DictTests::test_dict_mutation_side_effect, test/dynamo/test_dicts.py::DictTests::test_dict_namedtuple, test/dynamo/test_dicts.py::DictTests::test_dict_order_keys, test/dynamo/test_dicts.py::DictTests::test_dict_order_keys_modules, test/dynamo/test_dicts.py::DictTests::test_dict_order_keys_tensors, test/dynamo/test_dicts.py::DictTests::test_dict_reconstruct_keeps_original_order, test/dynamo/test_dicts.py::DictTests::test_dict_subclass_contains, test/dynamo/test_dicts.py::DictTests::test_dict_subclass_get_method, test/dynamo/test_dicts.py::DictTests::test_dict_subclass_initialization_in_graph, test/dynamo/test_dicts.py::DictTests::test_dict_subclass_instantiation, test/dynamo/test_dicts.py::DictTests::test_dict_subclass_instantiation_return, test/dynamo/test_dicts.py::DictTests::test_dict_subclass_local_mutation, test/dynamo/test_dicts.py::DictTests::test_dict_subclass_local_with_non_dict_method, test/dynamo/test_dicts.py::DictTests::test_dict_subclass_methods_fallback_mutation, test/dynamo/test_dicts.py::DictTests::test_dict_subclass_methods_fallback_readonly, test/dynamo/test_dicts.py::DictTests::test_dict_subclass_setitem, test/dynamo/test_dicts.py::DictTests::test_dict_tag_guard, test/dynamo/test_dicts.py::DictTests::test_empty_dict_recompilation, test/dynamo/test_dicts.py::DictTests::test_fn_id, test/dynamo/test_dicts.py::DictTests::test_items_type, test/dynamo/test_dicts.py::DictTests::test_lazy_key_guarding, test/dynamo/test_dicts.py::DictTests::test_lazy_key_non_const_guarding, test/dynamo/test_dicts.py::DictTests::test_mapping_proxy_existing, test/dynamo/test_dicts.py::DictTests::test_mapping_proxy_existing_local_mutation, test/dynamo/test_dicts.py::DictTests::test_mapping_proxy_existing_mutation, test/dynamo/test_dicts.py::DictTests::test_mapping_proxy_for_local, test/dynamo/test_dicts.py::DictTests::test_mapping_proxy_for_nonlocal, test/dynamo/test_dicts.py::DictTests::test_move_to_end, test/dynamo/test_dicts.py::DictTests::test_newly_constructed_default_dict, test/dynamo/test_dicts.py::DictTests::test_ordered_dict_reordered_keys, test/dynamo/test_dicts.py::DictTests::test_ordered_dict_subclass_reordered_keys, test/dynamo/test_dicts.py::DictTests::test_overridden_get_item, test/dynamo/test_dicts.py::DictTests::test_udf_dict_reconstruction, test/dynamo/test_dicts.py::DictTests::test_update_dunder_dict, test/dynamo/test_dicts.py::DictTests::test_update_module_dunder_dict, test/dynamo/test_dicts.py::DictTests::test_weakref_dict, test/dynamo/test_dicts.py::DictGuardTests::test_cmp_eq, test/dynamo/test_dicts.py::DictGuardTests::test_cmp_ne, test/dynamo/test_dicts.py::DictGuardTests::test_popitem, test/dynamo/test_dicts.py::DictMethodsTests::test_binop_or, test/dynamo/test_dicts.py::DictMethodsTests::test_clear, test/dynamo/test_dicts.py::DictMethodsTests::test_cmp_eq, test/dynamo/test_dicts.py::DictMethodsTests::test_cmp_ne, test/dynamo/test_dicts.py::DictMethodsTests::test_copy, test/dynamo/test_dicts.py::DictMethodsTests::test_fromkeys, test/dynamo/test_dicts.py::DictMethodsTests::test_get, test/dynamo/test_dicts.py::DictMethodsTests::test_items, test/dynamo/test_dicts.py::DictMethodsTests::test_keys, test/dynamo/test_dicts.py::DictMethodsTests::test_pop, test/dynamo/test_dicts.py::DictMethodsTests::test_popitem, test/dynamo/test_dicts.py::DictMethodsTests::test_setdefault, test/dynamo/test_dicts.py::DictMethodsTests::test_update, test/dynamo/test_dicts.py::DictMethodsTests::test_values, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_binop_or, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_clear, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_cmp_eq, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_cmp_ne, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_copy, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_fromkeys, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_get, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_items, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_keys, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_pop, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_popitem, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_setdefault, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_update, test/dynamo/test_dicts.py::DictSubclassMethodsTests::test_values, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_binop_or, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_clear, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_cmp_eq, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_cmp_eq_order, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_cmp_ne, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_copy, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_fromkeys, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_get, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_items, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_keys, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_pop, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_popitem, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_setdefault, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_update, test/dynamo/test_dicts.py::OrderedDictMethodsTests::test_values
2025-07-17T07:43:37.2817150Z 
2025-07-17T07:43:39.3220410Z Running dynamo/test_dynamic_shapes 1/3 ... [2025-07-17 07:43:39.321876]
2025-07-17T07:43:39.3220760Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:43:39.3223620Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_dynamic_shapes.py', '-m', 'not serial', '--shard-id=1', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:43:39.322229]
2025-07-17T07:45:15.1738680Z 
2025-07-17T07:45:15.1739380Z inductor/test_torchinductor_opinfo 11/14 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_opinfo_11.14_e756ac015843f7df_.log
2025-07-17T07:45:15.1823020Z Running 259 items in this shard: test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___getitem___cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___rdiv___cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___rmatmul___cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___rpow___cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive__chunk_cat_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_acosh_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_acosh_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_add_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addbmm_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addmm_decomposed_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_alias_copy_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_amax_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_amin_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_as_strided_partial_views_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atleast_2d_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atleast_3d_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_bitwise_not_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_bitwise_or_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_block_diag_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_block_diag_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_bmm_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_broadcast_tensors_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_broadcast_to_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cdouble_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cdouble_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cfloat_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_clone_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_column_stack_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_combinations_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_conj_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_conj_physical_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cos_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cos_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cosh_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cosh_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_cross_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diag_embed_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diagflat_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diagonal_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_div_floor_rounding_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_div_floor_rounding_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_div_no_rounding_mode_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_dot_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_dstack_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_empty_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_empty_like_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_empty_strided_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_equal_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_erfinv_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expand_as_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expand_as_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expand_copy_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_fft_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_fftn_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_hfft2_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_hfft_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_ihfft2_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_ihfft2_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_ihfft_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fill_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_flip_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_float_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_float_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_float_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_floor_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_floor_divide_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_floor_divide_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fmod_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_frac_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_frac_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_ge_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_ge_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_geometric_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_geometric_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_grid_sampler_2d_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_half_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_half_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_igammac_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_fill_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_put_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_reduce_amin_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_index_select_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_isnan_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_isneginf_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_isposinf_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_isposinf_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_isreal_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_jiterator_2inputs_2outputs_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_jiterator_binary_return_by_ref_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_jiterator_unary_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_kron_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_linalg_diagonal_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_linalg_ldl_solve_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_linalg_lu_factor_ex_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_linalg_matrix_norm_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_linalg_solve_ex_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_linspace_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_linspace_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_linspace_tensor_overload_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_log1p_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_log_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_log_softmax_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_logical_and_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_logical_or_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_logit_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_logspace_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_lu_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_mT_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_masked_cumprod_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_masked_cumprod_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_masked_cumsum_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_masked_fill_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_masked_logaddexp_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_masked_logsumexp_cpu_float32, 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test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_max_pool3d_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_max_unpool2d_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pad_circular_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pad_constant_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pad_constant_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pad_constant_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pad_replicate_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pad_replicate_cpu_uint8, 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test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unbind_copy_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unbind_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unique_consecutive_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unique_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unique_cpu_uint16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unsafe_split_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unsqueeze_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_view_as_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_view_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_view_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_where_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_zeros_like_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_zeros_like_cpu_uint8
2025-07-17T07:45:15.1897780Z 
2025-07-17T07:45:17.2125940Z Running dynamo/test_dynamic_shapes 2/3 ... [2025-07-17 07:45:17.212383]
2025-07-17T07:45:17.2127530Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:45:17.2130310Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_dynamic_shapes.py', '-m', 'not serial', '--shard-id=2', '--num-shards=3', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:45:17.212675]
2025-07-17T07:46:36.1506300Z 
2025-07-17T07:46:36.1506910Z inductor/test_torchinductor_opinfo 7/14 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_opinfo_7.14_c5be10f36a800fc9_.log
2025-07-17T07:46:36.1589260Z Running 276 items in this shard: test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_T_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___radd___cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___rdiv___cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___rmod___cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___rsub___cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive___rxor___cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive__chunk_cat_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive__native_batch_norm_legit_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive__unsafe_masked_index_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive__unsafe_masked_index_put_accumulate_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_abs_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_acos_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_acosh_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addbmm_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addbmm_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addcmul_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addmm_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addmv_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addmv_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addmv_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addr_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_addr_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_alias_copy_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_allclose_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_angle_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_angle_cpu_float32, 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test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atanh_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atanh_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atleast_1d_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atleast_2d_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_atleast_3d_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_baddbmm_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_bitwise_not_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_bitwise_or_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_bitwise_right_shift_cpu_int32, 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test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diag_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_diff_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_dist_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_double_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_dstack_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_einsum_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_erfc_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_exp2_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_exp_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_expand_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_eye_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_eye_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_fft_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_fft_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_hfft_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_hfft_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_ifft2_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fft_ihfft2_cpu_bool, 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test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fliplr_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_flipud_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_float_power_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_float_power_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fmod_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_fmod_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_full_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_gather_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_geqrf_cpu_float32, 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test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_cross_entropy_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_dropout3d_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_dropout_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_embedding_bag_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_feature_alpha_dropout_with_train_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_hardsigmoid_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_hardsigmoid_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_interpolate_nearest_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_interpolate_trilinear_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_interpolate_trilinear_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_local_response_norm_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_max_pool2d_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_max_pool3d_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_max_unpool1d_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_max_unpool2d_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pad_replicate_negative_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pixel_shuffle_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pixel_shuffle_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_pixel_unshuffle_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_poisson_nll_loss_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_prelu_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_relu6_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_relu6_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_softmin_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_softshrink_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_softsign_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_tanhshrink_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_nn_functional_threshold_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_norm_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_ones_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_ones_like_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_outer_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_permute_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_polygamma_polygamma_n_0_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_positive_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_qr_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_quantile_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_rad2deg_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_randn_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_randn_like_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_reciprocal_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_reciprocal_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_renorm_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_repeat_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_repeat_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_reshape_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_reshape_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_resize_as__cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_resolve_neg_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_rot90_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_scalar_tensor_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_scatter_reduce_amin_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_short_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_signal_windows_cosine_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_signbit_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_sinc_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_sinh_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_slice_scatter_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_bessel_y0_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_chebyshev_polynomial_t_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_chebyshev_polynomial_u_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_i0e_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_i1e_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_laguerre_polynomial_l_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_modified_bessel_i0_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_modified_bessel_i0_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_polygamma_special_polygamma_n_0_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_scaled_modified_bessel_k0_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_scaled_modified_bessel_k0_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_shifted_chebyshev_polynomial_t_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_shifted_chebyshev_polynomial_t_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_shifted_chebyshev_polynomial_u_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_shifted_chebyshev_polynomial_u_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_shifted_chebyshev_polynomial_v_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_spherical_bessel_j0_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_special_xlog1py_cpu_bool, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_split_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_split_list_args_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_sqrt_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_stack_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_t_copy_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_take_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_tanh_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_tanh_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_tensordot_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_tensordot_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_topk_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_topk_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_transpose_copy_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_transpose_copy_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_trapezoid_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_true_divide_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unbind_copy_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unbind_copy_cpu_uint8, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unbind_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_uniform_cpu_float64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_unsqueeze_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_var_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_var_mean_unbiased_cpu_float32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_view_as_cpu_float16, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_view_as_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_view_copy_cpu_int64, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_vstack_cpu_int32, test/inductor/test_torchinductor_opinfo.py::TestInductorOpInfoCPU::test_comprehensive_zeros_cpu_float64
2025-07-17T07:46:36.1668650Z 
2025-07-17T07:46:38.1645920Z Running dynamo/test_list 1/1 ... [2025-07-17 07:46:38.164390]
2025-07-17T07:46:38.1646670Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:46:38.1648980Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_list.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:46:38.164703]
2025-07-17T07:46:41.3386730Z 
2025-07-17T07:46:41.3387910Z dynamo/test_list 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_list_1.1_91715fd017a5f3bf_.log
2025-07-17T07:46:41.3393820Z Running 39 items in this shard: test/dynamo/test_list.py::TupleTests::test___contains__, test/dynamo/test_list.py::TupleTests::test___getitem__, test/dynamo/test_list.py::TupleTests::test_binop_add, test/dynamo/test_list.py::TupleTests::test_binop_imul, test/dynamo/test_list.py::TupleTests::test_cmp_eq, test/dynamo/test_list.py::TupleTests::test_cmp_greater_than, test/dynamo/test_list.py::TupleTests::test_cmp_greater_than_or_equal, test/dynamo/test_list.py::TupleTests::test_cmp_less_than, test/dynamo/test_list.py::TupleTests::test_cmp_less_than_or_equal, test/dynamo/test_list.py::TupleTests::test_cmp_ne, test/dynamo/test_list.py::TupleTests::test_count, test/dynamo/test_list.py::TupleTests::test_index, test/dynamo/test_list.py::ListTests::test___contains__, test/dynamo/test_list.py::ListTests::test___delitem__, test/dynamo/test_list.py::ListTests::test___getitem__, test/dynamo/test_list.py::ListTests::test___setitem__, test/dynamo/test_list.py::ListTests::test_append, test/dynamo/test_list.py::ListTests::test_binop_add, test/dynamo/test_list.py::ListTests::test_binop_delitem_global_list, test/dynamo/test_list.py::ListTests::test_binop_iadd, test/dynamo/test_list.py::ListTests::test_binop_iadd_global_list, test/dynamo/test_list.py::ListTests::test_binop_imul, test/dynamo/test_list.py::ListTests::test_binop_imul_global_list, test/dynamo/test_list.py::ListTests::test_clear, test/dynamo/test_list.py::ListTests::test_cmp_eq, test/dynamo/test_list.py::ListTests::test_cmp_greater_than, test/dynamo/test_list.py::ListTests::test_cmp_greater_than_or_equal, test/dynamo/test_list.py::ListTests::test_cmp_less_than, test/dynamo/test_list.py::ListTests::test_cmp_less_than_or_equal, test/dynamo/test_list.py::ListTests::test_cmp_ne, test/dynamo/test_list.py::ListTests::test_copy, test/dynamo/test_list.py::ListTests::test_count, test/dynamo/test_list.py::ListTests::test_extend, test/dynamo/test_list.py::ListTests::test_index, test/dynamo/test_list.py::ListTests::test_insert, test/dynamo/test_list.py::ListTests::test_pop, test/dynamo/test_list.py::ListTests::test_remove, test/dynamo/test_list.py::ListTests::test_reverse, test/dynamo/test_list.py::ListTests::test_sort
2025-07-17T07:46:41.3399260Z 
2025-07-17T07:46:43.3178250Z Running higher_order_ops/test_with_effects 1/1 ... [2025-07-17 07:46:43.317639]
2025-07-17T07:46:43.3179120Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:46:43.3180790Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'higher_order_ops/test_with_effects.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:46:43.317904]
2025-07-17T07:46:45.7847670Z 
2025-07-17T07:46:45.7849890Z higher_order_ops/test_with_effects 1/1 was successful, full logs can be found in artifacts with path test/test-reports/higher_order_ops.test_with_effects_1.1_9098db7a4cf9feae_.log
2025-07-17T07:46:45.7857970Z Running 18 items in this shard: test/higher_order_ops/test_with_effects.py::TestWithEffects::test_alias_op, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_compile_aot_eager, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_compile_aot_eager_requires_grad, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_compile_inductor, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_compile_inductor_external_op_return_none, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effectful_custom_op_with_subclasses, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effectful_op_in_backward, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effects_and_aliased_outputs, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effects_and_input_mutation_is_output, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effects_and_input_mutation_return, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effects_and_input_output_view_simple, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_print, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_print_with_buffer_mutations, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_print_with_input_mutations, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_register_effectful_custom_op, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_regular_effectful_op_in_forward_and_backward, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_regular_effectful_op_only_in_backward, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_torchbind_custom_op
2025-07-17T07:46:45.7862820Z 
2025-07-17T07:46:47.8331410Z Running dynamo/test_fx_graph_runnable 1/1 ... [2025-07-17 07:46:47.832956]
2025-07-17T07:46:47.8331750Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:46:47.8333930Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_fx_graph_runnable.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:46:47.833290]
2025-07-17T07:47:42.1555030Z 
2025-07-17T07:47:42.1565730Z dynamo/test_fx_graph_runnable 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_fx_graph_runnable_1.1_d33dfb74cf073991_.log
2025-07-17T07:47:42.1570400Z Running 13 items in this shard: test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_all_gather_collective, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_all_reduce_collective, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_basic_tensor_add, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_broadcast_add_dynamic, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_broadcast_collective, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_dtensor_compile_redistribute, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_dynamic_shapes_run, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_reduce_scatter_collective, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_scalar_multiply, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_toy_model_basic, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_toy_model_batch_processing, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_toy_model_dynamic_batch, test/dynamo/test_fx_graph_runnable.py::FxGraphRunnableTest::test_two_inputs_matmul
2025-07-17T07:47:42.1573630Z 
2025-07-17T07:47:42.5033130Z GITHUB_RUN_ID, GITHUB_RUN_ATTEMPT, or ARTIFACTS_FILE_SUFFIX not set, not uploading
2025-07-17T07:47:42.5033510Z Uploading artifacts took 0.00 seconds
2025-07-17T07:47:44.1595370Z Running inductor/test_graph_transform_observer 1/1 ... [2025-07-17 07:47:44.159321]
2025-07-17T07:47:44.1596270Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:47:44.1597820Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_graph_transform_observer.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:47:44.159611]
2025-07-17T07:47:46.7044630Z 
2025-07-17T07:47:46.7045500Z inductor/test_graph_transform_observer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_graph_transform_observer_1.1_dace48fe760c2dcc_.log
2025-07-17T07:47:46.7046030Z 
2025-07-17T07:47:48.7754760Z Running test_openmp 1/1 ... [2025-07-17 07:47:48.775248]
2025-07-17T07:47:48.7755550Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:47:48.7757590Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_openmp.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:47:48.775606]
2025-07-17T07:47:53.9694500Z 
2025-07-17T07:47:53.9695530Z test_openmp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_openmp_1.1_e53d16367905cadd_.log
2025-07-17T07:47:53.9696740Z Running 2 items in this shard: test/test_openmp.py::TestOpenMP_ParallelFor::test_n_threads, test/test_openmp.py::TestOpenMP_ParallelFor::test_one_thread
2025-07-17T07:47:53.9697170Z 
2025-07-17T07:47:55.9780140Z Running inductor/test_compiled_optimizers 1/1 ... [2025-07-17 07:47:55.977798]
2025-07-17T07:47:55.9781020Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:47:55.9783990Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_compiled_optimizers.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:47:55.978105]
2025-07-17T07:48:16.5634930Z 
2025-07-17T07:48:16.5635510Z dynamo/test_dynamic_shapes 1/3 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_dynamic_shapes_1.3_101410b28dba23ca_.log
2025-07-17T07:48:16.5816030Z Running 623 items in this shard: test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_autocast_arguments_binding_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_autocast_cpu_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_autocast_decorator_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_autocast_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_autograd_profiler_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_context_wrapping_grad_mode_decorator_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_context_wrapping_grad_mode_nested_function_decorator_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_cuda_amp_autocast_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_cuda_event_reconstruct_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_cuda_stream_compared_with_constant_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_cuda_stream_compared_with_stream_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_cuda_stream_context_manager2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_disable_saved_tensors_hooks_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_disable_saved_tensors_hooks_prev_disabled_nested_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_generic_context_manager_CustomizedCtxManager_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_generic_context_manager_customized_ctx_manager_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_generic_context_manager_with_graph_break_customized_ctx_manager_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_grad_mode_guard_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_inactive_context_graph_break_local_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_inactive_context_graph_break_local_nullctx_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_inactive_context_graph_break_stack_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_nested_generic_context_manager_CustomizedCtxManager_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_nested_grad_mode_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_no_grad_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_sdpa_kernel_ctx_manager1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_sdpa_kernel_ctx_manager3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_T_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_addcdiv__dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_addcdiv_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_call_dict1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_callable_builtin_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_cls_hasattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_compare_constant_and_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_constant2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_constant3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_constant_set_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_cublas_allow_tf32_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_default_dict_lambda_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_default_dict_list_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_defaultdict_setdefault3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_hasattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_id_guard_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_items_sorted_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_keys_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_mutable_map_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_setdefault1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_setdefault3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_distributed_is_initialized_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dtype_compare_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_filter_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_filter_graph_break_reconstruct_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_filter_infinite_iterator_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_fstrings1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_fstrings2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_functools_cache_guard_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_functools_partial_binding_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_generic_namedtuple_hasattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_generic_namedtuple_subclass_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_generic_namedtuple_user_methods_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_get_autocast_gpu_dtype_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_get_default_dtype_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_get_device_properties_tensor_device_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_globalfn_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_indexed_range_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_inline_jit__unwrap_optional_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_inline_with_default_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_inner_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_is_floating_point_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_is_not_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_is_not_null_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_islice_chain_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_itertools_chain_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_itertools_combinations_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_jit_annotate_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_len_constant_list_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_list_add_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_list_compare_polyfill_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_list_reversed_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_list_slice_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_list_truth_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_listarg1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_mT_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_manual_seed_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_call_function_ex_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_infinite_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_reconstruct_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_return_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_tuple_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_unpack_twice_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_unpack_vars_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_zip_dict_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_math_radians_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_mean_sum_np_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_methodcall2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_methodcall3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_module_constant_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_namedtuple_hasattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_namedtuple_subclass_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_namedtuple_user_methods_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_ndim_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_no_recompile_inner_lambda_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_non_inlined_closure_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_not_list_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_np_constant_collections_guards_float_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_np_iinfo_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_number_method_method_as_integer_ratio_num_type3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_number_method_method_bit_length_num_type1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_number_method_method_conjugate_num_type4_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_numpy_linalg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_numpy_random_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_as_input_partials_lambda_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_graph_break_reconstruct_args_and_kwargs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___annotations___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___class___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___delattr___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___dir___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___doc___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___getattribute___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___kwdefaults___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___ne___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___reduce___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___setattr___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___sizeof___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_udf_arg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_udf_kwarg_method_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_udf_kwarg_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_pop_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_rand_tensor_partial_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_range_length_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_range_with_index_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_reduce_with_single_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_return_multiple_numpy_ndarray_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_return_tuple1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_set_keys_view_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_shape1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_size_tuple_add_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_slice2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_slice3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_sliced_range_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_sum_with_start_arg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tensor_dim_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tensor_element_size_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tensor_is_complex_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tensor_len_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tensor_type2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_to_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_truth_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tuple_iadd_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_two_point_iter_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_unary_fold_op_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_unpack3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_unsqueeze_inplace_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_viatorch_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_312_binary_slice_with_graph_break2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_RAISE_VARARGS_0_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_add_to_set_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_anomaly_aot_autograd_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_aot_autograd_propagate_unbacked_symints_shape_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_argwhere_with_dynamic_shapes_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_builtin_bool_on_symbool_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_callpacked_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_catch_watchings1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_cell_captured_by_existing_func_but_not_root_frame_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_cell_output1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_class_duner_mro_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_clone_sparse_input_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_closure_out_of_scope_cell_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_closure_with_mutation_and_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_compilation_metrics_size_limit_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_cond_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_cond_export_single_arg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_cond_nested_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_conditional_list_comp_in_context_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_constant_getattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_cross_entropy_loss_fancy_ctor1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_cross_entropy_loss_fancy_ctor2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_cross_entropy_loss_simple_ctor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_custom_module_free_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dataclass_fields_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_deque_input_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_deterministic_algorithms_mutated_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dunder_methods_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dunder_new_function_inlining2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dunder_weakref_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dynamic_one_hot_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dynamic_sources_force_parameter_static_shapes_and_property_static_shapes_override_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dynamic_sources_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dynamic_sources_int_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dynamic_sources_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dynamo_disabled_in_custom_op_kernels_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_enum_as_dict_key_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_enum_subclass_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_error_on_nested_fx_trace_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_error_on_recompile_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_escaping_closure_var_with_nonlocal_var_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_fn_hasattr__name__3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_frozen_dataclass_default_factory_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_frozen_dataclass_kw_only_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_frozenset_of_non_literals_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_function_annotation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_generate_tensor_from_list_of_numpy_primitive_type_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_get_attr_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_get_custom_tensor_attribute_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_get_instruction_source_311_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_getattr_dict_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_getattrvariable_as_python_constant_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_global_state_guard_serialization_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_graph_break_compilation_metrics_on_failure_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_guard_failure_fn_shape_control_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_guard_filter_fn_by_name_and_value_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_guard_filter_nn_modules_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_guards_cse_pass_single_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_hasattr_nn_module_guard_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_id_guarded_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_if_cond_nn_mod3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_inline_closure_returned_by_another_function_and_captures_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_inline_dict_function_passed_as_arg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_inline_func_jump_on_tensor_condition_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_inline_list_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_inline_local_dict_clear_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_input_cell_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_int_int_comparisons_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_int_shape_binops_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_int_shape_comparisons_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_int_shape_inplace_binops_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_intermediary_tensor_grad_access_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_invalid_args_builtin_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_is_floating_point2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_is_tensor2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_is_tensor_like2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_item_changes_new_shape_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_itertools_accumulate_symint_default_sum_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_itertools_accumulate_tensors_default_sum_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_itertools_accumulate_tensors_kwargs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_itertools_groupby_pure_python_key_func_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_itertools_infinite_repeat_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_list_hasattr1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_map_side_effects_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_map_with_quantization_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_mark_static_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_mark_unbacked_strict_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_matmul1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_min_max_over_iterable_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_module_complex_iter_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_multiple_inheritance_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_namedtuple3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_namedtuple_with_custom_getitem_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_ne_operator_with_custom_eq_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_ne_operator_with_custom_ne_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_nested_optimize_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_nested_optimize_run_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_nested_sequential_try_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_nn_module_getattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_nn_module_getattribute_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_nn_sequential_invocation_reposition_indices_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_no_guard_for_unused_sym_node_fstring_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_gt_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_int_constant_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_ndarray_works_with_builtin_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_non_torch_dtype_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_random_config_to_numpy_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_ufunc_out_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_ufunc_out_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_object_classmethod_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_out_variants_with_resizing_on_graph_inputs_with_dynamic1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_overridden_getattribute_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_packaging_version_parse_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_param_shape_binops_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_parameter_free_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_precompile_entries_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_precompile_entry_miss_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_pure_python_accumulate_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_python_slice_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_pytree_tree_flatten_unflatten_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_pytree_tree_map_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_raise_guard_indirect_full_constraint_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_raise_guard_partial_constraint_no_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_raises_importerror1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_range_iter_side_effects_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_range_with_shape_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_recompile_on_global_state_change_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_reconstruct_frozen_dataclass_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_reconstruct_set_across_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_recursion_depth_guards_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_recursive_inline_list_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_release_module_memory_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_repro_graph_breaks_in__get_item_by_idx_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_running_nested_func_with_captured_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_sample_input_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_scalar_tensor_is_equivalent_to_symint_argument_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_set_aliasing_recompiles_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_set_discard_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_setattr_mutation1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_setattr_mutation2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_shape_env_equal_constructor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_shape_env_equal_evaluate_expr_refinement_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_shape_type_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_shape_unpack_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_side_effects_codegen_update_mutated_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_slice_input_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_source_non_input_grad_access_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_storage_return_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_str_format_assert1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_str_format_return2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_structseq2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_sym_constrain_range_on_replaced_unbacked_symbol_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_sym_max_unbacked_sizelike_simplification_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_symint_as_device_kwarg_multi_gpu_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tagging_tensors_simple_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_data_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_dict1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_interacts_with_numpy_ndarray_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_is_contiguous_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_item_capture_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_item_no_capture_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tolist_1d_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tolist_kd_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tolist_scalar_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_top_package_import_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_torch_check_is_size_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_torch_distributions_lazy_property_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_torch_dtype_python_type_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_torch_generator_set_state_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_torch_guards_stack_frame_register_inlining_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_torch_size_numel_dynamic_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_torch_variable_hasattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_trace_ndarray_frame_2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tracing_nested_py_tree_dicts_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tracing_tree_map_only_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tuple_iadd_with_shape_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_typing_union_and_optional_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_unbacked_2d_expand_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_unbacked_repeat_cat_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_unbacked_strict_mode_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_unhandled_exception_in_dynamo2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_unhandled_exception_in_dynamo_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_unique_consecutive_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_unpack5_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_update_locals_and_stack_uses_shared_cache_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_user_code_statically_known_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_user_defined_setattr2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_user_getattr1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_usr_cls_staticmethod_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_variable_access_in_exception_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_write_to_closures_in_inlining_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_yield_from_in_a_loop_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_yield_from_user_stop_iteration_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_yield_gen_and_from_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_yield_send_to_subgenerator_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_abc_setattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_add_complex_conj_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_amp_foreach_fake_impl_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_ao_fake_quantize_tracing_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_aot_autograd_runtime_wrapper_prologue_profiled_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_as_strided_on_base_with_mutation_works_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_autograd_function_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_avoid_dupe_specialization_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_batchnorm_e2e_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_boxes_len_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_chunk_reformer_ff_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_compilation_metrics_on_error_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_convert_boxes_to_pooler_format_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_copy_weird_strides_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_dalle2_maybe_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_deferred_runtime_asserts_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_delattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_delete_local_error_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_delsubscr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_delsubscr_raises_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_detectron2_instances_cat_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_dynamic_shape_disable_duck_size_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_dynamic_shapes_double_not_equal_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_ellipsis_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_empty_graph_nested_calls_fullgraph_True_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_empty_list_contains_with_jump_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_empty_out_dynamic_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_enum_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_error_return_without_exception_set_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_fsdp_set_input_mutation_applied_when_input_gets_no_gradients_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_grad_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_graph_break_on_jit_isinstance_pep585_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_guard_default_device_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_guard_fail_tensor_bool_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_inductor_dynamic_shapes_broadcasting_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_isinstance_dtype_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_isinstance_storage_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_issue134451_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_list_index_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_list_reverse_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_list_self_reference_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_listcomp_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_maml_item_capture_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_many_overlapping_inputs_does_not_explode_guards_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_many_views_with_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_maybe_multiply_symint_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_merge_criteria_processor_list2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_nanmean_out_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_nn_module_stack_bc_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_nn_parameter_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_no_tracing_into_eval_frame_ctx_manager_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_nonconst_issubclass_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_nullcontext1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_numpy_not_ndarray_recompiles_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_omegaconf_dictconfig_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_omegaconf_listconfig_iter_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_ones_out_dynamic_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_optimized_module_training_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_out_nested_cell_tuple_shape_change_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_out_none_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_output_aliases_intermediate_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_overwriting_params_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_partially_initialized_module_property_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_partitioner_activation_memory_budget_with_unbacked_symints_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_primtorch_no_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_reinplacing_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_requires_grad_guards_with_grad_mode2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_restricted_list_subclass2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_return_value_duplication_mixed_grad_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_return_value_duplication_scalar_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_rewrite_assert_with_msg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_rewrite_assert_with_non_string_msg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_rewrite_assert_without_msg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_setitem_tuple_boolean_mask_diff_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_sigmoid_out2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_size_typematch_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_slice_into_list_mutable_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_slicing_dynamic_shape_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_specialized_stride_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_staticmethod_allow_in_graph_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_string_format_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_super_classmethod_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_super_classmethod_inheritance_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_symint_bitwise_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_tensor_isinstance_tuple_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_tensor_item_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_tensor_random_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_tensor_set_data_backend_aot_eager_func_name_func1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_tensor_set_data_backend_inductor_func_name_func2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_tensor_set_data_mismatched_dtype_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_tensor_split_within_device_cm_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_tensor_uniform_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_trace_functional_tensor_with_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_unbacked_arange_in_bounds_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_user_ctor_ctx_manager_custom_init_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_user_ctor_ctx_manager_custom_init_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_user_ctor_ctx_manager_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_user_defined_iter_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_validate_model_kwargs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_view_dtype_overload_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_weakref_del_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_zeros_out_dynamic_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_call_fn_with_non_const_inputs_safe_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_cfgmod_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_conv_call_forward_directly_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_fnmembercmp2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_hasattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_intarg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_iseval1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_isnonelayer_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_lazy_module5_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_lazy_module6_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_module_attribute_precedence_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_module_class_method_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_module_forward_has_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_module_guard_name_is_valid_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_module_property_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_module_static_method_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_moduledict_custom_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_parameterdict_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_parameters2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_sequential_with_duplicated_module2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_super1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_tensorlist_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_viamodulecall_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_cond_raise_user_error_on_branch_return_multiple_tensors_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_cond_raise_user_error_on_mismatch_return_length_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_cond_raise_user_error_on_mismatch_return_tensor_meta_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_cond_raise_user_error_on_non_tensor_operands_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_cond_raise_user_error_on_unsupported_pred_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_dict_return_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_dict_return_with_aten_graph_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_dupes_2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_dupes_and_bypass_reorder_with_non_tensor_arg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_dupes_and_bypass_with_non_tensor_output_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_dupes_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_dynamic_slicing_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_dynamic_slicing_simple_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_enforce_equalities_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_decomp_asserts_bad_args_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_dynamic_dim_not_1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_graph_with_complex_reorder_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_mismatched_out_with_aten_graph_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_no_tensor_computation_with_aten_graph_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_raise_guard_partial_constraint_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_shape_control_flow_1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_specialized_int_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_symbolic_shape_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_args_with_default_None_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_args_with_default_float_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_cond_closure_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_constant_free_function_and_class_method_multiarg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_constant_in_unspecialized_nn_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_constant_method_on_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_constant_none_control_flow_free_func_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_constant_not_none_control_flow_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_functools_wrapped_method_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_kwargs_and_empty_args_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_kwargs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_kwargs_with_default_tuple_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_map_zero_sized_tensor_suppress_errors_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_symbool_inputs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_wrapped_fn_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_exported_graph_serialization_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_func_return_with_aten_graph_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_invalid_input_nonlocal_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_list_contains_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_list_unpack_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_map_cond_param_buffer_lifted_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_no_tensor_computation_2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_no_tensor_computation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_param_buffer_safe_from_mutation_recurse_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_param_buffer_safe_from_mutation_simple_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_predispatch_with_higher_order_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_preserve_fx_node_metadata_recompile_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_remove_redundant_dynamic_dim_in_error_message_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_retracibility_dict_container_inp_out_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_round_dynamic_shapes_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_strict_fake_tensor_prop_real_tensors_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_sym_contains_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_symbolic_tracing_within_fake_mode_with_constraints_with_parameters_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_torch_inference_mode_ctx_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_untracked_inputs_in_constraints_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_zeroes_in_and_out_different_shape_on_test_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_zeroes_in_new_shape_scalar_out_permute_dupe_and_bypass_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_zeroes_in_new_shape_scalar_out_permute_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_capi_call1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_capi_call3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_control_flow1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_dynamic_duck_size_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_dynamic_getitem_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_dynamic_kwarg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_graph_break_on_item_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_indirect_unsupported3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_resume2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_resume_freevars_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_resume_tuple_iterator_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_resume_with_no_grad3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_stack_state1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_stack_state2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_start4_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_capture_global_num_adds_guard_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_capture_untracked_global_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_capture_untracked_global_nested_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_capture_value_created_in_subgraph_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_cond_branches_no_arguments_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_cond_branches_no_arguments_no_closure_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_cond_free_variable_in_both_branches_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_cond_graph_break_in_one_branch_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_cond_pytree_operands_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_cond_pytree_operands_with_non_tensor_leaves_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_fallback_on_graph_break_simple_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_fallback_on_python_primitives_output_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_fn_with_kwargs_in_torch_ops_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_freevars_as_inputs_to_wrap_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_hints_wrapper_incorrect_type_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_hints_wrapper_pytree_inputs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_lift_tensors_with_shared_symbols_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_map_pytree_return_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_nested_wrap_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_no_freevars_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_return_captured_var_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_return_captured_vars_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_del_existing_attr_nonlocal_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_del_existing_attr_nonlocal_obj_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_mutate_global_list_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_mutate_global_num_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_mutate_nonlocal_num_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_mutate_nonlocal_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_set_existing_attr_global_obj_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_set_existing_attr_nonlocal_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_set_new_attr_global_obj_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_set_new_attr_nonlocal_obj_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_tensor_with_unbacked_shape_closure_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_unbacked_symbol_closure_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_vmap_source_fn_stack_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_wrap_allow_local_assign_in_body_fn_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_wrap_kwarg_default_else_branch_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_wrap_kwarg_int_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_wrap_pytree_args_not_const_symint_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_wrap_source_fn_stack_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_functional_call_sequential_params_and_buffers_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_grad_call_torch_compile_fn_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_grad_has_aux_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_grad_non_tensor_input_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_grad_over_grad_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_jacrev_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_jvp_freevar_python_scalar_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_jvp_freevar_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_jvp_has_aux_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_linearize_jvp_fn_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vjp_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_multiple_outputs_out_dims_tuple_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_new_tensor_in_body_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_new_tensor_unused_in_body_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_side_effects_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_with_graph_break_lambda_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_LSTM_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_alias_inputs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_aot_grad_mode_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_aot_sequence_nr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_call_fn_with_non_const_inputs_aot_safe_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_different_inputs_overlapping_set_with_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_donated_buffer4_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_donated_buffer_with_retain_or_create_graph1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_donated_buffer_with_retain_or_create_graph3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_eager_sequence_nr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_negative_testing_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_no_storage_overlap_guards_no_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_requires_grad_fake_via_dynamo_recompiles_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_split_with_sizes_aot_autograd_cleans_up_traceback_meta_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesTestSDPA::test_intermediate_attr_access_SDPAParams_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesTestSDPA::test_returns_SDPAParams_dynamic_shapes
2025-07-17T07:48:16.5984630Z 
2025-07-17T07:48:18.5298310Z Running dynamo/test_functions 1/1 ... [2025-07-17 07:48:18.529628]
2025-07-17T07:48:18.5299120Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:48:18.5300760Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_functions.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:48:18.529921]
2025-07-17T07:48:47.6499610Z 
2025-07-17T07:48:47.6500690Z dynamo/test_functions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_functions_1.1_83379b1636f37cdd_.log
2025-07-17T07:48:47.6582050Z Running 455 items in this shard: test/dynamo/test_functions.py::FunctionTests::test_T, test/dynamo/test_functions.py::FunctionTests::test_add, test/dynamo/test_functions.py::FunctionTests::test_add_, test/dynamo/test_functions.py::FunctionTests::test_addcdiv, test/dynamo/test_functions.py::FunctionTests::test_addcdiv_, test/dynamo/test_functions.py::FunctionTests::test_addcmul_, test/dynamo/test_functions.py::FunctionTests::test_are_functorch_transforms_active, test/dynamo/test_functions.py::FunctionTests::test_attrgetter, test/dynamo/test_functions.py::FunctionTests::test_broadcast_foreach_pow, test/dynamo/test_functions.py::FunctionTests::test_build_list_unpack, test/dynamo/test_functions.py::FunctionTests::test_call_dict1, test/dynamo/test_functions.py::FunctionTests::test_call_dict2, test/dynamo/test_functions.py::FunctionTests::test_call_dict3, test/dynamo/test_functions.py::FunctionTests::test_call_dict4, test/dynamo/test_functions.py::FunctionTests::test_call_dict5, test/dynamo/test_functions.py::FunctionTests::test_callable_builtin, test/dynamo/test_functions.py::FunctionTests::test_callable_class, test/dynamo/test_functions.py::FunctionTests::test_callable_lambda, test/dynamo/test_functions.py::FunctionTests::test_callable_list, test/dynamo/test_functions.py::FunctionTests::test_callable_torch, test/dynamo/test_functions.py::FunctionTests::test_chunks1, test/dynamo/test_functions.py::FunctionTests::test_class_dict, test/dynamo/test_functions.py::FunctionTests::test_cls_eq, test/dynamo/test_functions.py::FunctionTests::test_cls_hasattr, test/dynamo/test_functions.py::FunctionTests::test_cls_is, test/dynamo/test_functions.py::FunctionTests::test_compare_constant_and_tensor, test/dynamo/test_functions.py::FunctionTests::test_complex_closure, test/dynamo/test_functions.py::FunctionTests::test_const_tuple_add1, test/dynamo/test_functions.py::FunctionTests::test_const_tuple_add2, test/dynamo/test_functions.py::FunctionTests::test_constant1, test/dynamo/test_functions.py::FunctionTests::test_constant2, test/dynamo/test_functions.py::FunctionTests::test_constant3, test/dynamo/test_functions.py::FunctionTests::test_constant4, test/dynamo/test_functions.py::FunctionTests::test_constant_set, test/dynamo/test_functions.py::FunctionTests::test_context_wrapping_nested_functions_no_closure, test/dynamo/test_functions.py::FunctionTests::test_cublas_allow_tf32, test/dynamo/test_functions.py::FunctionTests::test_custom_dict_kwargs, test/dynamo/test_functions.py::FunctionTests::test_default_dict_closure, test/dynamo/test_functions.py::FunctionTests::test_default_dict_constr, test/dynamo/test_functions.py::FunctionTests::test_default_dict_dict, test/dynamo/test_functions.py::FunctionTests::test_default_dict_lambda, test/dynamo/test_functions.py::FunctionTests::test_default_dict_list, test/dynamo/test_functions.py::FunctionTests::test_default_dict_set, test/dynamo/test_functions.py::FunctionTests::test_default_dict_tuple, test/dynamo/test_functions.py::FunctionTests::test_defaultdict_setdefault1, test/dynamo/test_functions.py::FunctionTests::test_defaultdict_setdefault2, test/dynamo/test_functions.py::FunctionTests::test_defaultdict_setdefault3, test/dynamo/test_functions.py::FunctionTests::test_del, test/dynamo/test_functions.py::FunctionTests::test_deque, test/dynamo/test_functions.py::FunctionTests::test_device, test/dynamo/test_functions.py::FunctionTests::test_device_constant, test/dynamo/test_functions.py::FunctionTests::test_dict_copy, test/dynamo/test_functions.py::FunctionTests::test_dict_fromkeys, test/dynamo/test_functions.py::FunctionTests::test_dict_hasattr, test/dynamo/test_functions.py::FunctionTests::test_dict_id_guard, test/dynamo/test_functions.py::FunctionTests::test_dict_items_sorted, test/dynamo/test_functions.py::FunctionTests::test_dict_key_set1, test/dynamo/test_functions.py::FunctionTests::test_dict_key_set2, test/dynamo/test_functions.py::FunctionTests::test_dict_key_set3, test/dynamo/test_functions.py::FunctionTests::test_dict_keys, test/dynamo/test_functions.py::FunctionTests::test_dict_kwargs, test/dynamo/test_functions.py::FunctionTests::test_dict_mutable_map, test/dynamo/test_functions.py::FunctionTests::test_dict_ops, test/dynamo/test_functions.py::FunctionTests::test_dict_param_keys, test/dynamo/test_functions.py::FunctionTests::test_dict_setdefault1, test/dynamo/test_functions.py::FunctionTests::test_dict_setdefault2, test/dynamo/test_functions.py::FunctionTests::test_dict_setdefault3, test/dynamo/test_functions.py::FunctionTests::test_dict_sorted, test/dynamo/test_functions.py::FunctionTests::test_dict_tuple_lazy_guard, test/dynamo/test_functions.py::FunctionTests::test_dict_update, test/dynamo/test_functions.py::FunctionTests::test_dict_update_kwargs, test/dynamo/test_functions.py::FunctionTests::test_dict_values, test/dynamo/test_functions.py::FunctionTests::test_distributed_is_available, test/dynamo/test_functions.py::FunctionTests::test_distributed_is_initialized, test/dynamo/test_functions.py::FunctionTests::test_dtype, test/dynamo/test_functions.py::FunctionTests::test_dtype_compare, test/dynamo/test_functions.py::FunctionTests::test_elipsis, test/dynamo/test_functions.py::FunctionTests::test_enumerate, test/dynamo/test_functions.py::FunctionTests::test_enumerate_custom, test/dynamo/test_functions.py::FunctionTests::test_enumerate_reconstruct, test/dynamo/test_functions.py::FunctionTests::test_filter, test/dynamo/test_functions.py::FunctionTests::test_filter_fallback, test/dynamo/test_functions.py::FunctionTests::test_filter_graph_break_reconstruct, test/dynamo/test_functions.py::FunctionTests::test_filter_infinite_iterator, test/dynamo/test_functions.py::FunctionTests::test_filter_reconstruct, test/dynamo/test_functions.py::FunctionTests::test_filter_with_graph_break, test/dynamo/test_functions.py::FunctionTests::test_finfo, test/dynamo/test_functions.py::FunctionTests::test_flat_param_same_storage_size, test/dynamo/test_functions.py::FunctionTests::test_float, test/dynamo/test_functions.py::FunctionTests::test_fn_with_self_set, test/dynamo/test_functions.py::FunctionTests::test_foreach_lerp_, test/dynamo/test_functions.py::FunctionTests::test_fstrings1, test/dynamo/test_functions.py::FunctionTests::test_fstrings2, test/dynamo/test_functions.py::FunctionTests::test_fstrings3, test/dynamo/test_functions.py::FunctionTests::test_fstrings4, test/dynamo/test_functions.py::FunctionTests::test_fstrings5, test/dynamo/test_functions.py::FunctionTests::test_fstrings6, test/dynamo/test_functions.py::FunctionTests::test_funcdef_closure, test/dynamo/test_functions.py::FunctionTests::test_functools_cache_guard, test/dynamo/test_functions.py::FunctionTests::test_functools_partial, test/dynamo/test_functions.py::FunctionTests::test_functools_partial_binding, test/dynamo/test_functions.py::FunctionTests::test_generic_namedtuple_hasattr, test/dynamo/test_functions.py::FunctionTests::test_generic_namedtuple_subclass, test/dynamo/test_functions.py::FunctionTests::test_generic_namedtuple_user_methods, test/dynamo/test_functions.py::FunctionTests::test_get_autocast_gpu_dtype, test/dynamo/test_functions.py::FunctionTests::test_get_calculate_correct_fan, test/dynamo/test_functions.py::FunctionTests::test_get_default_dtype, test/dynamo/test_functions.py::FunctionTests::test_get_device_properties_tensor_device, test/dynamo/test_functions.py::FunctionTests::test_get_privateuse1_name, test/dynamo/test_functions.py::FunctionTests::test_getattr, test/dynamo/test_functions.py::FunctionTests::test_getattr_metaclass, test/dynamo/test_functions.py::FunctionTests::test_globalfn, test/dynamo/test_functions.py::FunctionTests::test_globalmodule, test/dynamo/test_functions.py::FunctionTests::test_globalvar, test/dynamo/test_functions.py::FunctionTests::test_import1, test/dynamo/test_functions.py::FunctionTests::test_in_not_in, test/dynamo/test_functions.py::FunctionTests::test_index, test/dynamo/test_functions.py::FunctionTests::test_indexed_range, test/dynamo/test_functions.py::FunctionTests::test_indirect1, test/dynamo/test_functions.py::FunctionTests::test_indirect2, test/dynamo/test_functions.py::FunctionTests::test_indirect3, test/dynamo/test_functions.py::FunctionTests::test_inline_jit__unwrap_optional, test/dynamo/test_functions.py::FunctionTests::test_inline_jit_annotations, test/dynamo/test_functions.py::FunctionTests::test_inline_lru_cache_fn_with_default_args, test/dynamo/test_functions.py::FunctionTests::test_inline_script_if_tracing_fn_with_default_args, test/dynamo/test_functions.py::FunctionTests::test_inline_softmax, test/dynamo/test_functions.py::FunctionTests::test_inline_with_default, test/dynamo/test_functions.py::FunctionTests::test_inner_function, test/dynamo/test_functions.py::FunctionTests::test_is, test/dynamo/test_functions.py::FunctionTests::test_is_any_autocast_enabled, test/dynamo/test_functions.py::FunctionTests::test_is_checkpoint_valid, test/dynamo/test_functions.py::FunctionTests::test_is_complex, test/dynamo/test_functions.py::FunctionTests::test_is_contiguous_frame_counts, test/dynamo/test_functions.py::FunctionTests::test_is_contiguous_memory_format, test/dynamo/test_functions.py::FunctionTests::test_is_floating_point, test/dynamo/test_functions.py::FunctionTests::test_is_fx_tracing, test/dynamo/test_functions.py::FunctionTests::test_is_in_onnx_export, test/dynamo/test_functions.py::FunctionTests::test_is_inference_mode_global_recompilation, test/dynamo/test_functions.py::FunctionTests::test_is_inference_recompilation, test/dynamo/test_functions.py::FunctionTests::test_is_integer, test/dynamo/test_functions.py::FunctionTests::test_is_not, test/dynamo/test_functions.py::FunctionTests::test_is_not_null, test/dynamo/test_functions.py::FunctionTests::test_is_quantized, test/dynamo/test_functions.py::FunctionTests::test_is_sparse, test/dynamo/test_functions.py::FunctionTests::test_isinstance, test/dynamo/test_functions.py::FunctionTests::test_islice_chain, test/dynamo/test_functions.py::FunctionTests::test_itemgetter, test/dynamo/test_functions.py::FunctionTests::test_itertools_chain, test/dynamo/test_functions.py::FunctionTests::test_itertools_chain_from_iterable, test/dynamo/test_functions.py::FunctionTests::test_itertools_combinations, test/dynamo/test_functions.py::FunctionTests::test_itertools_compress, test/dynamo/test_functions.py::FunctionTests::test_itertools_compress_tensors, test/dynamo/test_functions.py::FunctionTests::test_itertools_pairwise, test/dynamo/test_functions.py::FunctionTests::test_itertools_product, test/dynamo/test_functions.py::FunctionTests::test_itertools_reconstruct, test/dynamo/test_functions.py::FunctionTests::test_jit_annotate, test/dynamo/test_functions.py::FunctionTests::test_len_constant_dict, test/dynamo/test_functions.py::FunctionTests::test_len_constant_list, test/dynamo/test_functions.py::FunctionTests::test_len_constant_misc_iterables, test/dynamo/test_functions.py::FunctionTests::test_len_tensor, test/dynamo/test_functions.py::FunctionTests::test_list_add, test/dynamo/test_functions.py::FunctionTests::test_list_add_then_mutate, test/dynamo/test_functions.py::FunctionTests::test_list_clear, test/dynamo/test_functions.py::FunctionTests::test_list_compare_polyfill, test/dynamo/test_functions.py::FunctionTests::test_list_compare_polyfill_non_lists, test/dynamo/test_functions.py::FunctionTests::test_list_convert, test/dynamo/test_functions.py::FunctionTests::test_list_expand_lhs, test/dynamo/test_functions.py::FunctionTests::test_list_index_with_constant_tensor, test/dynamo/test_functions.py::FunctionTests::test_list_reversed, test/dynamo/test_functions.py::FunctionTests::test_list_setitem, test/dynamo/test_functions.py::FunctionTests::test_list_setitem_slice, test/dynamo/test_functions.py::FunctionTests::test_list_slice, test/dynamo/test_functions.py::FunctionTests::test_list_slice_assignment, test/dynamo/test_functions.py::FunctionTests::test_list_sorted1, test/dynamo/test_functions.py::FunctionTests::test_list_sorted2, test/dynamo/test_functions.py::FunctionTests::test_list_truth, test/dynamo/test_functions.py::FunctionTests::test_listarg1, test/dynamo/test_functions.py::FunctionTests::test_listarg2, test/dynamo/test_functions.py::FunctionTests::test_listarg3, test/dynamo/test_functions.py::FunctionTests::test_listarg4, test/dynamo/test_functions.py::FunctionTests::test_listarg5, test/dynamo/test_functions.py::FunctionTests::test_load_global_bool, test/dynamo/test_functions.py::FunctionTests::test_lru_cache_warning_issued_during_tracing, test/dynamo/test_functions.py::FunctionTests::test_mT, test/dynamo/test_functions.py::FunctionTests::test_manual_seed, 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test/dynamo/test_functions.py::FunctionTests::test_map_return, test/dynamo/test_functions.py::FunctionTests::test_map_set, test/dynamo/test_functions.py::FunctionTests::test_map_sorted, test/dynamo/test_functions.py::FunctionTests::test_map_str_join, test/dynamo/test_functions.py::FunctionTests::test_map_sum, test/dynamo/test_functions.py::FunctionTests::test_map_tuple, test/dynamo/test_functions.py::FunctionTests::test_map_unpack_twice, test/dynamo/test_functions.py::FunctionTests::test_map_unpack_vars, test/dynamo/test_functions.py::FunctionTests::test_map_with_graph_break, test/dynamo/test_functions.py::FunctionTests::test_map_zip_dict, test/dynamo/test_functions.py::FunctionTests::test_math_radians, test/dynamo/test_functions.py::FunctionTests::test_mean_sum_np, test/dynamo/test_functions.py::FunctionTests::test_methodcall1, test/dynamo/test_functions.py::FunctionTests::test_methodcall2, test/dynamo/test_functions.py::FunctionTests::test_methodcall3, test/dynamo/test_functions.py::FunctionTests::test_methodcaller, test/dynamo/test_functions.py::FunctionTests::test_min_max, test/dynamo/test_functions.py::FunctionTests::test_module_constant, test/dynamo/test_functions.py::FunctionTests::test_namedtuple, test/dynamo/test_functions.py::FunctionTests::test_namedtuple_defaults, test/dynamo/test_functions.py::FunctionTests::test_namedtuple_hasattr, test/dynamo/test_functions.py::FunctionTests::test_namedtuple_subclass, test/dynamo/test_functions.py::FunctionTests::test_namedtuple_user_methods, test/dynamo/test_functions.py::FunctionTests::test_ndarray_builtin_functions, test/dynamo/test_functions.py::FunctionTests::test_ndarray_method, test/dynamo/test_functions.py::FunctionTests::test_ndarray_methods_returning_scalar, test/dynamo/test_functions.py::FunctionTests::test_ndarray_reshape, test/dynamo/test_functions.py::FunctionTests::test_ndarray_transpose, test/dynamo/test_functions.py::FunctionTests::test_ndim, 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test/dynamo/test_functions.py::FunctionTests::test_partials_udf_kwarg, test/dynamo/test_functions.py::FunctionTests::test_partials_udf_kwarg_method, test/dynamo/test_functions.py::FunctionTests::test_partials_udf_kwarg_module, test/dynamo/test_functions.py::FunctionTests::test_pop, test/dynamo/test_functions.py::FunctionTests::test_pos, test/dynamo/test_functions.py::FunctionTests::test_pow_int, test/dynamo/test_functions.py::FunctionTests::test_promote_types, test/dynamo/test_functions.py::FunctionTests::test_rand_inlined, test/dynamo/test_functions.py::FunctionTests::test_rand_tensor_partial, test/dynamo/test_functions.py::FunctionTests::test_range1, test/dynamo/test_functions.py::FunctionTests::test_range2, test/dynamo/test_functions.py::FunctionTests::test_range_length, test/dynamo/test_functions.py::FunctionTests::test_range_with_index, test/dynamo/test_functions.py::FunctionTests::test_range_with_slice_index, test/dynamo/test_functions.py::FunctionTests::test_reduce, test/dynamo/test_functions.py::FunctionTests::test_reduce_with_initial, test/dynamo/test_functions.py::FunctionTests::test_reduce_with_none_initial, test/dynamo/test_functions.py::FunctionTests::test_reduce_with_single, test/dynamo/test_functions.py::FunctionTests::test_reduce_with_single_with_initial, test/dynamo/test_functions.py::FunctionTests::test_return_dict, test/dynamo/test_functions.py::FunctionTests::test_return_dict2, test/dynamo/test_functions.py::FunctionTests::test_return_multiple_numpy_ndarray, test/dynamo/test_functions.py::FunctionTests::test_return_numpy_ndarray, test/dynamo/test_functions.py::FunctionTests::test_return_tuple1, test/dynamo/test_functions.py::FunctionTests::test_return_tuple2, test/dynamo/test_functions.py::FunctionTests::test_returning_recursive_func, test/dynamo/test_functions.py::FunctionTests::test_round, test/dynamo/test_functions.py::FunctionTests::test_set_add, test/dynamo/test_functions.py::FunctionTests::test_set_in_frozenset, test/dynamo/test_functions.py::FunctionTests::test_set_keys_view, test/dynamo/test_functions.py::FunctionTests::test_set_update_bytecode, test/dynamo/test_functions.py::FunctionTests::test_set_update_list_with_duplicated_items, test/dynamo/test_functions.py::FunctionTests::test_shape1, test/dynamo/test_functions.py::FunctionTests::test_shape2, test/dynamo/test_functions.py::FunctionTests::test_size_tuple_add, test/dynamo/test_functions.py::FunctionTests::test_slice1, test/dynamo/test_functions.py::FunctionTests::test_slice2, test/dynamo/test_functions.py::FunctionTests::test_slice3, test/dynamo/test_functions.py::FunctionTests::test_slice4, test/dynamo/test_functions.py::FunctionTests::test_slice5, test/dynamo/test_functions.py::FunctionTests::test_slice6, test/dynamo/test_functions.py::FunctionTests::test_slice_eq, test/dynamo/test_functions.py::FunctionTests::test_sliced_range, test/dynamo/test_functions.py::FunctionTests::test_sorted_const_key_non_const_items, test/dynamo/test_functions.py::FunctionTests::test_sourceless_build_method_type, test/dynamo/test_functions.py::FunctionTests::test_startswith, test/dynamo/test_functions.py::FunctionTests::test_sum, test/dynamo/test_functions.py::FunctionTests::test_sum_shortcut, test/dynamo/test_functions.py::FunctionTests::test_sum_shortcut_with_start_arg, test/dynamo/test_functions.py::FunctionTests::test_sum_shortcut_with_start_kwarg, test/dynamo/test_functions.py::FunctionTests::test_sum_with_start_arg, test/dynamo/test_functions.py::FunctionTests::test_sum_with_start_kwarg, test/dynamo/test_functions.py::FunctionTests::test_symbool_to_int, test/dynamo/test_functions.py::FunctionTests::test_tensor_dim, test/dynamo/test_functions.py::FunctionTests::test_tensor_element_size, test/dynamo/test_functions.py::FunctionTests::test_tensor_is_complex, test/dynamo/test_functions.py::FunctionTests::test_tensor_len, test/dynamo/test_functions.py::FunctionTests::test_tensor_new_with_shape, test/dynamo/test_functions.py::FunctionTests::test_tensor_new_with_size, test/dynamo/test_functions.py::FunctionTests::test_tensor_size, test/dynamo/test_functions.py::FunctionTests::test_tensor_size_indexed_by_symint, test/dynamo/test_functions.py::FunctionTests::test_tensor_type, test/dynamo/test_functions.py::FunctionTests::test_tensor_type2, test/dynamo/test_functions.py::FunctionTests::test_tensor_type3, test/dynamo/test_functions.py::FunctionTests::test_tensor_type4, test/dynamo/test_functions.py::FunctionTests::test_tensor_type5, test/dynamo/test_functions.py::FunctionTests::test_to, test/dynamo/test_functions.py::FunctionTests::test_torch_distributions_functions, test/dynamo/test_functions.py::FunctionTests::test_torch_from_numpy, test/dynamo/test_functions.py::FunctionTests::test_torch_get_device_module, test/dynamo/test_functions.py::FunctionTests::test_torch_size_as_dict_key, test/dynamo/test_functions.py::FunctionTests::test_torch_size_hasattr, test/dynamo/test_functions.py::FunctionTests::test_torch_source, test/dynamo/test_functions.py::FunctionTests::test_transpose_for_scores, test/dynamo/test_functions.py::FunctionTests::test_truth, test/dynamo/test_functions.py::FunctionTests::test_tuple1, test/dynamo/test_functions.py::FunctionTests::test_tuple2, test/dynamo/test_functions.py::FunctionTests::test_tuple_contains, test/dynamo/test_functions.py::FunctionTests::test_tuple_iadd, test/dynamo/test_functions.py::FunctionTests::test_tuple_sorted, test/dynamo/test_functions.py::FunctionTests::test_two_point_iter, test/dynamo/test_functions.py::FunctionTests::test_unary_fold_op, test/dynamo/test_functions.py::FunctionTests::test_unary_fold_op_seq, test/dynamo/test_functions.py::FunctionTests::test_unpack1, test/dynamo/test_functions.py::FunctionTests::test_unpack2, test/dynamo/test_functions.py::FunctionTests::test_unpack3, test/dynamo/test_functions.py::FunctionTests::test_unpack_ex1, test/dynamo/test_functions.py::FunctionTests::test_unpack_ex2, test/dynamo/test_functions.py::FunctionTests::test_unpack_ex3, test/dynamo/test_functions.py::FunctionTests::test_unpack_mutable_map, test/dynamo/test_functions.py::FunctionTests::test_unsqueeze_inplace, test/dynamo/test_functions.py::FunctionTests::test_viamethod, test/dynamo/test_functions.py::FunctionTests::test_viatorch, test/dynamo/test_functions.py::FunctionTests::test_zip_longest, test/dynamo/test_functions.py::FunctionTests::test_zip_reconstruct, test/dynamo/test_functions.py::DefaultsTests::test_cast_tensor_single_elem, test/dynamo/test_functions.py::DefaultsTests::test_cuda_current_device, test/dynamo/test_functions.py::DefaultsTests::test_dataclass_factory, test/dynamo/test_functions.py::DefaultsTests::test_dataclass_nested, test/dynamo/test_functions.py::DefaultsTests::test_fn_with_attr, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_construction, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_illegal_call_method, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_reconstruction, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_return_type_method_name_copy, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_return_type_method_name_difference, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_return_type_method_name_intersection, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_return_type_method_name_symmetric_difference, test/dynamo/test_functions.py::DefaultsTests::test_frozenset_return_type_method_name_union, test/dynamo/test_functions.py::DefaultsTests::test_func_attrs, test/dynamo/test_functions.py::DefaultsTests::test_func_default_tensor_args, test/dynamo/test_functions.py::DefaultsTests::test_func_default_torch_args, test/dynamo/test_functions.py::DefaultsTests::test_functional_compile, test/dynamo/test_functions.py::DefaultsTests::test_functools_partial_id, test/dynamo/test_functions.py::DefaultsTests::test_fx_immutable_list_mutation_not_allowed, test/dynamo/test_functions.py::DefaultsTests::test_fx_map_aggregate, test/dynamo/test_functions.py::DefaultsTests::test_in_set_inplace, test/dynamo/test_functions.py::DefaultsTests::test_in_set_would_fail_broadcast, test/dynamo/test_functions.py::DefaultsTests::test_is_init_in_compile_mutated_tensor_tensor, test/dynamo/test_functions.py::DefaultsTests::test_is_init_in_compile_vmapped_mutated_tensor_tensor, test/dynamo/test_functions.py::DefaultsTests::test_is_init_in_compile_vmapped_mutated_tensor_tensor_multi_arg, test/dynamo/test_functions.py::DefaultsTests::test_is_mutated_tensor_tensor, test/dynamo/test_functions.py::DefaultsTests::test_is_mutated_tensor_tensor_across_graph_break, test/dynamo/test_functions.py::DefaultsTests::test_is_not_tensor_tensor, test/dynamo/test_functions.py::DefaultsTests::test_is_tensor_tensor, test/dynamo/test_functions.py::DefaultsTests::test_is_vmapped_mutated_tensor_tensor, test/dynamo/test_functions.py::DefaultsTests::test_keyword, test/dynamo/test_functions.py::DefaultsTests::test_listlike_of_tensors_contains_constant, test/dynamo/test_functions.py::DefaultsTests::test_meth_default_tensor_args, test/dynamo/test_functions.py::DefaultsTests::test_pybind_object, test/dynamo/test_functions.py::DefaultsTests::test_reconstructed_name, test/dynamo/test_functions.py::DefaultsTests::test_set_call___init___frozenset, test/dynamo/test_functions.py::DefaultsTests::test_set_call___init___set, test/dynamo/test_functions.py::DefaultsTests::test_set_construction, test/dynamo/test_functions.py::DefaultsTests::test_skip_function_call_very_weird_value, test/dynamo/test_functions.py::DefaultsTests::test_str_handler_for_user_defined_object, test/dynamo/test_functions.py::DefaultsTests::test_sys_recursionlimit, test/dynamo/test_functions.py::DefaultsTests::test_tree_map, test/dynamo/test_functions.py::DefaultsTests::test_udf_list, test/dynamo/test_functions.py::DefaultsTests::test_udf_list_reconstruction, test/dynamo/test_functions.py::DefaultsTests::test_udf_list_slice, test/dynamo/test_functions.py::DefaultsTests::test_udf_namedtuple, test/dynamo/test_functions.py::DefaultsTests::test_udf_tuple, test/dynamo/test_functions.py::DefaultsTests::test_udf_tuple_construction, test/dynamo/test_functions.py::DefaultsTests::test_udf_tuple_construction_custom_new, test/dynamo/test_functions.py::DefaultsTests::test_udf_tuple_reconstruction, test/dynamo/test_functions.py::DefaultsTests::test_zip_strict
2025-07-17T07:48:47.6661320Z 
2025-07-17T07:48:49.6595480Z Running torch_np/test_ufuncs_basic 1/1 ... [2025-07-17 07:48:49.659373]
2025-07-17T07:48:49.6596290Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:48:49.6598410Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'torch_np/test_ufuncs_basic.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:48:49.659668]
2025-07-17T07:48:52.4439690Z 
2025-07-17T07:48:52.4440450Z torch_np/test_ufuncs_basic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_ufuncs_basic_1.1_a2d27057d84367fb_.log
2025-07-17T07:48:52.4555030Z Running 371 items in this shard: test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_scalar_ufunc0, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_equiv_ufunc0_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_equiv_ufunc0_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_equiv_ufunc0_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_no_ufunc0_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_no_ufunc0_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_no_ufunc0_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_safe_ufunc0_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_safe_ufunc0_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_safe_ufunc0_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_same_kind_ufunc0_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_same_kind_ufunc0_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_same_kind_ufunc0_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_unsafe_ufunc0_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_unsafe_ufunc0_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestUnaryUfuncs::test_x_and_dtype_casting_casting_unsafe_ufunc0_dtype_float64, 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test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_no_ufunc7_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_no_ufunc7_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_no_ufunc7_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_no_ufunc8_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_no_ufunc8_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_no_ufunc8_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_no_ufunc9_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_no_ufunc9_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_no_ufunc9_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc0_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc0_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc0_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc10_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc10_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc10_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc11_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc11_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc11_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc12_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc12_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc12_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc13_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc13_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc13_out_dtype_float64, 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test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc6_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc6_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc6_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc7_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc7_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc7_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc8_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_safe_ufunc8_out_dtype_float32, 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test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc13_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc13_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc13_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc14_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc14_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc14_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc15_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc15_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc15_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc16_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc16_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc16_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc1_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc1_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc1_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc2_out_dtype_complex128, 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test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc5_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc5_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc5_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc6_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc6_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc6_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc7_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc7_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc7_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc8_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc8_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc8_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc9_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc9_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_same_kind_ufunc9_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc0_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc0_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc0_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc10_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc10_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc10_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc11_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc11_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc11_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc12_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc12_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc12_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc13_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc13_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc13_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc14_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc14_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc14_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc15_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc15_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc15_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc16_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc16_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc16_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc1_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc1_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc1_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc2_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc2_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc2_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc3_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc3_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc3_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc4_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc4_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc4_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc5_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc5_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc5_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc6_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc6_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc6_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc7_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc7_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc7_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc8_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc8_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc8_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc9_out_dtype_complex128, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc9_out_dtype_float32, test/torch_np/test_ufuncs_basic.py::TestBinaryUfuncs::test_xy_and_out_casting_casting_unsafe_ufunc9_out_dtype_float64, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_basic_ufunc0_op0_iop0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_basic_ufunc1_op1_iop1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_basic_ufunc2_op2_iop2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_bcast_ufunc0_op0_iop0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_bcast_ufunc1_op1_iop1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_bcast_ufunc2_op2_iop2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc0_op0_iop0_other_dtype0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc0_op0_iop0_other_dtype1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc0_op0_iop0_other_dtype2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc0_op0_iop0_other_dtype3, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc1_op1_iop1_other_dtype0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc1_op1_iop1_other_dtype1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc1_op1_iop1_other_dtype2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc1_op1_iop1_other_dtype3, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc2_op2_iop2_other_dtype0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc2_op2_iop2_other_dtype1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc2_op2_iop2_other_dtype2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_array_ufunc2_op2_iop2_other_dtype3, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc0_op0_iop0_other_dtype0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc0_op0_iop0_other_dtype1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc0_op0_iop0_other_dtype2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc0_op0_iop0_other_dtype3, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc1_op1_iop1_other_dtype0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc1_op1_iop1_other_dtype1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc1_op1_iop1_other_dtype2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc1_op1_iop1_other_dtype3, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc2_op2_iop2_other_dtype0, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc2_op2_iop2_other_dtype1, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc2_op2_iop2_other_dtype2, test/torch_np/test_ufuncs_basic.py::TestNdarrayDunderVsUfunc::test_other_scalar_ufunc2_op2_iop2_other_dtype3, test/torch_np/test_ufuncs_basic.py::TestUfuncDtypeKwd::test_binary_ufunc_dtype, test/torch_np/test_ufuncs_basic.py::TestUfuncDtypeKwd::test_binary_ufunc_dtype_and_out
2025-07-17T07:48:52.4653290Z 
2025-07-17T07:48:54.4382850Z Running inductor/test_ordered_set 1/1 ... [2025-07-17 07:48:54.438136]
2025-07-17T07:48:54.4383180Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:48:54.4385970Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_ordered_set.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:48:54.438472]
2025-07-17T07:48:57.9333730Z 
2025-07-17T07:48:57.9334640Z inductor/test_ordered_set 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_ordered_set_1.1_6832485b3d772b74_.log
2025-07-17T07:48:57.9411660Z Running 401 items in this shard: test/inductor/test_ordered_set.py::TestJointOps::test_and, test/inductor/test_ordered_set.py::TestJointOps::test_badcmp, test/inductor/test_ordered_set.py::TestJointOps::test_container_iterator, test/inductor/test_ordered_set.py::TestJointOps::test_contains, test/inductor/test_ordered_set.py::TestJointOps::test_cyclical_repr, test/inductor/test_ordered_set.py::TestJointOps::test_deepcopy, test/inductor/test_ordered_set.py::TestJointOps::test_difference, test/inductor/test_ordered_set.py::TestJointOps::test_do_not_rehash_dict_keys, test/inductor/test_ordered_set.py::TestJointOps::test_equality, test/inductor/test_ordered_set.py::TestJointOps::test_free_after_iterating, test/inductor/test_ordered_set.py::TestJointOps::test_gc, test/inductor/test_ordered_set.py::TestJointOps::test_intersection, test/inductor/test_ordered_set.py::TestJointOps::test_isdisjoint, test/inductor/test_ordered_set.py::TestJointOps::test_iterator_pickling, test/inductor/test_ordered_set.py::TestJointOps::test_len, test/inductor/test_ordered_set.py::TestJointOps::test_new_or_init, test/inductor/test_ordered_set.py::TestJointOps::test_or, test/inductor/test_ordered_set.py::TestJointOps::test_pickling, test/inductor/test_ordered_set.py::TestJointOps::test_setOfFrozensets, test/inductor/test_ordered_set.py::TestJointOps::test_sub, test/inductor/test_ordered_set.py::TestJointOps::test_sub_and_super, test/inductor/test_ordered_set.py::TestJointOps::test_subclass_with_custom_hash, test/inductor/test_ordered_set.py::TestJointOps::test_symmetric_difference, test/inductor/test_ordered_set.py::TestJointOps::test_union, test/inductor/test_ordered_set.py::TestJointOps::test_uniquification, test/inductor/test_ordered_set.py::TestJointOps::test_xor, test/inductor/test_ordered_set.py::TestSet::test_add, test/inductor/test_ordered_set.py::TestSet::test_and, test/inductor/test_ordered_set.py::TestSet::test_badcmp, test/inductor/test_ordered_set.py::TestSet::test_clear, test/inductor/test_ordered_set.py::TestSet::test_constructor_identity, test/inductor/test_ordered_set.py::TestSet::test_container_iterator, test/inductor/test_ordered_set.py::TestSet::test_contains, test/inductor/test_ordered_set.py::TestSet::test_copy, test/inductor/test_ordered_set.py::TestSet::test_cyclical_repr, test/inductor/test_ordered_set.py::TestSet::test_deepcopy, test/inductor/test_ordered_set.py::TestSet::test_difference, test/inductor/test_ordered_set.py::TestSet::test_difference_update, test/inductor/test_ordered_set.py::TestSet::test_discard, test/inductor/test_ordered_set.py::TestSet::test_do_not_rehash_dict_keys, test/inductor/test_ordered_set.py::TestSet::test_equality, test/inductor/test_ordered_set.py::TestSet::test_free_after_iterating, test/inductor/test_ordered_set.py::TestSet::test_gc, test/inductor/test_ordered_set.py::TestSet::test_hash, test/inductor/test_ordered_set.py::TestSet::test_iand, test/inductor/test_ordered_set.py::TestSet::test_init, test/inductor/test_ordered_set.py::TestSet::test_inplace_on_self, test/inductor/test_ordered_set.py::TestSet::test_intersection, test/inductor/test_ordered_set.py::TestSet::test_intersection_update, test/inductor/test_ordered_set.py::TestSet::test_ior, test/inductor/test_ordered_set.py::TestSet::test_isdisjoint, test/inductor/test_ordered_set.py::TestSet::test_isub, test/inductor/test_ordered_set.py::TestSet::test_iterator_pickling, test/inductor/test_ordered_set.py::TestSet::test_ixor, test/inductor/test_ordered_set.py::TestSet::test_len, test/inductor/test_ordered_set.py::TestSet::test_new_or_init, test/inductor/test_ordered_set.py::TestSet::test_or, test/inductor/test_ordered_set.py::TestSet::test_pickling, test/inductor/test_ordered_set.py::TestSet::test_pop, test/inductor/test_ordered_set.py::TestSet::test_remove, test/inductor/test_ordered_set.py::TestSet::test_remove_keyerror_set, test/inductor/test_ordered_set.py::TestSet::test_remove_keyerror_unpacking, test/inductor/test_ordered_set.py::TestSet::test_rich_compare, test/inductor/test_ordered_set.py::TestSet::test_setOfFrozensets, test/inductor/test_ordered_set.py::TestSet::test_set_literal, test/inductor/test_ordered_set.py::TestSet::test_set_literal_evaluation_order, test/inductor/test_ordered_set.py::TestSet::test_set_literal_insertion_order, test/inductor/test_ordered_set.py::TestSet::test_sub, test/inductor/test_ordered_set.py::TestSet::test_sub_and_super, test/inductor/test_ordered_set.py::TestSet::test_subclass_with_custom_hash, test/inductor/test_ordered_set.py::TestSet::test_symmetric_difference, test/inductor/test_ordered_set.py::TestSet::test_symmetric_difference_update, test/inductor/test_ordered_set.py::TestSet::test_union, test/inductor/test_ordered_set.py::TestSet::test_uniquification, test/inductor/test_ordered_set.py::TestSet::test_update, test/inductor/test_ordered_set.py::TestSet::test_weakref, test/inductor/test_ordered_set.py::TestSet::test_xor, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_copy, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_empty_difference, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_empty_difference_rev, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_empty_intersection, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_empty_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_empty_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_empty_union, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_equivalent_equality, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_intersection_empty, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_isdisjoint_empty, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_issue_37219, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_iteration, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_length, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_pickling, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_repr, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_self_difference, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_self_equality, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_self_intersection, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_self_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_self_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_self_union, test/inductor/test_ordered_set.py::TestBasicOpsEmpty::test_union_empty, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_copy, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_empty_difference, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_empty_difference_rev, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_empty_intersection, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_empty_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_empty_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_empty_union, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_equivalent_equality, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_in, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_intersection_empty, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_isdisjoint_empty, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_issue_37219, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_iteration, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_length, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_not_in, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_pickling, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_repr, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_self_difference, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_self_equality, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_self_intersection, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_self_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_self_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_self_union, test/inductor/test_ordered_set.py::TestBasicOpsSingleton::test_union_empty, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_copy, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_empty_difference, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_empty_difference_rev, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_empty_intersection, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_empty_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_empty_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_empty_union, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_equivalent_equality, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_in, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_intersection_empty, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_isdisjoint_empty, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_issue_37219, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_iteration, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_length, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_not_in, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_pickling, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_repr, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_self_difference, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_self_equality, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_self_intersection, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_self_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_self_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_self_union, test/inductor/test_ordered_set.py::TestBasicOpsTuple::test_union_empty, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_copy, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_empty_difference, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_empty_difference_rev, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_empty_intersection, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_empty_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_empty_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_empty_union, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_equivalent_equality, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_intersection_empty, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_isdisjoint_empty, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_issue_37219, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_iteration, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_length, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_pickling, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_repr, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_self_difference, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_self_equality, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_self_intersection, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_self_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_self_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_self_union, test/inductor/test_ordered_set.py::TestBasicOpsTriple::test_union_empty, test/inductor/test_ordered_set.py::TestBasicOpsString::test_copy, test/inductor/test_ordered_set.py::TestBasicOpsString::test_empty_difference, test/inductor/test_ordered_set.py::TestBasicOpsString::test_empty_difference_rev, test/inductor/test_ordered_set.py::TestBasicOpsString::test_empty_intersection, test/inductor/test_ordered_set.py::TestBasicOpsString::test_empty_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsString::test_empty_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsString::test_empty_union, test/inductor/test_ordered_set.py::TestBasicOpsString::test_equivalent_equality, test/inductor/test_ordered_set.py::TestBasicOpsString::test_intersection_empty, test/inductor/test_ordered_set.py::TestBasicOpsString::test_isdisjoint_empty, test/inductor/test_ordered_set.py::TestBasicOpsString::test_issue_37219, test/inductor/test_ordered_set.py::TestBasicOpsString::test_iteration, test/inductor/test_ordered_set.py::TestBasicOpsString::test_length, test/inductor/test_ordered_set.py::TestBasicOpsString::test_pickling, test/inductor/test_ordered_set.py::TestBasicOpsString::test_repr, test/inductor/test_ordered_set.py::TestBasicOpsString::test_self_difference, test/inductor/test_ordered_set.py::TestBasicOpsString::test_self_equality, test/inductor/test_ordered_set.py::TestBasicOpsString::test_self_intersection, test/inductor/test_ordered_set.py::TestBasicOpsString::test_self_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsString::test_self_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsString::test_self_union, test/inductor/test_ordered_set.py::TestBasicOpsString::test_union_empty, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_copy, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_empty_difference, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_empty_difference_rev, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_empty_intersection, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_empty_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_empty_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_empty_union, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_equivalent_equality, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_intersection_empty, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_isdisjoint_empty, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_issue_37219, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_iteration, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_length, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_pickling, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_repr, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_self_difference, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_self_equality, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_self_intersection, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_self_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_self_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_self_union, test/inductor/test_ordered_set.py::TestBasicOpsBytes::test_union_empty, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_copy, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_empty_difference, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_empty_difference_rev, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_empty_intersection, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_empty_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_empty_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_empty_union, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_equivalent_equality, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_intersection_empty, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_isdisjoint_empty, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_issue_37219, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_iteration, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_length, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_pickling, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_repr, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_self_difference, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_self_equality, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_self_intersection, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_self_isdisjoint, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_self_symmetric_difference, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_self_union, test/inductor/test_ordered_set.py::TestBasicOpsMixedStringBytes::test_union_empty, test/inductor/test_ordered_set.py::TestExceptionPropagation::test_changingSizeWhileIterating, test/inductor/test_ordered_set.py::TestExceptionPropagation::test_instanceWithException, test/inductor/test_ordered_set.py::TestExceptionPropagation::test_instancesWithoutException, test/inductor/test_ordered_set.py::TestSetOfSets::test_constructor, test/inductor/test_ordered_set.py::TestBinaryOps::test_eq, test/inductor/test_ordered_set.py::TestBinaryOps::test_intersection_non_overlap, test/inductor/test_ordered_set.py::TestBinaryOps::test_intersection_overlap, test/inductor/test_ordered_set.py::TestBinaryOps::test_intersection_subset, test/inductor/test_ordered_set.py::TestBinaryOps::test_intersection_superset, test/inductor/test_ordered_set.py::TestBinaryOps::test_isdisjoint_non_overlap, test/inductor/test_ordered_set.py::TestBinaryOps::test_isdisjoint_overlap, test/inductor/test_ordered_set.py::TestBinaryOps::test_isdisjoint_subset, test/inductor/test_ordered_set.py::TestBinaryOps::test_isdisjoint_superset, test/inductor/test_ordered_set.py::TestBinaryOps::test_sym_difference_non_overlap, test/inductor/test_ordered_set.py::TestBinaryOps::test_sym_difference_overlap, test/inductor/test_ordered_set.py::TestBinaryOps::test_sym_difference_subset, test/inductor/test_ordered_set.py::TestBinaryOps::test_sym_difference_superset, test/inductor/test_ordered_set.py::TestBinaryOps::test_union_non_overlap, test/inductor/test_ordered_set.py::TestBinaryOps::test_union_overlap, test/inductor/test_ordered_set.py::TestBinaryOps::test_union_subset, test/inductor/test_ordered_set.py::TestBinaryOps::test_union_superset, test/inductor/test_ordered_set.py::TestUpdateOps::test_difference_method_call, test/inductor/test_ordered_set.py::TestUpdateOps::test_difference_non_overlap, test/inductor/test_ordered_set.py::TestUpdateOps::test_difference_overlap, test/inductor/test_ordered_set.py::TestUpdateOps::test_difference_subset, test/inductor/test_ordered_set.py::TestUpdateOps::test_difference_superset, test/inductor/test_ordered_set.py::TestUpdateOps::test_intersection_method_call, test/inductor/test_ordered_set.py::TestUpdateOps::test_intersection_non_overlap, test/inductor/test_ordered_set.py::TestUpdateOps::test_intersection_overlap, test/inductor/test_ordered_set.py::TestUpdateOps::test_intersection_subset, test/inductor/test_ordered_set.py::TestUpdateOps::test_intersection_superset, test/inductor/test_ordered_set.py::TestUpdateOps::test_sym_difference_method_call, test/inductor/test_ordered_set.py::TestUpdateOps::test_sym_difference_non_overlap, test/inductor/test_ordered_set.py::TestUpdateOps::test_sym_difference_overlap, test/inductor/test_ordered_set.py::TestUpdateOps::test_sym_difference_subset, test/inductor/test_ordered_set.py::TestUpdateOps::test_sym_difference_superset, test/inductor/test_ordered_set.py::TestUpdateOps::test_union_method_call, test/inductor/test_ordered_set.py::TestUpdateOps::test_union_non_overlap, test/inductor/test_ordered_set.py::TestUpdateOps::test_union_overlap, test/inductor/test_ordered_set.py::TestUpdateOps::test_union_subset, test/inductor/test_ordered_set.py::TestUpdateOps::test_union_superset, test/inductor/test_ordered_set.py::TestMutate::test_add_absent, test/inductor/test_ordered_set.py::TestMutate::test_add_present, test/inductor/test_ordered_set.py::TestMutate::test_add_until_full, test/inductor/test_ordered_set.py::TestMutate::test_clear, test/inductor/test_ordered_set.py::TestMutate::test_discard_absent, test/inductor/test_ordered_set.py::TestMutate::test_discard_present, test/inductor/test_ordered_set.py::TestMutate::test_pop, test/inductor/test_ordered_set.py::TestMutate::test_remove_absent, test/inductor/test_ordered_set.py::TestMutate::test_remove_present, test/inductor/test_ordered_set.py::TestMutate::test_remove_until_empty, test/inductor/test_ordered_set.py::TestMutate::test_update_empty_tuple, test/inductor/test_ordered_set.py::TestMutate::test_update_unit_tuple_non_overlap, test/inductor/test_ordered_set.py::TestMutate::test_update_unit_tuple_overlap, test/inductor/test_ordered_set.py::TestSubsets::test_issubset, test/inductor/test_ordered_set.py::TestSubsetEqualEmpty::test_issubset, test/inductor/test_ordered_set.py::TestSubsetEqualNonEmpty::test_issubset, test/inductor/test_ordered_set.py::TestSubsetEmptyNonEmpty::test_issubset, test/inductor/test_ordered_set.py::TestSubsetPartial::test_issubset, test/inductor/test_ordered_set.py::TestSubsetNonOverlap::test_issubset, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_difference, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_difference_update, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_difference_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_eq_ne, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_ge_gt_le_lt, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_intersection, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_intersection_update, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_intersection_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_sym_difference, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_sym_difference_update, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_sym_difference_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_union, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_update, test/inductor/test_ordered_set.py::TestOnlySetsNumeric::test_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_difference, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_difference_update, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_difference_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_eq_ne, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_ge_gt_le_lt, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_intersection, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_intersection_update, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_intersection_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_sym_difference, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_sym_difference_update, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_sym_difference_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_union, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_update, test/inductor/test_ordered_set.py::TestOnlySetsDict::test_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_difference, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_difference_update, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_difference_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_eq_ne, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_ge_gt_le_lt, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_intersection, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_intersection_update, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_intersection_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_sym_difference, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_sym_difference_update, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_sym_difference_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_union, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_update, test/inductor/test_ordered_set.py::TestOnlySetsOperator::test_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_difference, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_difference_update, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_difference_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_eq_ne, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_ge_gt_le_lt, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_intersection, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_intersection_update, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_intersection_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_sym_difference, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_sym_difference_update, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_sym_difference_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_union, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_update, test/inductor/test_ordered_set.py::TestOnlySetsTuple::test_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsString::test_difference, test/inductor/test_ordered_set.py::TestOnlySetsString::test_difference_update, test/inductor/test_ordered_set.py::TestOnlySetsString::test_difference_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsString::test_eq_ne, test/inductor/test_ordered_set.py::TestOnlySetsString::test_ge_gt_le_lt, test/inductor/test_ordered_set.py::TestOnlySetsString::test_intersection, test/inductor/test_ordered_set.py::TestOnlySetsString::test_intersection_update, test/inductor/test_ordered_set.py::TestOnlySetsString::test_intersection_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsString::test_sym_difference, test/inductor/test_ordered_set.py::TestOnlySetsString::test_sym_difference_update, test/inductor/test_ordered_set.py::TestOnlySetsString::test_sym_difference_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsString::test_union, test/inductor/test_ordered_set.py::TestOnlySetsString::test_update, test/inductor/test_ordered_set.py::TestOnlySetsString::test_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_difference, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_difference_update, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_difference_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_eq_ne, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_ge_gt_le_lt, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_intersection, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_intersection_update, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_intersection_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_sym_difference, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_sym_difference_update, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_sym_difference_update_operator, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_union, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_update, test/inductor/test_ordered_set.py::TestOnlySetsGenerator::test_update_operator, test/inductor/test_ordered_set.py::TestCopyingEmpty::test_copy, test/inductor/test_ordered_set.py::TestCopyingEmpty::test_deep_copy, test/inductor/test_ordered_set.py::TestCopyingSingleton::test_copy, test/inductor/test_ordered_set.py::TestCopyingSingleton::test_deep_copy, test/inductor/test_ordered_set.py::TestCopyingTriple::test_copy, test/inductor/test_ordered_set.py::TestCopyingTriple::test_deep_copy, test/inductor/test_ordered_set.py::TestCopyingTuple::test_copy, test/inductor/test_ordered_set.py::TestCopyingTuple::test_deep_copy, test/inductor/test_ordered_set.py::TestCopyingNested::test_copy, test/inductor/test_ordered_set.py::TestCopyingNested::test_deep_copy, test/inductor/test_ordered_set.py::TestIdentities::test_binopsVsSubsets, test/inductor/test_ordered_set.py::TestIdentities::test_commutativity, test/inductor/test_ordered_set.py::TestIdentities::test_exclusion, test/inductor/test_ordered_set.py::TestIdentities::test_summations, test/inductor/test_ordered_set.py::TestVariousIteratorArgs::test_constructor, test/inductor/test_ordered_set.py::TestVariousIteratorArgs::test_inline_methods, test/inductor/test_ordered_set.py::TestVariousIteratorArgs::test_inplace_methods, test/inductor/test_ordered_set.py::TestWeirdBugs::test_8420_set_merge, test/inductor/test_ordered_set.py::TestWeirdBugs::test_iter_and_mutate, test/inductor/test_ordered_set.py::TestWeirdBugs::test_merge_and_mutate, test/inductor/test_ordered_set.py::TestGraphs::test_cube, test/inductor/test_ordered_set.py::TestGraphs::test_cuboctahedron
2025-07-17T07:48:57.9485310Z 
2025-07-17T07:48:59.9867690Z Running test_compile_benchmark_util 1/1 ... [2025-07-17 07:48:59.986560]
2025-07-17T07:48:59.9868530Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:48:59.9870230Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_compile_benchmark_util.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:48:59.986856]
2025-07-17T07:49:01.9847010Z 
2025-07-17T07:49:01.9848980Z test_compile_benchmark_util 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_compile_benchmark_util_1.1_180038f7c535f1b4_.log
2025-07-17T07:49:01.9849820Z Running 1 items in this shard: test/test_compile_benchmark_util.py::TestCompileBenchmarkUtil::test_training_and_inference
2025-07-17T07:49:01.9850340Z 
2025-07-17T07:49:04.0154390Z Running export/test_passes 1/1 ... [2025-07-17 07:49:04.015242]
2025-07-17T07:49:04.0155140Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:04.0158380Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_passes.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:04.015533]
2025-07-17T07:49:07.2079460Z 
2025-07-17T07:49:07.2080370Z inductor/test_compiled_optimizers 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compiled_optimizers_1.1_7459bee6982ad777_.log
2025-07-17T07:49:07.2136540Z Running 213 items in this shard: test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_S429861, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adadelta_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adadelta_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adadelta_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adadelta_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adadelta_recompile, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adadelta_rho_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adadelta_rho_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adadelta_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adadelta_weight_decay_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adadelta_weight_decay_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adadelta_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_initial_accumulator_value_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_initial_accumulator_value_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_lr_decay_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_lr_decay_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_recompile, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_cpu_constantlr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_cpu_cosineannealinglr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_cpu_cosineannealingwarmrestarts, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_cpu_cycliclr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_cpu_exponentiallr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_cpu_lambdalr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_cpu_linearlr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_cpu_multiplicativelr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_cpu_multisteplr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_cpu_onecyclelr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_cpu_polynomiallr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_cpu_reducelronplateau, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_cpu_steplr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_mps_constantlr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_mps_cosineannealinglr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_mps_cosineannealingwarmrestarts, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_mps_cycliclr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_mps_exponentiallr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_mps_lambdalr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_mps_linearlr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_mps_multiplicativelr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_mps_multisteplr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_mps_onecyclelr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_mps_polynomiallr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_mps_reducelronplateau, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_tensor_lr_mps_steplr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_weight_decay_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_weight_decay_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adagrad_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_recompile, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_tensor_lr_mps_constantlr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_tensor_lr_mps_cosineannealinglr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_tensor_lr_mps_cosineannealingwarmrestarts, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_tensor_lr_mps_cycliclr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_tensor_lr_mps_exponentiallr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_tensor_lr_mps_lambdalr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_tensor_lr_mps_linearlr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_tensor_lr_mps_multiplicativelr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_tensor_lr_mps_multisteplr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_tensor_lr_mps_onecyclelr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_tensor_lr_mps_polynomiallr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_tensor_lr_mps_reducelronplateau, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_tensor_lr_mps_steplr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_weight_decay_amsgrad_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_weight_decay_amsgrad_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_weight_decay_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_weight_decay_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adam_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamax_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamax_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamax_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamax_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamax_recompile, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamax_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamax_weight_decay_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamax_weight_decay_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamax_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_recompile, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_tensor_lr_mps_constantlr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_tensor_lr_mps_cosineannealinglr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_tensor_lr_mps_cosineannealingwarmrestarts, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_tensor_lr_mps_cycliclr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_tensor_lr_mps_exponentiallr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_tensor_lr_mps_lambdalr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_tensor_lr_mps_linearlr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_tensor_lr_mps_multiplicativelr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_tensor_lr_mps_multisteplr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_tensor_lr_mps_onecyclelr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_tensor_lr_mps_polynomiallr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_tensor_lr_mps_reducelronplateau, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_tensor_lr_mps_steplr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_weight_decay_amsgrad_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_weight_decay_amsgrad_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_weight_decay_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_weight_decay_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_adamw_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_lambd_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_lambd_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_recompile_default, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_recompile_foreach, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_recompile_single, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_t0_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_t0_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_weight_decay_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_weight_decay_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_asgd_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_basic_shampoo, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_closure_graph_break, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_compile_time_smoketest, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_foreach_map_adam, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_get_value_on_static_address, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_guard_on_none_grads, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_nadam_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_nadam_momentum_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_nadam_momentum_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_nadam_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_nadam_recompile, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_nadam_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_nadam_weight_decay_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_nadam_weight_decay_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_nadam_weight_decay_momentum_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_nadam_weight_decay_momentum_decay_decoupled_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_nadam_weight_decay_momentum_decay_decoupled_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_nadam_weight_decay_momentum_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_nadam_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_radam_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_radam_eps_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_radam_eps_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_radam_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_radam_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_radam_weight_decay_decoupled_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_radam_weight_decay_decoupled_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_radam_weight_decay_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_radam_weight_decay_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_radam_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_maximize_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_maximize_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_recompile, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_weight_decay_centered_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_weight_decay_centered_momentum_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_weight_decay_centered_momentum_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_weight_decay_centered_momentum_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_weight_decay_centered_momentum_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_weight_decay_centered_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rmsprop_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rprop_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rprop_etas_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rprop_etas_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rprop_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rprop_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rprop_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rprop_recompile, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rprop_step_sizes_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_rprop_step_sizes_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_momentum_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_momentum_dampening_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_momentum_dampening_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_momentum_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_momentum_nesterov_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_momentum_nesterov_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_momentum_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_momentum_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_recompile_foreach, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_recompile_single, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_cpu_constantlr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_cpu_cosineannealinglr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_cpu_cosineannealingwarmrestarts, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_cpu_cycliclr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_cpu_exponentiallr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_cpu_lambdalr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_cpu_linearlr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_cpu_multiplicativelr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_cpu_multisteplr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_cpu_onecyclelr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_cpu_polynomiallr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_cpu_reducelronplateau, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_cpu_steplr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_mps_constantlr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_mps_cosineannealinglr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_mps_cosineannealingwarmrestarts, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_mps_cycliclr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_mps_exponentiallr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_mps_lambdalr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_mps_linearlr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_mps_multiplicativelr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_mps_multisteplr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_mps_onecyclelr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_mps_polynomiallr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_mps_reducelronplateau, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_tensor_lr_mps_steplr, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_weight_decay_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_weight_decay_maximize_cpu, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_weight_decay_maximize_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_sgd_weight_decay_mps, test/inductor/test_compiled_optimizers.py::CompiledOptimizerTests::test_static_address_finalizer
2025-07-17T07:49:07.2191720Z 
2025-07-17T07:49:09.2238580Z Running inductor/test_helion_kernels 1/1 ... [2025-07-17 07:49:09.223666]
2025-07-17T07:49:09.2239420Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:09.2241760Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_helion_kernels.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:09.223976]
2025-07-17T07:49:11.8149890Z 
2025-07-17T07:49:11.8151940Z inductor/test_helion_kernels 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_helion_kernels_1.1_484711711b083fa5_.log
2025-07-17T07:49:11.8154170Z Running 2 items in this shard: test/inductor/test_helion_kernels.py::HelionTests::test_add_kernel, test/inductor/test_helion_kernels.py::HelionTests::test_softmax_view_reshape
2025-07-17T07:49:11.8154660Z 
2025-07-17T07:49:13.8269760Z Running torch_np/test_random 1/1 ... [2025-07-17 07:49:13.826762]
2025-07-17T07:49:13.8270560Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:13.8271710Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'torch_np/test_random.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:13.827072]
2025-07-17T07:49:16.1696780Z 
2025-07-17T07:49:16.1697320Z torch_np/test_random 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_random_1.1_2e3db8d72d9e27ad_.log
2025-07-17T07:49:16.1706330Z Running 41 items in this shard: test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_func0, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_func1, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_func2, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_func3, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_func6, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_func7, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_random_random, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_False_random_sample, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_func0, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_func1, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_func2, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_func3, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_func6, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_func7, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_random_random, test/torch_np/test_random.py::TestScalarReturn::test_rndm_array_use_numpy_True_random_sample, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_func0, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_func1, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_func2, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_func3, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_func6, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_func7, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_random_random, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_False_random_sample, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_func0, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_func1, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_func2, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_func3, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_func6, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_func7, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_random_random, test/torch_np/test_random.py::TestScalarReturn::test_rndm_scalar_use_numpy_True_random_sample, test/torch_np/test_random.py::TestShuffle::test_1d_use_numpy_False, test/torch_np/test_random.py::TestShuffle::test_1d_use_numpy_True, test/torch_np/test_random.py::TestShuffle::test_2d_use_numpy_False, test/torch_np/test_random.py::TestShuffle::test_2d_use_numpy_True, test/torch_np/test_random.py::TestShuffle::test_shuffle_list_use_numpy_False, test/torch_np/test_random.py::TestShuffle::test_shuffle_list_use_numpy_True, test/torch_np/test_random.py::TestChoice::test_choice_use_numpy_False, test/torch_np/test_random.py::TestChoice::test_choice_use_numpy_True, test/torch_np/test_random.py::TestNumpyGlobal::test_numpy_global
2025-07-17T07:49:16.1714860Z 
2025-07-17T07:49:16.3046680Z 
2025-07-17T07:49:16.3047360Z export/test_passes 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_passes_1.1_c120c15e67834079_.log
2025-07-17T07:49:16.3052690Z Running 25 items in this shard: test/export/test_passes.py::TestPasses::test_constant_folding_pass, test/export/test_passes.py::TestPasses::test_custom_obj_tuple_out, test/export/test_passes.py::TestPasses::test_fakify_script_objects, test/export/test_passes.py::TestPasses::test_fakify_script_objects_properly_handle_containers, test/export/test_passes.py::TestPasses::test_functionalization_with_view_copy, test/export/test_passes.py::TestPasses::test_inline_, test/export/test_passes.py::TestPasses::test_math_ops, test/export/test_passes.py::TestPasses::test_move_to_device_pass, test/export/test_passes.py::TestPasses::test_predispatch_autocast, test/export/test_passes.py::TestPasses::test_predispatch_autocast_and_set_grad, test/export/test_passes.py::TestPasses::test_predispatch_set_grad, test/export/test_passes.py::TestPasses::test_remove_auto_functionalized_pass, test/export/test_passes.py::TestPasses::test_remove_auto_functionalized_pass_tuple, test/export/test_passes.py::TestPasses::test_remove_effect_token_kwargs, test/export/test_passes.py::TestPasses::test_runtime_assert_inline_constraints_for_cond, test/export/test_passes.py::TestPasses::test_runtime_assert_inline_constraints_for_item, test/export/test_passes.py::TestPasses::test_runtime_assert_inline_constraints_for_nonzero, test/export/test_passes.py::TestPasses::test_runtime_assert_multiple_dims, test/export/test_passes.py::TestPasses::test_runtime_assert_one_dim, test/export/test_passes.py::TestPasses::test_runtime_assert_some_dims_not_specified, test/export/test_passes.py::TestPasses::test_runtime_assert_some_inps_not_used, test/export/test_passes.py::TestPasses::test_sequential_split, test/export/test_passes.py::TestPasses::test_sequential_split_graph, test/export/test_passes.py::TestPasses::test_view_to_view_copy, test/export/test_passes.py::TestPasses::test_views_op_having_view_copy
2025-07-17T07:49:16.3057520Z 
2025-07-17T07:49:18.3970120Z Running inductor/test_alignment 1/1 ... [2025-07-17 07:49:18.396785]
2025-07-17T07:49:18.3970970Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:18.3972750Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_alignment.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:18.397077]
2025-07-17T07:49:18.4837180Z Running test_namedtensor 1/1 ... [2025-07-17 07:49:18.483552]
2025-07-17T07:49:18.4837860Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:18.4839570Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_namedtensor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:18.483852]
2025-07-17T07:49:21.0784970Z 
2025-07-17T07:49:21.0785720Z test_namedtensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_namedtensor_1.1_196ae4357b44eb2d_.log
2025-07-17T07:49:21.0806820Z Running 88 items in this shard: test/test_namedtensor.py::TestNamedTensor::test_aaa_must_run_first_check_experimental_warning, test/test_namedtensor.py::TestNamedTensor::test_addcmul_addcdiv, test/test_namedtensor.py::TestNamedTensor::test_addmm, test/test_namedtensor.py::TestNamedTensor::test_addmv, test/test_namedtensor.py::TestNamedTensor::test_align_as, test/test_namedtensor.py::TestNamedTensor::test_align_tensors, test/test_namedtensor.py::TestNamedTensor::test_align_tensors_two_inputs, test/test_namedtensor.py::TestNamedTensor::test_align_to, test/test_namedtensor.py::TestNamedTensor::test_align_to_ellipsis, test/test_namedtensor.py::TestNamedTensor::test_any_all, test/test_namedtensor.py::TestNamedTensor::test_as_strided, test/test_namedtensor.py::TestNamedTensor::test_as_strided_cuda, test/test_namedtensor.py::TestNamedTensor::test_autograd_ignores_names, test/test_namedtensor.py::TestNamedTensor::test_autograd_smoke, test/test_namedtensor.py::TestNamedTensor::test_autograd_warns_named_grad, test/test_namedtensor.py::TestNamedTensor::test_bernoulli, test/test_namedtensor.py::TestNamedTensor::test_big_tensor_repr_has_names, test/test_namedtensor.py::TestNamedTensor::test_binary_ops, test/test_namedtensor.py::TestNamedTensor::test_bitwise_not, test/test_namedtensor.py::TestNamedTensor::test_bmm, test/test_namedtensor.py::TestNamedTensor::test_cat, test/test_namedtensor.py::TestNamedTensor::test_cdist, test/test_namedtensor.py::TestNamedTensor::test_comparison_ops, test/test_namedtensor.py::TestNamedTensor::test_copy_transpose, test/test_namedtensor.py::TestNamedTensor::test_cummax_cummin, test/test_namedtensor.py::TestNamedTensor::test_detach, test/test_namedtensor.py::TestNamedTensor::test_diagonal, test/test_namedtensor.py::TestNamedTensor::test_dot, test/test_namedtensor.py::TestNamedTensor::test_equal, test/test_namedtensor.py::TestNamedTensor::test_expand, test/test_namedtensor.py::TestNamedTensor::test_factory_coverage, test/test_namedtensor.py::TestNamedTensor::test_factory_edge_cases, test/test_namedtensor.py::TestNamedTensor::test_flatten, test/test_namedtensor.py::TestNamedTensor::test_flatten_index_error, test/test_namedtensor.py::TestNamedTensor::test_flatten_nodims, test/test_namedtensor.py::TestNamedTensor::test_has_names, test/test_namedtensor.py::TestNamedTensor::test_index_fill, test/test_namedtensor.py::TestNamedTensor::test_info_smoke, test/test_namedtensor.py::TestNamedTensor::test_logcumsumexp, test/test_namedtensor.py::TestNamedTensor::test_logical_not, test/test_namedtensor.py::TestNamedTensor::test_logical_ops, test/test_namedtensor.py::TestNamedTensor::test_masked_fill, test/test_namedtensor.py::TestNamedTensor::test_masked_select, test/test_namedtensor.py::TestNamedTensor::test_matmul, test/test_namedtensor.py::TestNamedTensor::test_max_pooling, test/test_namedtensor.py::TestNamedTensor::test_max_pooling_without_names_does_not_warn, test/test_namedtensor.py::TestNamedTensor::test_mm, test/test_namedtensor.py::TestNamedTensor::test_mv, test/test_namedtensor.py::TestNamedTensor::test_no_jit_script_support, test/test_namedtensor.py::TestNamedTensor::test_no_jit_tracer_support, test/test_namedtensor.py::TestNamedTensor::test_no_multiprocessing_support, test/test_namedtensor.py::TestNamedTensor::test_no_pickle_support, test/test_namedtensor.py::TestNamedTensor::test_no_save_support, test/test_namedtensor.py::TestNamedTensor::test_noncontig_contiguous, test/test_namedtensor.py::TestNamedTensor::test_none_names_refcount, test/test_namedtensor.py::TestNamedTensor::test_nyi_dimname_overload_msg, test/test_namedtensor.py::TestNamedTensor::test_out_fn_semantics, test/test_namedtensor.py::TestNamedTensor::test_pow_special, test/test_namedtensor.py::TestNamedTensor::test_py3_ellipsis, test/test_namedtensor.py::TestNamedTensor::test_reduction_fns, test/test_namedtensor.py::TestNamedTensor::test_refine_names, test/test_namedtensor.py::TestNamedTensor::test_rename, test/test_namedtensor.py::TestNamedTensor::test_rename_, test/test_namedtensor.py::TestNamedTensor::test_rename_globber, test/test_namedtensor.py::TestNamedTensor::test_rename_rename_map, test/test_namedtensor.py::TestNamedTensor::test_repr, test/test_namedtensor.py::TestNamedTensor::test_resize, test/test_namedtensor.py::TestNamedTensor::test_select, test/test_namedtensor.py::TestNamedTensor::test_select_cuda, test/test_namedtensor.py::TestNamedTensor::test_set_names_property, test/test_namedtensor.py::TestNamedTensor::test_size, test/test_namedtensor.py::TestNamedTensor::test_split_fns_propagates_names, test/test_namedtensor.py::TestNamedTensor::test_squeeze, test/test_namedtensor.py::TestNamedTensor::test_stride, test/test_namedtensor.py::TestNamedTensor::test_support_device_named_grad, test/test_namedtensor.py::TestNamedTensor::test_tensor_from_lists, test/test_namedtensor.py::TestNamedTensor::test_tensor_from_named_tensor, test/test_namedtensor.py::TestNamedTensor::test_tensor_from_numpy, test/test_namedtensor.py::TestNamedTensor::test_tensor_from_tensor, test/test_namedtensor.py::TestNamedTensor::test_tensor_grad_is_unnamed, test/test_namedtensor.py::TestNamedTensor::test_transpose_variants, test/test_namedtensor.py::TestNamedTensor::test_trivial, test/test_namedtensor.py::TestNamedTensor::test_unary_propagate_names_fns, test/test_namedtensor.py::TestNamedTensor::test_unflatten, test/test_namedtensor.py::TestNamedTensor::test_unsupported_op_error_msg, test/test_namedtensor.py::TestNamedTensor::test_using_seen_interned_string_doesnt_bump_refcount, test/test_namedtensor.py::TestNamedTensor::test_using_unseen_interned_string_bumps_refcount_permanently, test/test_namedtensor.py::TestNamedTensor::test_using_unseen_uninterned_string_refcounts
2025-07-17T07:49:21.0821370Z 
2025-07-17T07:49:23.2825640Z Running export/test_package 1/1 ... [2025-07-17 07:49:23.282352]
2025-07-17T07:49:23.2826830Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:23.2828820Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_package.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:23.282649]
2025-07-17T07:49:25.9977210Z 
2025-07-17T07:49:25.9979220Z export/test_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_package_1.1_312d65ada20c4f44_.log
2025-07-17T07:49:25.9980280Z Running 4 items in this shard: test/export/test_package.py::TestPackage::test_basic, test/export/test_package.py::TestPackage::test_error, test/export/test_package.py::TestPackage::test_more_than_once, test/export/test_package.py::TestPackage::test_overloads
2025-07-17T07:49:25.9980960Z 
2025-07-17T07:49:28.0250630Z Running dynamo/test_config 1/1 ... [2025-07-17 07:49:28.024842]
2025-07-17T07:49:28.0251410Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:28.0253280Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_config.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:28.025162]
2025-07-17T07:49:29.6873310Z 
2025-07-17T07:49:29.6874410Z inductor/test_alignment 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_alignment_1.1_b91eb8242c7b8cbf_.log
2025-07-17T07:49:29.6877150Z Running 12 items in this shard: test/inductor/test_alignment.py::CpuTests::test_Q4_K_dequantization_cpu, test/inductor/test_alignment.py::CpuTests::test_alignment_without_custom_op_cpu, test/inductor/test_alignment.py::CpuTests::test_incorrect_meta_for_custom_op_2d_cpu, test/inductor/test_alignment.py::CpuTests::test_no_align_for_custom_op_2d_cpu, test/inductor/test_alignment.py::CpuTests::test_no_align_for_custom_op_cpu, test/inductor/test_alignment.py::CpuTests::test_slice_cpu, test/inductor/test_alignment.py::CpuTests::test_slice_view_dtype_size_1024_cpu, test/inductor/test_alignment.py::CpuTests::test_slice_view_dtype_size_1048576_cpu, test/inductor/test_alignment.py::CpuTests::test_slice_view_dtype_size_128_cpu, test/inductor/test_alignment.py::CpuTests::test_unaligned_input_2d_cpu, test/inductor/test_alignment.py::CpuTests::test_unaligned_input_cpu, test/inductor/test_alignment.py::CpuTests::test_view_dtype_slice_cpu
2025-07-17T07:49:29.6879480Z 
2025-07-17T07:49:30.9690800Z 
2025-07-17T07:49:30.9691770Z dynamo/test_config 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_config_1.1_c62afacb2357baf9_.log
2025-07-17T07:49:30.9693100Z Running 5 items in this shard: test/dynamo/test_config.py::ConfigTests::test_automatic_dynamic, test/dynamo/test_config.py::ConfigTests::test_config_compile_ignored, test/dynamo/test_config.py::ConfigTests::test_config_hash, test/dynamo/test_config.py::ConfigTests::test_no_assume_static_by_default, test/dynamo/test_config.py::ConfigTests::test_no_automatic_dynamic
2025-07-17T07:49:30.9694040Z 
2025-07-17T07:49:31.8935550Z Running inductor/test_cudacodecache 1/1 ... [2025-07-17 07:49:31.893352]
2025-07-17T07:49:31.8936380Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:31.8938250Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_cudacodecache.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:31.893645]
2025-07-17T07:49:33.2253080Z Running inductor/test_codecache 1/1 ... [2025-07-17 07:49:33.225106]
2025-07-17T07:49:33.2253400Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:33.2256910Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_codecache.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:33.225461]
2025-07-17T07:49:33.9821430Z 
2025-07-17T07:49:33.9823470Z inductor/test_cudacodecache 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cudacodecache_1.1_99793eb1eee911fe_.log
2025-07-17T07:49:33.9824800Z 
2025-07-17T07:49:36.0519570Z Running torch_np/numpy_tests/core/test_scalarinherit 1/1 ... [2025-07-17 07:49:36.051753]
2025-07-17T07:49:36.0519940Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:36.0521410Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'torch_np/numpy_tests/core/test_scalarinherit.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:36.052032]
2025-07-17T07:49:38.1442590Z 
2025-07-17T07:49:38.1443480Z torch_np/numpy_tests/core/test_scalarinherit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_scalarinherit_1.1_58d576e3d815392a_.log
2025-07-17T07:49:38.1444720Z Running 3 items in this shard: test/torch_np/numpy_tests/core/test_scalarinherit.py::TestInherit::test_gh_15395, test/torch_np/numpy_tests/core/test_scalarinherit.py::TestInherit::test_init, test/torch_np/numpy_tests/core/test_scalarinherit.py::TestInherit::test_init2
2025-07-17T07:49:38.1445450Z 
2025-07-17T07:49:40.1996970Z Running export/test_upgrader 1/1 ... [2025-07-17 07:49:40.199491]
2025-07-17T07:49:40.1997760Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:40.1999640Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_upgrader.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:40.199796]
2025-07-17T07:49:42.2343430Z 
2025-07-17T07:49:42.2343980Z export/test_upgrader 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_upgrader_1.1_00dcf69c2a97d600_.log
2025-07-17T07:49:42.2345810Z Running 6 items in this shard: test/export/test_upgrader.py::TestUpgrader::test_field_renaming_chain_from_v0_complete, test/export/test_upgrader.py::TestUpgrader::test_field_renaming_chain_from_v0_missing_field, test/export/test_upgrader.py::TestUpgrader::test_field_renaming_from_v1_partial_chain, test/export/test_upgrader.py::TestUpgrader::test_nn_module_stack_error_handling_invalid_type, test/export/test_upgrader.py::TestUpgrader::test_nn_module_stack_transformation_from_v0, test/export/test_upgrader.py::TestUpgrader::test_nodes_without_metadata_handled_gracefully
2025-07-17T07:49:42.2347270Z 
2025-07-17T07:49:44.2204680Z Running dynamo/test_compile 1/1 ... [2025-07-17 07:49:44.220264]
2025-07-17T07:49:44.2205470Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:44.2207280Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_compile.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:44.220557]
2025-07-17T07:49:49.2440870Z 
2025-07-17T07:49:49.2441690Z dynamo/test_compile 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_compile_1.1_fe200e10b24fe63b_.log
2025-07-17T07:49:49.2448240Z Running 17 items in this shard: test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_callback, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_callback_with_graph_break, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_constant_hasattr_fail, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_evnum_hasattr_fail, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_name_error, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_nn_module_invalid_method, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compilation_tensor_invalid_method, test/dynamo/test_compile.py::InPlaceCompilationTests::test_compile_eager_options, test/dynamo/test_compile.py::InPlaceCompilationTests::test_jit_save, test/dynamo/test_compile.py::InPlaceCompilationTests::test_list_bad_access, test/dynamo/test_compile.py::InPlaceCompilationTests::test_overwrite_call_impl, test/dynamo/test_compile.py::InPlaceCompilationTests::test_save, test/dynamo/test_compile.py::InPlaceCompilationTests::test_state_dict_save, test/dynamo/test_compile.py::InPlaceCompilationTests::test_to_sparse_to_dense_with_graph_break, test/dynamo/test_compile.py::InPlaceCompilationTests::test_torch_script_compilation, test/dynamo/test_compile.py::PublicTorchCompilerTests::test_dynamo_signatures
2025-07-17T07:49:49.2452380Z 
2025-07-17T07:49:51.2180230Z Running dynamo/test_after_aot 1/1 ... [2025-07-17 07:49:51.217833]
2025-07-17T07:49:51.2181000Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:51.2182680Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_after_aot.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:51.218120]
2025-07-17T07:49:55.7722400Z 
2025-07-17T07:49:55.7724300Z dynamo/test_after_aot 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_after_aot_1.1_d0361bd2071f67ab_.log
2025-07-17T07:49:55.7726920Z Running 2 items in this shard: test/dynamo/test_after_aot.py::TestAfterAot::test_dump_tensor, test/dynamo/test_after_aot.py::TestAfterAot::test_save_graph_repro
2025-07-17T07:49:55.7728000Z 
2025-07-17T07:49:57.7605990Z Running test_hub 1/1 ... [2025-07-17 07:49:57.760368]
2025-07-17T07:49:57.7606730Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:49:57.7608210Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_hub.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:49:57.760698]
2025-07-17T07:50:05.5369340Z 
2025-07-17T07:50:05.5369890Z dynamo/test_dynamic_shapes 2/3 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_dynamic_shapes_2.3_3202854424e1c6fb_.log
2025-07-17T07:50:05.5552830Z Running 641 items in this shard: test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_autocast_cpu_graph_break_2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_autocast_cpu_graph_break_inner_fn_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_autocast_float64_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_autocast_graph_break_method_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_cuda_event_across_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_cuda_event_method_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_cuda_stream_across_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_cuda_stream_context_manager1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_disable_saved_tensors_hooks_prev_disabled_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_generic_context_manager_with_graph_break_CustomizedCtxManager_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_generic_ctx_manager_with_graph_break_CustomizedCtxManagerWithGraphBreak_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_generic_ctx_manager_with_graph_break_customized_ctx_manager_with_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_graph_break_inlining_autocast_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_inactive_context_graph_break_local_nullctx2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_inactive_context_graph_break_stack2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_return_context_manager_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_sdpa_kernel_ctx_manager2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesCtxManagerTests::test_torch_profiler_use_after_with_block_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_add__dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_addcmul__dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_attrgetter_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_broadcast_foreach_pow_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_build_list_unpack_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_callable_list_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_callable_torch_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_cls_eq_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_cls_is_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_const_tuple_add2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_constant1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_context_wrapping_nested_functions_no_closure_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_custom_dict_kwargs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_default_dict_constr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_device_constant_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_device_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_fromkeys_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_key_set2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_key_set3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_ops_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_setdefault2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_update_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_update_kwargs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_dict_values_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_enumerate_custom_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_filter_with_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_flat_param_same_storage_size_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_float_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_fn_with_self_set_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_fstrings4_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_fstrings5_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_fstrings6_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_get_calculate_correct_fan_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_get_privateuse1_name_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_getattr_metaclass_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_globalvar_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_inline_jit_annotations_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_is_any_autocast_enabled_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_is_checkpoint_valid_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_is_contiguous_frame_counts_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_is_contiguous_memory_format_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_is_in_onnx_export_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_is_inference_recompilation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_is_integer_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_is_sparse_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_isinstance_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_itertools_chain_from_iterable_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_itertools_compress_tensors_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_itertools_pairwise_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_len_constant_misc_iterables_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_list_clear_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_list_compare_polyfill_non_lists_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_list_convert_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_list_expand_lhs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_list_setitem_slice_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_list_slice_assignment_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_listarg2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_listarg4_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_load_global_bool_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_lru_cache_warning_issued_during_tracing_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_dict_fromkeys_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_iter_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_list_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_list_slice_assign_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_max_const_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_sorted_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_str_join_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_map_with_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_methodcall1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_methodcaller_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_namedtuple_defaults_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_ndarray_method_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_ndarray_methods_returning_scalar_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_ndarray_reshape_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_no_recompile_inner_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_np_constant_collections_as_input_int_or_float_float_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_np_constant_collections_as_input_int_or_float_int_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_number_method_method_hex_num_type5_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_number_method_method_is_integer_num_type6_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_numpy_attributes_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_numpy_dtype_argument_to_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_numpy_dtype_call_in_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_numpy_size_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_obj_eq_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_as_input_UDF_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_as_input_partials_mod_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_graph_break_reconstruct_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___call___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___closure___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___defaults___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___dict___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___format___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___le___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___reduce_ex___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___repr___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr___str___dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr_func_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_attr_keywords_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_hasattr_set_attr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_lambda_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_partials_torch_op_arg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_pos_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_pow_int_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_promote_types_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_rand_inlined_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_reduce_with_initial_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_reduce_with_none_initial_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_return_numpy_ndarray_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_set_update_bytecode_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_slice1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_slice4_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_sorted_const_key_non_const_items_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_sourceless_build_method_type_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_symbool_to_int_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tensor_new_with_shape_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tensor_new_with_size_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tensor_size_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tensor_size_indexed_by_symint_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tensor_type3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tensor_type4_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tensor_type5_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tensor_type_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_torch_distributions_functions_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_torch_get_device_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_torch_size_as_dict_key_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_torch_size_hasattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_torch_source_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tuple1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_tuple2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_unary_fold_op_seq_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_unpack1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_unpack2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_unpack_ex3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_unpack_mutable_map_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFunctionTests::test_viamethod_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_312_binary_slice_with_graph_break1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_T_tensor_attribute_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_assert_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_backend_match_guard_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_backend_match_guard_multi_threads_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_backward_deterministic_mode_mismatch_warning_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_boolarg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_builder_for_class_with_metaclass_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_builtin_bool_on_symfloat_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_builtin_bool_on_symint_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_builtin_subclasses_as_method_on_class_type_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_builtin_subclasses_as_method_on_var_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_call_parent_non_class_methods_from_child_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_cannot_trace_mark_dynamic_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_cat_unbacked_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_class_duner_flags_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_closure_out_of_scope_cell_with_cond_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_closure_out_of_scope_cell_with_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_closure_write_across_functions_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_compare_shapes_neq_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_compare_shapes_tuple_eq_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_compare_shapes_tuple_neq_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_compare_shapes_with_constant_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_config_getattr_default_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_config_obj_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_const_dict_variable_python_type_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_custom_dict_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_data_ptr_graph_break_builtin_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dataclass_local_hasattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_default_dtype_change_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_defaultdict_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_derpy_nn_module_usage_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dtypes_no_graphbreaks_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dunder_new_function_inlining3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dynamic_shapes_as_strided_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dynamic_sources_dynamic_override_regex_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dynamo_cache_invalidate_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_dynamo_cache_move_to_front_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_enum_as_dict_key_with_overloaded_str_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_enum_guards_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_enum_method_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_enum_no_graphbreaks_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_existing_func_that_creates_capturing_nested_func_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_fn_hasattr__name__1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_fn_hasattr__name__2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_fold_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_free_var_and_local_name_collision_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_frozen_dataclass_default_value_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_frozen_dict_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_frozenset_torch_func_contains_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_funcname_cache_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_function_generic_alias_annotation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_generate_trivial_abstract_impl_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_get_cache_entry_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_grad_non_none_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_graph_break_correctly_when_passing_numpy_ndarray_to_torch_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_guard_failure_fn_tensor_iter_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_guard_filter_fn_by_is_global_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_guard_filter_inbuilt_nn_modules_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_guard_filter_tensors_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_guard_function_builder_with_cse_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_guard_size_oblivious_simplification_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_guards_strip_function_call_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_hash_getitem_slice_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_id_guarded_class_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_id_guarded_object_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_id_of_nn_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_if_cond_nn_mod2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_inference_mode_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_inline_dict_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_inline_dict_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_inline_module_attr_dict_clear_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_inline_user_defined_dict_attr_clear_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_inspect_signature_bind_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_item_changes_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_iter_set_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_iter_type_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_iterator_limit_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_itertools_groupby_pure_python_default_identify_func_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_itertools_infinite_repeat_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_itertools_islice_default_end_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_itertools_islice_default_step_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_itertools_repeat_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_large_reduction_list_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_linear_module_free_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_list_hasattr2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_list_iadd_with_shape_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_list_iterator_contains_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_list_slice_mul_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_listcomp_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_load_fast_and_clear_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_mark_dynamic_with_ranges_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_module_deepcopy_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_mutable_mapping_multiple_inheritance_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_named_parameters_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_namedtuple_class_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_ne_operator_with_custom_graphbreak_eq_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_nested_closure_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_nested_optimize_decorator_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_nested_sequential_try_with_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_new_with_int_list_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_newly_constructed_tensor_attr_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_no_raise_guard_partial_constraint_across_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numel_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_fallback_on_eager_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_force_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_ndarray_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_ndarray_graph_break_with_multiple_outputs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_no_raise_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_readonly_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_subdtype_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_take_along_axis_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_tolist_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_variable_isinstance_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_numpy_with_builtin_type_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_object_setattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_object_staticmethod_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_onnx_shape_as_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_optimize_on_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_os_environ_get_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_os_environ_set_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_pep0479_convert_stopiteration_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_precompile_entry_hit_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_precompile_fail_on_recompile_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_pt2_compliant_ops_are_allowed_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_raise_guard_partial_constraint_across_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_raise_on_backend_error_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_raises_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_range_input_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_range_iter_guards_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_recompile_message_on_parameter_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_release_input_memory_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_release_scope_memory_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_remove_set_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_repeat_interleave_graphbreaks_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_return_dict_with_graph_break_and_update_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_return_nested_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_returning_func_with_captured_func_and_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_returning_nested_func_with_captured_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_runtime_assert_replacement_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_scalar_device_movement_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_scalar_tensor_is_equivalent_to_symint_list_argument_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_sequential_module_free_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_set_custom_tensor_attribute_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_set_descriptor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_set_update_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_setattr_mutation3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_shape_and_tuple_equality_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_shape_env_equal_evaluate_expr_divisible_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_shape_env_equal_runtime_assert_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_shape_env_equal_unbacked_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_shape_int_comparisons_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_shape_int_inplace_binops_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_sourceless_namedtuple_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_str_format_assert2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_stride_dim_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_structseq1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_sym_and_terms_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_symint_copy_into_unbacked_slice_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_sys_modules_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_ctor_list_of_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_dict2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_dict3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_dot_grad_no_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_dynamic_method_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_iter_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_layout_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_setattr_getset_descriptor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tensor_types_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_torch_check_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_torch_check_symbolic_shape_rel_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_torch_guards_stack_frame_register_inlining_deep_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_torch_package_working_with_trace_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_torch_size_numel_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tracing_nested_py_tree_mixed_all_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_tuple_mul_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_type_copy_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_typing_dict_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_typing_typevar_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_unbacked_empty_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_unbacked_sources_scalar_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_unbacked_sources_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_unpack4_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_unpack_tensor_shape_mismatch_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_user_defined_binop_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_user_defined_class_name_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_user_defined_class_python_type_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_user_defined_iter_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_user_defined_setattr1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_user_getattr2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_validate_outputs_unbacked_by_custom_op_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_validate_outputs_unbacked_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_write_to_cells_with_name_shadowing_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_writes_to_cells_across_frames2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesMiscTests::test_yield_from_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_Size_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_as_strided_on_existing_view_banned_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_batch_encoding_clone_inputs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_bigbird_unsqueeze_inplace_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_bitwise_op_guard_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_c_defined_metaclass_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_class_member_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_classmethod_with_slots_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_compile_complex_conj_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_compile_copy__int_overload_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_const_dict_keyerror_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_data_attr_mutation_after_saved_for_bw_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_dataclass_init_with_default_factory_with_inputs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_ddp_checkpoint_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_dedup_global_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_delattr_raises_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_delattr_return_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_do_paste_mask_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_dont_aggressively_write_assert_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_dynamic_shapes_float_guard_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_ephemeral_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_flip_bad_accuracy_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_for_loop_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_functools_wraps_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_generator_dealloc_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_get_parameter_dtype_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_graph_break_on_jit_isinstance_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_guard_fail_nested_tuple_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_guard_with_tuple_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_hf_gelu_inline_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_hf_xsoftmax_inference_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_incompatible_configs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_inductor_no_recursionerror_on_for_loops_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_inlining_cornercase_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_int_format_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_intermediate_leaf_requires_grad_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_is_make_fx_tracing_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_issue111522_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_issue111918_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_issue114171_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_issue126128_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_issue1466_size_aot_autograd_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_issue175_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_jit_script_defaults_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_jit_trace_errors_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_list_index_not_found_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_longformer_chunk_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_maml_no_item_capture_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_map_with_multiple_args_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_method_overriding_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_multi_dot_import_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_multi_import_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_negative_floor_div_solve_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_negative_shape_guard_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_nn_param_freevar_codegen_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_no_grad_inline_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_numpy_tobytes_no_error_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_omegaconf_listconfig_contains_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_optimized_deepcopy_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_optimized_module_patched_init_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_out_nested_cell_shape_change_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_out_root_cell_shape_change_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_pointless_graph_removal_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_primtorch_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_randint_out_dynamic_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_recursive_map_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_reformer_eval_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_reformer_train_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_restricted_list_subclass3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_return_value_duplication_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_rewrite_assert_dont_change_bytecode_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_rewrite_assert_noop_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_sort_out_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_split_with_sizes_aot_autograd_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_str_isalnum_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_super_in_staticmethod_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_super_staticmethod_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_swin_base_tensor_attr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_tensor_data_kwarg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_tensor_set_data_backend_aot_eager_func_name_func2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_tensor_set_data_backend_eager_func_name_func1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_tensor_set_data_backend_inductor_func_name_func3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_torch_variable_type_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_torchname_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_tuple_enum_as_key_dict_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_udf_classes_reconstruction_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_unpack_hooks_dont_run_during_tracing_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_unspecialized_nn_module_with_torch_variable_attribute_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_unsqueeze_mul_strides_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_user_defined_object_callable_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_vc_bumped_in_inference_graph_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_weakref_callback_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_weakref_construction_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_weakref_reconstruct_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesReproTests::test_with_on_graph_break_nested_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_basicmodule2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_conv_call_super_forward_directly_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_conv_transpose_call_forward_directly_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_conv_transpose_call_super_forward_directly_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_fnmember_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_forward_directly_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_generation_tag_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_inject_module_parameters_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_iseval2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_istraining1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_istraining2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_lazy_module1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_lazy_module2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_lazy_module4_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_lazy_module7_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_lazy_module_kwargs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_lazy_module_no_cls_to_become_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_module_call_module_with_static_forward_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_module_name_string_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_moduledict_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_modulelist_custom_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_nn_module_setattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_nn_moduledict_contains_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_parameterdict_custom_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_parameters3_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_seq_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_sequential_with_duplicated_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_simple_torch_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_submodules1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_torch_function_with_closure_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_torch_mangled_class_name_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_unsupportedmethod_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesNNModuleTests::test_unsupportedmodule_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_access_class_method_from_user_class_attr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_access_class_method_from_user_class_builtin_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_byte_tensor_does_not_crash_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_capture_symbolic_tracing_within_fake_mode_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_cond_free_variables_overlapping_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_cond_op_param_buffer_lifted_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_cond_raise_user_error_on_branch_args_mismatch_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_cond_raise_user_error_on_branch_return_non_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_cond_raise_user_error_on_missing_args_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_cond_raise_user_error_on_non_list_operands_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_cond_supported_pred_types_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_constraint_violation_error_messages_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_dupes_and_bypass_reorder_with_non_tensor_arg_with_aten_graph_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_dupes_and_bypass_with_non_tensor_arg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_dupes_and_bypass_with_non_tensor_output_with_aten_graph_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_empty_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_compare_optimize_with_make_fx_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_cond_in_aten_symbolic_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_control_flow_with_getattr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_defaults_ok_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_dynamic_control_flow_error_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_dynamic_dim_cleanup_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_dynamic_dim_range_constraint_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_graph_with_complex_reorder_with_aten_graph_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_graph_with_list_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_identity_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_meta_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_mismatched_out_2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_mismatched_out_2_with_aten_graph_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_mismatched_out_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_module_specify_constraints_signature_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_pass_arg_by_name_star_args_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_preserve_constraints_as_metadata_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_raise_on_relationship_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_builtin_op_on_assume_constant_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_cond_with_closed_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_constant_free_function_and_class_method_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_constant_free_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_constant_global_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_constant_list_nonzero_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_constant_list_nonzero_free_function_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_constant_none_control_flow_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_constant_not_none_control_flow_pos_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_functools_wrapped_fn_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_kwargs_with_default_None_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_kwargs_with_default_float_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_map_cond_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_module_layer_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_shallow_list_copy_with_side_effects_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_export_with_stack_trace_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_func_return_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_input_container_type_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_invalid_input_global_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_list_not_contains_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_list_unpack_with_aten_graph_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_mixed_real_and_fake_inputs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_multiple_outputs_op_with_evaluator_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_nested_cond_op_param_buffer_lifted_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_no_tensor_computation_fail_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_not_functionalize_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_pre_dispatch_simple_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_predispatch_with_for_out_dtype_nested_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_predispatch_with_higher_order_nested_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_preserve_fx_node_metadata_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_retracibility_nested_list_out_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_symbolic_tracing_within_fake_mode_with_constraints_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_uncaptured_higher_order_op_error_not_suppresed_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesExportTests::test_zeroes_in_new_shape_scalar_out_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_capi_call2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_control_flow2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_control_flow4_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_enumerate_not_break_graph_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_no_graph_break_on_item_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_pop_after_resume_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_restore_range_iter_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_restore_state_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_resume1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesSubGraphTests::test_resume_with_no_grad1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_access_module_attr_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_capture_constants_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_capture_global_num_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_capture_input_num_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_capture_numpy_number_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_capture_tracked_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_capture_tracked_nested_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_capture_untracked_nonlocal_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_concat_unbacked_shape_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_cond_side_effect_in_one_branches_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_cond_source_fn_stack_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_dynamic_shapes_over_vmap_batch_size_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_enum_arg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_error_message_sane_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_fallback_on_graph_break_complicated_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_hooks_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_inlined_functions_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_internal_nonlocal_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_lift_tensor_constant_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_map_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_map_multi_return_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_map_side_effect_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_map_subgraph_name_is_valid_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_modules_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_output_with_dict_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_register_mode_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_same_freevar_twice_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_del_existing_attr_global_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_del_existing_attr_global_obj_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_in_body_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_mutate_global_num_builtin_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_mutate_global_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_mutate_nonlocal_tensor_builtin_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_nested_nonlocal_list_append_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_nonlocal_list_append_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_set_existing_attr_nonlocal_obj_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_set_new_attr_global_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_side_effect_set_new_attr_nonlocal_module_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_tensor_to_list_closure_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_wrap_all_kwarg_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_wrap_kwarg_default_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_wrap_kwarg_default_if_branch_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_wrap_kwarg_recompile_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesHigherOrderOpTests::test_wrap_pytree_args_with_symint_constant_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_grad_capture_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_grad_freevar_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_grad_pytree_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_grad_with_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_grad_with_side_effect_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_jacfwd_randomness_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_jacrev_has_aux_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vjp_call_compiled_backward_fn_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vjp_multiple_outputs_python_struct_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_call_torch_compile_fn_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_free_tensor_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_multiple_invocation_in_dims_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_pytree_inputs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_recompile_different_config_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_recompile_with_randomness_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_two_inputs_tuple_in_dims_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_with_graph_break_2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesFuncTorchHigherOrderOpTests::test_vmap_with_graph_break_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_aot_autograd_expand_mutation_backwards_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_aot_autograd_expand_mutation_error_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_aot_autograd_expand_mutation_functionalizes_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_aot_autograd_raises_invalid_leaf_set_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_aot_export_joint_simple_repro_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_arg_dupe_via_dynamo_recompiles_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_arg_dupe_via_dynamo_recompiles_many_args_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_arg_dupe_via_dynamo_recompiles_many_with_global_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_call_fn_with_non_const_inputs_aot_unsafe_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_data_ptr_access_fails_in_backward_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_donated_buffer1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_donated_buffer2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_donated_buffer5_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_donated_buffer_with_retain_or_create_graph2_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_donated_buffer_with_retain_or_create_graph4_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_double_backward_errors_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_grad_inputs_alias_inputs_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_multiple_aot_autograd_calls_dupe_args_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_mutation1_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_mutation_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_negative_testing_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_nn_parameter_construction_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesAotAutogradFallbackTests::test_no_storage_overlap_guards_no_aliasing_dynamic_shapes, test/dynamo/test_dynamic_shapes.py::DynamicShapesTestSDPA::test_graph_break_SDPAParams_dynamic_shapes
2025-07-17T07:50:05.5726010Z 
2025-07-17T07:50:07.4245730Z Running dynamo/test_autograd_function 1/1 ... [2025-07-17 07:50:07.424407]
2025-07-17T07:50:07.4246560Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:07.4248090Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_autograd_function.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:07.424684]
2025-07-17T07:50:10.7943950Z 
2025-07-17T07:50:10.7945030Z test_hub 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_hub_1.1_6fee09a28b52f076_.log
2025-07-17T07:50:10.7948170Z Running 20 items in this shard: test/test_hub.py::TestHub::test_download_url_to_file, test/test_hub.py::TestHub::test_get_set_dir, test/test_hub.py::TestHub::test_hub_parse_repo_info, test/test_hub.py::TestHub::test_list_entrypoints, test/test_hub.py::TestHub::test_load_commit_from_forked_repo, test/test_hub.py::TestHub::test_load_from_branch, test/test_hub.py::TestHub::test_load_from_github, test/test_hub.py::TestHub::test_load_from_local_dir, test/test_hub.py::TestHub::test_load_legacy_zip_checkpoint, test/test_hub.py::TestHub::test_load_state_dict_from_url, test/test_hub.py::TestHub::test_load_zip_1_6_checkpoint, test/test_hub.py::TestHub::test_trust_repo_builtin_trusted_owners, test/test_hub.py::TestHub::test_trust_repo_check_no, test/test_hub.py::TestHub::test_trust_repo_check_yes, test/test_hub.py::TestHub::test_trust_repo_false_emptystring, test/test_hub.py::TestHub::test_trust_repo_false_no, test/test_hub.py::TestHub::test_trust_repo_legacy, test/test_hub.py::TestHub::test_trust_repo_none, test/test_hub.py::TestHub::test_trust_repo_true, test/test_hub.py::TestHub::test_trusted_repo_false_yes
2025-07-17T07:50:10.7950970Z 
2025-07-17T07:50:12.8384280Z Running export/test_db 1/1 ... [2025-07-17 07:50:12.838230]
2025-07-17T07:50:12.8384990Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:12.8386820Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_db.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:12.838542]
2025-07-17T07:50:13.7388470Z 
2025-07-17T07:50:13.7389200Z dynamo/test_autograd_function 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_autograd_function_1.1_f7a9b9c64f04dd78_.log
2025-07-17T07:50:13.7399670Z Running 40 items in this shard: test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_allow_in_graph, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_amp_custom_fwd_bwd, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_assert_is_contiguous_after_matmul, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_assert_is_contiguous_on_grad_output_directly, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_autograd_function_equivalence, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_autograd_function_has_graph_break, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_backward_returns_none_for_tensor_input, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_classmethod, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_data_in_bwd, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_default_values, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_enum_arg, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_forward_returns_constant, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_function_context_mark_and_save, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_function_context_save_and_mark, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_function_with_bound_free_variable, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_fwd_no_grad, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_fwd_propogation_correctness, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_linear_setup_context, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_mark_multi_output_non_differentiable, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_mark_non_differentiable, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_materialize_grad, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_multi_output, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_multiple_different_non_tensor_inputs, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_needs_input_grad, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_once_differentiable, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_print_in_bwd, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_repeated_save_for_backward_calls, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_requires_grad_in_bwd, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_save_for_bwd, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_set_materialize_grads_no_graph_break, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_smoke_from_test_autograd, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_smuggle_symint_issue_111031, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_smuggle_tensor_and_complex_structures, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_stride_in_bwd, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_tensor_list_as_input, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_tensor_subclass_intermediary_input, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_triton_kernel_basic, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_triton_kernel_multiple_out, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_tuple_arg, test/dynamo/test_autograd_function.py::AutogradFunctionTests::test_user_defined_object_as_input
2025-07-17T07:50:13.7409590Z 
2025-07-17T07:50:15.7810350Z Running test_optim 1/1 ... [2025-07-17 07:50:15.780844]
2025-07-17T07:50:15.7811100Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:15.7813100Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_optim.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:15.781177]
2025-07-17T07:50:20.1300570Z 
2025-07-17T07:50:20.1301110Z inductor/test_codecache 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_codecache_1.1_9b8ae01895b022d1_.log
2025-07-17T07:50:20.1370120Z Running 209 items in this shard: test/inductor/test_codecache.py::TestPyCodeCache::test_linemaps_empty, test/inductor/test_codecache.py::TestFxGraphCache::test_async_compile_cache, test/inductor/test_codecache.py::TestFxGraphCache::test_auto_functionalized_caching_variant_v1, test/inductor/test_codecache.py::TestFxGraphCache::test_auto_functionalized_caching_variant_v2, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_clear, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_guard, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_guard_overspec, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_hot_load_device_cpu_bfloat16_dynamic_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_hot_load_device_cpu_bfloat16_dynamic_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_hot_load_device_cpu_float32_dynamic_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_hot_load_device_cpu_float32_dynamic_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_hot_load_device_mps_bfloat16_dynamic_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_hot_load_device_mps_bfloat16_dynamic_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_hot_load_device_mps_float32_dynamic_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_hot_load_device_mps_float32_dynamic_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_hot_load_empty, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_hot_load_generic, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_hot_load_pgo, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_hot_load_pgo_swap_file_names, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_hot_load_repeat, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_True_bundle_triton_False_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_True_bundle_triton_False_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_True_bundle_triton_False_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_True_bundle_triton_False_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_True_bundle_triton_True_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_True_bundle_triton_True_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_True_bundle_triton_True_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_bfloat16_dynamic_True_bundle_triton_True_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_False_bundle_triton_False_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_False_bundle_triton_False_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_True_bundle_triton_False_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_True_bundle_triton_False_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_True_bundle_triton_False_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_True_bundle_triton_False_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_True_bundle_triton_True_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_True_bundle_triton_True_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_True_bundle_triton_True_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_cpu_float32_dynamic_True_bundle_triton_True_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_True_bundle_triton_False_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_True_bundle_triton_False_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_True_bundle_triton_False_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_True_bundle_triton_False_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_True_bundle_triton_True_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_True_bundle_triton_True_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_True_bundle_triton_True_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_bfloat16_dynamic_True_bundle_triton_True_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_False_bundle_triton_False_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_False_bundle_triton_False_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_True_bundle_triton_False_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_True_bundle_triton_False_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_True_bundle_triton_False_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_True_bundle_triton_False_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_True_bundle_triton_True_use_static_cuda_launcher_False_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_True_bundle_triton_True_use_static_cuda_launcher_False_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_True_bundle_triton_True_use_static_cuda_launcher_True_grad_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_function_device_mps_float32_dynamic_True_bundle_triton_True_use_static_cuda_launcher_True_grad_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_model_device_cpu_float32_dynamic_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_model_device_cpu_float32_dynamic_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_model_device_cpu_float64_dynamic_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_model_device_cpu_float64_dynamic_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_model_device_mps_float32_dynamic_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_model_device_mps_float32_dynamic_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_model_device_mps_float64_dynamic_False, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_model_device_mps_float64_dynamic_True, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_with_guards_int32_bounds_device_mps_bfloat16, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_with_guards_int32_bounds_device_mps_float16, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_with_guards_static_bounds_device_cpu_bfloat16, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_with_guards_static_bounds_device_cpu_float32, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_with_guards_static_bounds_device_mps_bfloat16, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_load_with_guards_static_bounds_device_mps_float32, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_with_nt, test/inductor/test_codecache.py::TestFxGraphCache::test_cache_with_symint_non_arg_guard, test/inductor/test_codecache.py::TestFxGraphCache::test_constant_handling_device_cpu, test/inductor/test_codecache.py::TestFxGraphCache::test_constant_handling_device_mps, test/inductor/test_codecache.py::TestFxGraphCache::test_flex_attention_caching, test/inductor/test_codecache.py::TestFxGraphCache::test_freezing_device_cpu_inlinable_False, test/inductor/test_codecache.py::TestFxGraphCache::test_freezing_device_cpu_inlinable_True, test/inductor/test_codecache.py::TestFxGraphCache::test_freezing_device_mps_inlinable_False, test/inductor/test_codecache.py::TestFxGraphCache::test_freezing_device_mps_inlinable_True, test/inductor/test_codecache.py::TestFxGraphCache::test_generated_kernel_count, test/inductor/test_codecache.py::TestFxGraphCache::test_higher_order_op_bypass_bundle_triton_False, test/inductor/test_codecache.py::TestFxGraphCache::test_higher_order_op_bypass_bundle_triton_True, test/inductor/test_codecache.py::TestFxGraphCache::test_inductor_counters, test/inductor/test_codecache.py::TestFxGraphCache::test_no_arguments_tensor_device_guards, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_bfloat16_dynamic_True_bundle_triton_False_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_bfloat16_dynamic_True_bundle_triton_False_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_bfloat16_dynamic_True_bundle_triton_True_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_bfloat16_dynamic_True_bundle_triton_True_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_float32_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_float32_dynamic_False_bundle_triton_False_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_float32_dynamic_True_bundle_triton_False_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_float32_dynamic_True_bundle_triton_False_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_float32_dynamic_True_bundle_triton_True_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_cpu_float32_dynamic_True_bundle_triton_True_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_bfloat16_dynamic_False_bundle_triton_False_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_bfloat16_dynamic_False_bundle_triton_True_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_bfloat16_dynamic_True_bundle_triton_False_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_bfloat16_dynamic_True_bundle_triton_False_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_bfloat16_dynamic_True_bundle_triton_True_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_bfloat16_dynamic_True_bundle_triton_True_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_float32_dynamic_False_bundle_triton_False_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_float32_dynamic_False_bundle_triton_False_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_float32_dynamic_False_bundle_triton_True_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_float32_dynamic_True_bundle_triton_False_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_float32_dynamic_True_bundle_triton_False_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_float32_dynamic_True_bundle_triton_True_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_remote_cache_load_function_device_mps_float32_dynamic_True_bundle_triton_True_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_tensor_device_guards_cpu_tensor, test/inductor/test_codecache.py::TestFxGraphCache::test_triton_higher_order_op_bundle_triton_False, test/inductor/test_codecache.py::TestFxGraphCache::test_triton_higher_order_op_bundle_triton_True, test/inductor/test_codecache.py::TestFxGraphCache::test_triton_higher_order_op_different_configs_bundle_triton_False, test/inductor/test_codecache.py::TestFxGraphCache::test_triton_higher_order_op_different_configs_bundle_triton_True, test/inductor/test_codecache.py::TestFxGraphCache::test_triton_op_bundle_triton_False_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_triton_op_bundle_triton_False_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestFxGraphCache::test_triton_op_bundle_triton_True_use_static_cuda_launcher_False, test/inductor/test_codecache.py::TestFxGraphCache::test_triton_op_bundle_triton_True_use_static_cuda_launcher_True, test/inductor/test_codecache.py::TestStandaloneCompile::test_backend_dynamic_shapes_from_example_inputs, test/inductor/test_codecache.py::TestStandaloneCompile::test_backend_dynamic_shapes_from_graph, test/inductor/test_codecache.py::TestStandaloneCompile::test_backend_dynamic_shapes_from_tracing_context, test/inductor/test_codecache.py::TestStandaloneCompile::test_backend_static_shapes_dynamic_shapes_from_example_inputs, test/inductor/test_codecache.py::TestStandaloneCompile::test_backend_static_shapes_dynamic_shapes_from_graph, test/inductor/test_codecache.py::TestStandaloneCompile::test_backend_static_shapes_dynamic_shapes_from_tracing_context, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_cpu_format_binary_dynamic_False_graph_partition_False, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_cpu_format_binary_dynamic_False_graph_partition_True, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_cpu_format_binary_dynamic_True_graph_partition_False, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_cpu_format_binary_dynamic_True_graph_partition_True, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_cpu_format_unpacked_dynamic_False_graph_partition_False, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_cpu_format_unpacked_dynamic_False_graph_partition_True, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_cpu_format_unpacked_dynamic_True_graph_partition_False, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_cpu_format_unpacked_dynamic_True_graph_partition_True, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_mps_format_binary_dynamic_False_graph_partition_False, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_mps_format_binary_dynamic_False_graph_partition_True, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_mps_format_binary_dynamic_True_graph_partition_False, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_mps_format_binary_dynamic_True_graph_partition_True, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_mps_format_unpacked_dynamic_False_graph_partition_False, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_mps_format_unpacked_dynamic_False_graph_partition_True, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_mps_format_unpacked_dynamic_True_graph_partition_False, test/inductor/test_codecache.py::TestStandaloneCompile::test_basic_device_mps_format_unpacked_dynamic_True_graph_partition_True, test/inductor/test_codecache.py::TestStandaloneCompile::test_call_in_backend_dynamic_False, test/inductor/test_codecache.py::TestStandaloneCompile::test_call_in_backend_dynamic_True, test/inductor/test_codecache.py::TestStandaloneCompile::test_custom_pass_handling, test/inductor/test_codecache.py::TestStandaloneCompile::test_different_process, test/inductor/test_codecache.py::TestStandaloneCompile::test_dynamic_shapes_from_example_inputs_config_patches_False, test/inductor/test_codecache.py::TestStandaloneCompile::test_dynamic_shapes_from_example_inputs_config_patches_True, test/inductor/test_codecache.py::TestStandaloneCompile::test_dynamic_shapes_from_graph, test/inductor/test_codecache.py::TestStandaloneCompile::test_modify_unpacked_file_device_cpu, test/inductor/test_codecache.py::TestStandaloneCompile::test_modify_unpacked_file_device_mps, test/inductor/test_codecache.py::TestStandaloneCompile::test_save_in_new_path, test/inductor/test_codecache.py::TestStandaloneCompile::test_split_module, test/inductor/test_codecache.py::TestStandaloneCompile::test_static_shapes_dynamic_shapes_from_example_inputs, test/inductor/test_codecache.py::TestStandaloneCompile::test_static_shapes_dynamic_shapes_from_graph, test/inductor/test_codecache.py::TestFxGraphCacheHashing::test_bypass_unsupported, test/inductor/test_codecache.py::TestFxGraphCacheHashing::test_get_hash_for_files, test/inductor/test_codecache.py::TestFxGraphCacheHashing::test_hash_config_changes, test/inductor/test_codecache.py::TestFxGraphCacheHashing::test_hash_custom_backend_pass, test/inductor/test_codecache.py::TestFxGraphCacheHashing::test_hash_custom_passes, test/inductor/test_codecache.py::TestFxGraphCacheHashing::test_hash_fake_tensors, test/inductor/test_codecache.py::TestFxGraphCacheHashing::test_hash_kwargs, test/inductor/test_codecache.py::TestFxGraphCacheHashing::test_hash_private_config_changes, test/inductor/test_codecache.py::TestFxGraphCacheHashing::test_non_serializable_custom_passes_causes_cache_miss, test/inductor/test_codecache.py::TestFxGraphCacheHashing::test_parameter_constants, test/inductor/test_codecache.py::TestFxGraphCacheHashing::test_stable_strings, test/inductor/test_codecache.py::TestCudaCompileCommand::test_cuda_compile_command, test/inductor/test_codecache.py::TestAutotuneCache::test_autotune_cache, test/inductor/test_codecache.py::TestAutotuneCache::test_autotune_cache_warm_start, test/inductor/test_codecache.py::TestAutotuneCache::test_bundled_autotune_remote_cache, test/inductor/test_codecache.py::TestAutotuneCache::test_modified_autotune_cache_remote_cache_False, test/inductor/test_codecache.py::TestAutotuneCache::test_modified_autotune_cache_remote_cache_True, test/inductor/test_codecache.py::TestRemoteAOTAutogradCache::test_autograd_remote_cache, test/inductor/test_codecache.py::TestRemoteAOTAutogradCache::test_autograd_remote_lazy_backward, test/inductor/test_codecache.py::TestUtils::test_force_disable_coordinate_descent, test/inductor/test_codecache.py::TestUtils::test_fresh_cache
2025-07-17T07:50:20.1437510Z 
2025-07-17T07:50:22.1064670Z Running inductor/test_profiler 1/1 ... [2025-07-17 07:50:22.106255]
2025-07-17T07:50:22.1065450Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:22.1067340Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_profiler.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:22.106553]
2025-07-17T07:50:24.5693220Z 
2025-07-17T07:50:24.5693970Z export/test_db 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_db_1.1_98b80983976b024d_.log
2025-07-17T07:50:24.5702550Z Running 36 items in this shard: test/export/test_db.py::ExampleTests::test_exportdb_not_supported_case_dynamic_shape_round, test/export/test_db.py::ExampleTests::test_exportdb_not_supported_case_model_attr_mutation, test/export/test_db.py::ExampleTests::test_exportdb_not_supported_case_optional_input, test/export/test_db.py::ExampleTests::test_exportdb_not_supported_case_unsupported_operator, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_assume_constant_result, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_autograd_function, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_class_method, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_cond_branch_class_method, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_cond_branch_nested_function, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_cond_branch_nonlocal_variables, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_cond_closed_over_variable, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_cond_operands, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_cond_predicate, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_constrain_as_size_example, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_constrain_as_value_example, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_decorator, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_dictionary, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_dynamic_shape_assert, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_dynamic_shape_constructor, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_dynamic_shape_if_guard, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_dynamic_shape_map, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_dynamic_shape_slicing, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_dynamic_shape_view, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_fn_with_kwargs, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_list_contains, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_list_unpack, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_nested_function, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_null_context_manager, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_pytree_flatten, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_scalar_output, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_specialized_attribute, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_static_for_loop, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_static_if, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_tensor_setattr, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_type_reflection_method, test/export/test_db.py::ExampleTests::test_exportdb_supported_case_user_input_mutation
2025-07-17T07:50:24.5710660Z 
2025-07-17T07:50:24.6551030Z 
2025-07-17T07:50:24.6551560Z inductor/test_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_profiler_1.1_26083f88ba0355e9_.log
2025-07-17T07:50:24.6552020Z 
2025-07-17T07:50:26.7161310Z Running inductor/test_cpu_select_algorithm 1/1 ... [2025-07-17 07:50:26.715935]
2025-07-17T07:50:26.7162230Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:26.7163660Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_cpu_select_algorithm.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:26.716242]
2025-07-17T07:50:26.8448380Z Running dynamo/test_cudagraphs_expandable_segments 1/1 ... [2025-07-17 07:50:26.844658]
2025-07-17T07:50:26.8448760Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:26.8450630Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_cudagraphs_expandable_segments.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:26.844959]
2025-07-17T07:50:29.0970690Z 
2025-07-17T07:50:29.0971410Z dynamo/test_cudagraphs_expandable_segments 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_expandable_segments_1.1_1430a59c052d24cb_.log
2025-07-17T07:50:29.0971960Z 
2025-07-17T07:50:29.7219350Z 
2025-07-17T07:50:29.7324980Z inductor/test_cpu_select_algorithm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_select_algorithm_1.1_8a978e7b15f4c37d_.log
2025-07-17T07:50:29.7428050Z 
2025-07-17T07:50:31.2480880Z Running inductor/test_halide 1/1 ... [2025-07-17 07:50:31.247886]
2025-07-17T07:50:31.2481650Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:31.2483320Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_halide.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:31.248175]
2025-07-17T07:50:31.8972060Z Running inductor/test_online_softmax 1/1 ... [2025-07-17 07:50:31.896992]
2025-07-17T07:50:31.8972440Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:31.8973870Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_online_softmax.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:31.897282]
2025-07-17T07:50:34.0858300Z 
2025-07-17T07:50:34.0859210Z inductor/test_halide 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_halide_1.1_73a99979bdead54c_.log
2025-07-17T07:50:34.0859670Z 
2025-07-17T07:50:34.5053020Z 
2025-07-17T07:50:34.5053930Z inductor/test_online_softmax 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_online_softmax_1.1_a4970e50243f20ef_.log
2025-07-17T07:50:34.5054410Z 
2025-07-17T07:50:36.3044530Z Running inductor/test_inplacing_pass 1/1 ... [2025-07-17 07:50:36.303883]
2025-07-17T07:50:36.3045000Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:36.3045990Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_inplacing_pass.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:36.304239]
2025-07-17T07:50:36.5750440Z Running inductor/test_fxir_backend 1/1 ... [2025-07-17 07:50:36.563370]
2025-07-17T07:50:36.5852120Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:36.5955240Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_fxir_backend.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:36.563634]
2025-07-17T07:50:39.1150640Z 
2025-07-17T07:50:39.1151340Z inductor/test_inplacing_pass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inplacing_pass_1.1_5114745ed6f26c4b_.log
2025-07-17T07:50:39.1151820Z 
2025-07-17T07:50:39.3516380Z 
2025-07-17T07:50:39.3517210Z inductor/test_fxir_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_fxir_backend_1.1_a87660a1cc55608e_.log
2025-07-17T07:50:39.3517760Z 
2025-07-17T07:50:41.4180060Z Running inductor/test_layout_optim 1/1 ... [2025-07-17 07:50:41.417823]
2025-07-17T07:50:41.4180400Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:41.4182370Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_layout_optim.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:41.418155]
2025-07-17T07:50:41.6414990Z Running xpu/test_gemm 1/1 ... [2025-07-17 07:50:41.641346]
2025-07-17T07:50:41.6515130Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:41.6517570Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'xpu/test_gemm.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:41.641616]
2025-07-17T07:50:43.9487950Z 
2025-07-17T07:50:43.9488850Z xpu/test_gemm 1/1 was successful, full logs can be found in artifacts with path test/test-reports/xpu.test_gemm_1.1_3d7f1c672ecec7e8_.log
2025-07-17T07:50:43.9489310Z Running 0 items in this shard:
2025-07-17T07:50:43.9489450Z 
2025-07-17T07:50:44.2044920Z 
2025-07-17T07:50:44.2045470Z inductor/test_layout_optim 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_layout_optim_1.1_255ce00590b8d2e1_.log
2025-07-17T07:50:44.2046010Z 
2025-07-17T07:50:46.2988410Z Running inductor/test_memory 1/1 ... [2025-07-17 07:50:46.298711]
2025-07-17T07:50:46.2988750Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:46.2992140Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_memory.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:46.299062]
2025-07-17T07:50:46.5753960Z Running inductor/test_dependencies 1/1 ... [2025-07-17 07:50:46.568407]
2025-07-17T07:50:46.5872440Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:46.5958260Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_dependencies.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:46.568680]
2025-07-17T07:50:49.1211870Z 
2025-07-17T07:50:49.1212860Z inductor/test_memory 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_memory_1.1_5c5f0179e90b5492_.log
2025-07-17T07:50:49.1213290Z 
2025-07-17T07:50:49.4569500Z 
2025-07-17T07:50:49.4570120Z inductor/test_dependencies 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_dependencies_1.1_27f0809efc563631_.log
2025-07-17T07:50:49.4570880Z 
2025-07-17T07:50:51.3994880Z Running dynamo/test_python_dispatcher 1/1 ... [2025-07-17 07:50:51.399314]
2025-07-17T07:50:51.3995230Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:51.4000610Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_python_dispatcher.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:51.399928]
2025-07-17T07:50:51.6405100Z Running test_pruning_op 1/1 ... [2025-07-17 07:50:51.640362]
2025-07-17T07:50:51.6505240Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:51.6608180Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_pruning_op.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:51.640637]
2025-07-17T07:50:54.1632380Z 
2025-07-17T07:50:54.1633460Z test_pruning_op 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_pruning_op_1.1_f349c19cee4cfcc1_.log
2025-07-17T07:50:54.1637000Z Running 2 items in this shard: test/test_pruning_op.py::PruningOpTest::test_rowwise_prune_op_32bit_indices, test/test_pruning_op.py::PruningOpTest::test_rowwise_prune_op_64bit_indices
2025-07-17T07:50:54.1637500Z 
2025-07-17T07:50:54.3731250Z 
2025-07-17T07:50:54.3732350Z dynamo/test_python_dispatcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_python_dispatcher_1.1_371a92324a90960e_.log
2025-07-17T07:50:54.3734710Z Running 6 items in this shard: test/dynamo/test_python_dispatcher.py::PythonDispatcherTests::test_dispatch_key1, test/dynamo/test_python_dispatcher.py::PythonDispatcherTests::test_dispatch_key2, test/dynamo/test_python_dispatcher.py::PythonDispatcherTests::test_dispatch_key3, test/dynamo/test_python_dispatcher.py::PythonDispatcherTests::test_dispatch_key4, test/dynamo/test_python_dispatcher.py::PythonDispatcherTests::test_dispatch_key_set_guard, test/dynamo/test_python_dispatcher.py::PythonDispatcherTests::test_functorch_interpreter
2025-07-17T07:50:54.3736200Z 
2025-07-17T07:50:56.6114210Z Running test_set_default_mobile_cpu_allocator 1/1 ... [2025-07-17 07:50:56.611284]
2025-07-17T07:50:56.6114580Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:56.6116890Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_set_default_mobile_cpu_allocator.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:56.611583]
2025-07-17T07:50:56.7413100Z Running test_monitor 1/1 ... [2025-07-17 07:50:56.741133]
2025-07-17T07:50:56.7413610Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:50:56.7417420Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_monitor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:50:56.741626]
2025-07-17T07:50:59.1627440Z 
2025-07-17T07:50:59.1628510Z test_set_default_mobile_cpu_allocator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_set_default_mobile_cpu_allocator_1.1_5311acc824d54a76_.log
2025-07-17T07:50:59.1630110Z Running 2 items in this shard: test/test_set_default_mobile_cpu_allocator.py::TestSetDefaultMobileCPUAllocator::test_exception, test/test_set_default_mobile_cpu_allocator.py::TestSetDefaultMobileCPUAllocator::test_no_exception
2025-07-17T07:50:59.1630750Z 
2025-07-17T07:50:59.6070390Z 
2025-07-17T07:50:59.6071520Z test_monitor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_monitor_1.1_f9697b2c68a23baa_.log
2025-07-17T07:50:59.6073270Z Running 6 items in this shard: test/test_monitor.py::TestMonitor::test_event_handler, test/test_monitor.py::TestMonitor::test_fixed_count_stat, test/test_monitor.py::TestMonitor::test_interval_stat, test/test_monitor.py::TestMonitor::test_log_event, test/test_monitor.py::TestMonitor::test_wait_counter, test/test_monitor.py::TestMonitorTensorboard::test_event_handler
2025-07-17T07:50:59.6074250Z 
2025-07-17T07:51:01.5897250Z Running dynamo/test_verify_correctness 1/1 ... [2025-07-17 07:51:01.589568]
2025-07-17T07:51:01.5897670Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:51:01.5900640Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_verify_correctness.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:51:01.589953]
2025-07-17T07:51:01.9383390Z Running dynamo/test_logging 1/1 ... [2025-07-17 07:51:01.938244]
2025-07-17T07:51:01.9383670Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:51:01.9411110Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_logging.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:51:01.939273]
2025-07-17T07:51:04.5018220Z 
2025-07-17T07:51:04.5019230Z dynamo/test_verify_correctness 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_verify_correctness_1.1_aa4f50888899fc16_.log
2025-07-17T07:51:04.5021130Z Running 4 items in this shard: test/dynamo/test_verify_correctness.py::TestVerifyCorrectness::test_example_inputs, test/dynamo/test_verify_correctness.py::TestVerifyCorrectness::test_incorrect_verify_false, test/dynamo/test_verify_correctness.py::TestVerifyCorrectness::test_incorrect_verify_true, test/dynamo/test_verify_correctness.py::TestVerifyCorrectness::test_torchscript
2025-07-17T07:51:04.5023490Z 
2025-07-17T07:51:06.8094770Z Running dynamo/test_package 1/1 ... [2025-07-17 07:51:06.809324]
2025-07-17T07:51:06.8095120Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:51:06.8098000Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_package.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:51:06.809685]
2025-07-17T07:51:18.1947390Z 
2025-07-17T07:51:18.1947930Z dynamo/test_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_logging_1.1_95c3a8bc2a74b0b6_.log
2025-07-17T07:51:18.1958760Z Running 51 items in this shard: test/dynamo/test_logging.py::LoggingTests::test_all, test/dynamo/test_logging.py::LoggingTests::test_aot, test/dynamo/test_logging.py::LoggingTests::test_aot_graphs, test/dynamo/test_logging.py::LoggingTests::test_aot_joint_graph, test/dynamo/test_logging.py::LoggingTests::test_autotuning, test/dynamo/test_logging.py::LoggingTests::test_bytecode, test/dynamo/test_logging.py::LoggingTests::test_cudagraph_static_inputs, test/dynamo/test_logging.py::LoggingTests::test_cudagraphs, test/dynamo/test_logging.py::LoggingTests::test_custom_format, test/dynamo/test_logging.py::LoggingTests::test_custom_format_exc, test/dynamo/test_logging.py::LoggingTests::test_ddp_graphs, test/dynamo/test_logging.py::LoggingTests::test_default_logging, test/dynamo/test_logging.py::LoggingTests::test_distributed_rank_logging, test/dynamo/test_logging.py::LoggingTests::test_dump_compile_times, test/dynamo/test_logging.py::LoggingTests::test_dynamo_debug, test/dynamo/test_logging.py::LoggingTests::test_dynamo_debug_default_off_artifacts, test/dynamo/test_logging.py::LoggingTests::test_dynamo_error, test/dynamo/test_logging.py::LoggingTests::test_dynamo_info, test/dynamo/test_logging.py::LoggingTests::test_fusion, test/dynamo/test_logging.py::LoggingTests::test_graph_breaks, test/dynamo/test_logging.py::LoggingTests::test_graph_region_expansion, test/dynamo/test_logging.py::LoggingTests::test_guards_polyfill_sloc, test/dynamo/test_logging.py::LoggingTests::test_guards_recompiles, test/dynamo/test_logging.py::LoggingTests::test_guards_sloc, test/dynamo/test_logging.py::LoggingTests::test_guards_sloc_vr, test/dynamo/test_logging.py::LoggingTests::test_hierarchical_compile, test/dynamo/test_logging.py::LoggingTests::test_inductor_debug, test/dynamo/test_logging.py::LoggingTests::test_inductor_error, test/dynamo/test_logging.py::LoggingTests::test_inductor_info, test/dynamo/test_logging.py::LoggingTests::test_invalid_artifact_flag, test/dynamo/test_logging.py::LoggingTests::test_invalid_artifact_flag_error_msg, test/dynamo/test_logging.py::LoggingTests::test_kernel_code, test/dynamo/test_logging.py::LoggingTests::test_log_traced_frames, test/dynamo/test_logging.py::LoggingTests::test_logs_out, test/dynamo/test_logging.py::LoggingTests::test_multiline_format, test/dynamo/test_logging.py::LoggingTests::test_open_registration, test/dynamo/test_logging.py::LoggingTests::test_open_registration_python_api, test/dynamo/test_logging.py::LoggingTests::test_open_registration_with_registered_parent, test/dynamo/test_logging.py::LoggingTests::test_optimizer_non_static_param, test/dynamo/test_logging.py::LoggingTests::test_output_code, test/dynamo/test_logging.py::LoggingTests::test_recompiles, test/dynamo/test_logging.py::LoggingTests::test_schedule, test/dynamo/test_logging.py::LoggingTests::test_trace_call, test/dynamo/test_logging.py::LoggingTests::test_trace_call_graph_break, test/dynamo/test_logging.py::LoggingTests::test_trace_call_inline_call, test/dynamo/test_logging.py::LoggingTests::test_trace_call_prefix, test/dynamo/test_logging.py::LoggingTests::test_trace_source_cond, test/dynamo/test_logging.py::LoggingTests::test_trace_source_funcname, test/dynamo/test_logging.py::LoggingTests::test_trace_source_if_stmt, test/dynamo/test_logging.py::LoggingTests::test_trace_source_nested, test/dynamo/test_logging.py::LoggingTests::test_trace_source_simple
2025-07-17T07:51:18.1968090Z 
2025-07-17T07:51:20.3729270Z Running dynamo/test_backends 1/1 ... [2025-07-17 07:51:20.372761]
2025-07-17T07:51:20.3729620Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:51:20.3731780Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_backends.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:51:20.373086]
2025-07-17T07:51:25.7929970Z 
2025-07-17T07:51:25.7930590Z dynamo/test_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_package_1.1_24515ad8f9abfb30_.log
2025-07-17T07:51:25.7942350Z Running 41 items in this shard: test/dynamo/test_package.py::TestPackage::test_automatic_dynamo_graph_breaks_device_cpu, test/dynamo/test_package.py::TestPackage::test_automatic_dynamo_graph_breaks_device_cuda, test/dynamo/test_package.py::TestPackage::test_automatic_dynamo_graph_breaks_device_xpu, test/dynamo/test_package.py::TestPackage::test_automatic_dynamo_lazy_backward_device_cpu, test/dynamo/test_package.py::TestPackage::test_automatic_dynamo_lazy_backward_device_cuda, test/dynamo/test_package.py::TestPackage::test_automatic_dynamo_lazy_backward_device_xpu, test/dynamo/test_package.py::TestPackage::test_automatic_dynamo_recompiles_device_cpu, test/dynamo/test_package.py::TestPackage::test_automatic_dynamo_recompiles_device_cuda, test/dynamo/test_package.py::TestPackage::test_automatic_dynamo_recompiles_device_xpu, test/dynamo/test_package.py::TestPackage::test_automatic_dynamo_serialize_device_cpu, test/dynamo/test_package.py::TestPackage::test_automatic_dynamo_serialize_device_cuda, test/dynamo/test_package.py::TestPackage::test_automatic_dynamo_serialize_device_xpu, test/dynamo/test_package.py::TestPackage::test_basic_fn_backend_eager_device_cpu, test/dynamo/test_package.py::TestPackage::test_basic_fn_backend_eager_device_cuda, test/dynamo/test_package.py::TestPackage::test_basic_fn_backend_eager_device_xpu, test/dynamo/test_package.py::TestPackage::test_basic_fn_backend_inductor_device_cpu, test/dynamo/test_package.py::TestPackage::test_basic_fn_backend_inductor_device_cuda, test/dynamo/test_package.py::TestPackage::test_basic_fn_backend_inductor_device_xpu, test/dynamo/test_package.py::TestPackage::test_dynamic_shape_backend_eager_device_cpu, test/dynamo/test_package.py::TestPackage::test_dynamic_shape_backend_eager_device_cuda, test/dynamo/test_package.py::TestPackage::test_dynamic_shape_backend_eager_device_xpu, test/dynamo/test_package.py::TestPackage::test_dynamic_shape_backend_inductor_device_cpu, test/dynamo/test_package.py::TestPackage::test_dynamic_shape_backend_inductor_device_cuda, test/dynamo/test_package.py::TestPackage::test_dynamic_shape_backend_inductor_device_xpu, test/dynamo/test_package.py::TestPackage::test_dynamo_cache_manual_load_device_cpu, test/dynamo/test_package.py::TestPackage::test_dynamo_cache_manual_load_device_cuda, test/dynamo/test_package.py::TestPackage::test_dynamo_cache_manual_load_device_xpu, test/dynamo/test_package.py::TestPackage::test_file_change, test/dynamo/test_package.py::TestPackage::test_graph_break_bomb_backend_eager_device_cpu, test/dynamo/test_package.py::TestPackage::test_graph_break_bomb_backend_eager_device_cuda, test/dynamo/test_package.py::TestPackage::test_graph_break_bomb_backend_eager_device_xpu, test/dynamo/test_package.py::TestPackage::test_graph_break_bomb_backend_inductor_device_cpu, test/dynamo/test_package.py::TestPackage::test_graph_break_bomb_backend_inductor_device_cuda, test/dynamo/test_package.py::TestPackage::test_graph_break_bomb_backend_inductor_device_xpu, test/dynamo/test_package.py::TestPackage::test_lazy_backward_backend_eager_device_cpu, test/dynamo/test_package.py::TestPackage::test_lazy_backward_backend_eager_device_cuda, test/dynamo/test_package.py::TestPackage::test_lazy_backward_backend_eager_device_xpu, test/dynamo/test_package.py::TestPackage::test_lazy_backward_backend_inductor_device_cpu, test/dynamo/test_package.py::TestPackage::test_lazy_backward_backend_inductor_device_cuda, test/dynamo/test_package.py::TestPackage::test_lazy_backward_backend_inductor_device_xpu, test/dynamo/test_package.py::TestPackage::test_nn_module
2025-07-17T07:51:25.7952090Z 
2025-07-17T07:51:27.8906330Z Running inductor/test_torchbind 1/1 ... [2025-07-17 07:51:27.890457]
2025-07-17T07:51:27.8907470Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:51:27.8915810Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_torchbind.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:51:27.890940]
2025-07-17T07:51:28.4320380Z 
2025-07-17T07:51:28.4321270Z dynamo/test_backends 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_backends_1.1_108d851fa01ae162_.log
2025-07-17T07:51:28.4326310Z Running 21 items in this shard: test/dynamo/test_backends.py::NormalizeIRTests::test_inplace_normalize, test/dynamo/test_backends.py::MPSSupportedTest::test_mps_supported, test/dynamo/test_backends.py::TestExplainWithBackend::test_explain_with_backend, test/dynamo/test_backends.py::TestCustomBackendAPI::test_aot_autograd_api, test/dynamo/test_backends.py::TestCustomBackendAPI::test_backend_graph_freeze, test/dynamo/test_backends.py::TestCustomBackendAPI::test_backend_recompilation, test/dynamo/test_backends.py::TestCustomBackendAPI::test_lookup_backend, test/dynamo/test_backends.py::TestCustomBackendAPI::test_lookup_custom_backend, test/dynamo/test_backends.py::TestCustomBackendAPI::test_register_backend_api, test/dynamo/test_backends.py::TestOptimizationsCPU::test_aot_cudagraphs_cpu, test/dynamo/test_backends.py::TestOptimizationsCPU::test_aot_eager_cpu, test/dynamo/test_backends.py::TestOptimizationsCPU::test_aot_eager_decomp_partition_cpu, test/dynamo/test_backends.py::TestOptimizationsCPU::test_aot_ts_cpu, test/dynamo/test_backends.py::TestOptimizationsCPU::test_eager_cpu, test/dynamo/test_backends.py::TestOptimizationsCPU::test_eager_noexcept_cpu, test/dynamo/test_backends.py::TestOptimizationsCPU::test_example_inputs_cpu, test/dynamo/test_backends.py::TestOptimizationsCPU::test_example_inputs_runtime_use_cpu, test/dynamo/test_backends.py::TestOptimizationsCPU::test_intel_gaudi_backend_cpu, test/dynamo/test_backends.py::TestOptimizationsCPU::test_list_backends_cpu, test/dynamo/test_backends.py::TestOptimizationsCPU::test_torchscript_cpu, test/dynamo/test_backends.py::TestOptimizationsCPU::test_tvm_cpu
2025-07-17T07:51:28.4330900Z 
2025-07-17T07:51:30.5281420Z Running export/test_serialize 1/1 ... [2025-07-17 07:51:30.527996]
2025-07-17T07:51:30.5281730Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:51:30.5285060Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_serialize.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:51:30.528380]
2025-07-17T07:51:30.9414190Z 
2025-07-17T07:51:30.9516980Z inductor/test_torchbind 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchbind_1.1_8a18db01c3d1e7a5_.log
2025-07-17T07:51:30.9618180Z Running 16 items in this shard: test/inductor/test_torchbind.py::TestTorchbind::test_aoti_torchbind_name_collision, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_aot_compile, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_aot_compile_constant_folding, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_aoti, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_compile, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_compile_gpu_op_symint_graph_partition, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_compile_symint, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_config_not_generated, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_get_buf_bytes, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_hop_schema, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_hop_schema_no_input, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_hop_schema_no_output, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_inductor, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_input_aot_compile, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_list_return_aot_compile, test/inductor/test_torchbind.py::TestTorchbind::test_torchbind_queue
2025-07-17T07:51:30.9621690Z 
2025-07-17T07:51:33.1287460Z Running test_segment_reductions 1/1 ... [2025-07-17 07:51:33.128543]
2025-07-17T07:51:33.1288250Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:51:33.1290200Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_segment_reductions.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:51:33.128863]
2025-07-17T07:51:35.9226540Z 
2025-07-17T07:51:35.9227540Z test_segment_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_segment_reductions_1.1_76175f67ab92fe30_.log
2025-07-17T07:51:35.9250050Z Running 74 items in this shard: test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_unsafe_flag_cpu_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_unsafe_flag_cpu_int64
2025-07-17T07:51:35.9272110Z 
2025-07-17T07:51:38.0858500Z Running inductor/test_auto_functionalize 1/1 ... [2025-07-17 07:51:38.085664]
2025-07-17T07:51:38.0858850Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:51:38.0860900Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_auto_functionalize.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:51:38.085989]
2025-07-17T07:51:38.8234160Z 
2025-07-17T07:51:38.8235420Z export/test_serialize 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_serialize_1.1_8c585f095ebbb300_.log
2025-07-17T07:51:38.8258490Z Running 98 items in this shard: test/export/test_serialize.py::TestSerialize::test_canonicalize, test/export/test_serialize.py::TestSerialize::test_export_example_inputs_preserved, test/export/test_serialize.py::TestSerialize::test_export_with_extension_op_serialization, test/export/test_serialize.py::TestSerialize::test_int_list, test/export/test_serialize.py::TestSerialize::test_kwargs_default, test/export/test_serialize.py::TestSerialize::test_metadata_parsing_with_layer_split, test/export/test_serialize.py::TestSerialize::test_metadata_run_decomp_serder, test/export/test_serialize.py::TestSerialize::test_multi_return_some_unused, test/export/test_serialize.py::TestSerialize::test_nested_layer_split, test/export/test_serialize.py::TestSerialize::test_nonfinite_inputs, test/export/test_serialize.py::TestSerialize::test_predispatch_export_with_autograd_op, test/export/test_serialize.py::TestSerialize::test_rational_ranges, test/export/test_serialize.py::TestSerialize::test_serialize_constant_outputs, test/export/test_serialize.py::TestSerialize::test_serialize_infinite_sym_int, test/export/test_serialize.py::TestSerialize::test_serialize_list_returns, test/export/test_serialize.py::TestSerialize::test_serialize_multiple_returns_from_node, test/export/test_serialize.py::TestSerialize::test_serialize_sym_float, test/export/test_serialize.py::TestSerialize::test_serialize_sym_int, test/export/test_serialize.py::TestSerialize::test_symint_list, test/export/test_serialize.py::TestDeserialize::test_arg_from, test/export/test_serialize.py::TestDeserialize::test_auto_functionalize, test/export/test_serialize.py::TestDeserialize::test_basic, test/export/test_serialize.py::TestDeserialize::test_cond, test/export/test_serialize.py::TestDeserialize::test_constraints, test/export/test_serialize.py::TestDeserialize::test_custom_obj, test/export/test_serialize.py::TestDeserialize::test_custom_obj_list_out, test/export/test_serialize.py::TestDeserialize::test_custom_obj_tuple_out, test/export/test_serialize.py::TestDeserialize::test_device, test/export/test_serialize.py::TestDeserialize::test_dynamic, test/export/test_serialize.py::TestDeserialize::test_export_no_inputs, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_assume_constant_result, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_autograd_function, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_class_method, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_cond_branch_class_method, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_cond_branch_nested_function, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_cond_branch_nonlocal_variables, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_cond_closed_over_variable, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_cond_operands, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_cond_predicate, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_constrain_as_size_example, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_constrain_as_value_example, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_decorator, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_dictionary, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_dynamic_shape_assert, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_dynamic_shape_constructor, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_dynamic_shape_if_guard, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_dynamic_shape_map, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_dynamic_shape_slicing, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_dynamic_shape_view, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_fn_with_kwargs, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_list_contains, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_list_unpack, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_nested_function, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_null_context_manager, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_pytree_flatten, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_scalar_output, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_specialized_attribute, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_static_for_loop, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_static_if, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_tensor_setattr, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_type_reflection_method, test/export/test_serialize.py::TestDeserialize::test_exportdb_supported_case_user_input_mutation, test/export/test_serialize.py::TestDeserialize::test_get_attr, test/export/test_serialize.py::TestDeserialize::test_get_attr_list, test/export/test_serialize.py::TestDeserialize::test_hoo_symint_input, test/export/test_serialize.py::TestDeserialize::test_list_of_optional_tensors, test/export/test_serialize.py::TestDeserialize::test_map, test/export/test_serialize.py::TestDeserialize::test_module, test/export/test_serialize.py::TestDeserialize::test_module_meta, test/export/test_serialize.py::TestDeserialize::test_multi_return, test/export/test_serialize.py::TestDeserialize::test_multiple_getitem, test/export/test_serialize.py::TestDeserialize::test_none_input, test/export/test_serialize.py::TestDeserialize::test_optional_tuple, test/export/test_serialize.py::TestDeserialize::test_positional_argument_with_default_value, test/export/test_serialize.py::TestDeserialize::test_pytree_namedtuple, test/export/test_serialize.py::TestDeserialize::test_serialize_float8, test/export/test_serialize.py::TestDeserialize::test_shape, test/export/test_serialize.py::TestDeserialize::test_sym_bool, test/export/test_serialize.py::TestDeserialize::test_sym_bool_dynamic_shapes, test/export/test_serialize.py::TestDeserialize::test_sym_bool_torch_check_equal, test/export/test_serialize.py::TestDeserialize::test_sym_float, test/export/test_serialize.py::TestDeserialize::test_sym_int_torch_check_equal, test/export/test_serialize.py::TestDeserialize::test_sym_ite, test/export/test_serialize.py::TestDeserialize::test_tensor_tensor_list, test/export/test_serialize.py::TestDeserialize::test_unbacked_bindings_serialize, test/export/test_serialize.py::TestSchemaVersioning::test_error, test/export/test_serialize.py::TestSaveLoad::test_save_buffer, test/export/test_serialize.py::TestSaveLoad::test_save_constants, test/export/test_serialize.py::TestSaveLoad::test_save_extra, test/export/test_serialize.py::TestSaveLoad::test_save_file, test/export/test_serialize.py::TestSaveLoad::test_save_path, test/export/test_serialize.py::TestSaveLoad::test_version_error, test/export/test_serialize.py::TestSerializeCustomClass::test_custom_class, test/export/test_serialize.py::TestSerializeCustomClass::test_custom_class_containing_fake_tensor, test/export/test_serialize.py::TestSerializeCustomClass::test_custom_class_input_to_function, test/export/test_serialize.py::TestSerializeCustomClass::test_custom_tag_metadata_copy, test/export/test_serialize.py::TestSerializeCustomClass::test_custom_tag_metadata_decomp, test/export/test_serialize.py::TestSerializeCustomClass::test_custom_tag_metadata_serialization
2025-07-17T07:51:41.0068060Z 
2025-07-17T07:51:41.0068850Z Running test_out_dtype_op 1/1 ... [2025-07-17 07:51:41.006575]
2025-07-17T07:51:41.0069600Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:51:41.0071100Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_out_dtype_op.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:51:41.006902]
2025-07-17T07:51:44.4381490Z 
2025-07-17T07:51:44.4381980Z test_out_dtype_op 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_out_dtype_op_1.1_e3ab6110c77b0bbf_.log
2025-07-17T07:51:44.4386020Z Running 12 items in this shard: test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_dynamo, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_inductor_decomp, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_inductor_decomp_trace, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_int_mm_default_trace, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_make_fx, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_mm_numerical, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_mul_scalar_numerical, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_no_autograd, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_non_functional, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_non_op_overload, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_op_functional, test/test_out_dtype_op.py::TestOutDtypeOp::test_out_dtype_wrong_output
2025-07-17T07:51:44.4388300Z 
2025-07-17T07:51:46.5740210Z Running export/test_hop 1/1 ... [2025-07-17 07:51:46.573868]
2025-07-17T07:51:46.5740510Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:51:46.5744630Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'export/test_hop.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:51:46.574367]
2025-07-17T07:51:55.3911480Z 
2025-07-17T07:51:55.3911960Z export/test_hop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_hop_1.1_9d6cfd9f0c7a9876_.log
2025-07-17T07:51:55.3922380Z Running 36 items in this shard: test/export/test_hop.py::TestHOPCPU::test_aot_export_auto_functionalize_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_aot_export_cond_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_aot_export_flex_attention_backward_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_aot_export_flex_attention_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_aot_export_invoke_quant_packed_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_aot_export_invoke_quant_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_aot_export_invoke_subgraph_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_aot_export_scan_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_aot_export_while_loop_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_pre_dispatch_export_auto_functionalize_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_pre_dispatch_export_cond_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_pre_dispatch_export_flex_attention_backward_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_pre_dispatch_export_flex_attention_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_pre_dispatch_export_invoke_quant_packed_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_pre_dispatch_export_invoke_quant_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_pre_dispatch_export_invoke_subgraph_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_pre_dispatch_export_scan_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_pre_dispatch_export_while_loop_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_retrace_export_auto_functionalize_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_retrace_export_cond_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_retrace_export_flex_attention_backward_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_retrace_export_flex_attention_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_retrace_export_invoke_quant_packed_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_retrace_export_invoke_quant_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_retrace_export_invoke_subgraph_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_retrace_export_scan_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_retrace_export_while_loop_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_serialize_export_auto_functionalize_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_serialize_export_cond_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_serialize_export_flex_attention_backward_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_serialize_export_flex_attention_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_serialize_export_invoke_quant_packed_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_serialize_export_invoke_quant_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_serialize_export_invoke_subgraph_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_serialize_export_scan_simple_cpu_float32, test/export/test_hop.py::TestHOPCPU::test_serialize_export_while_loop_simple_cpu_float32
2025-07-17T07:51:55.3931160Z 
2025-07-17T07:51:57.2756830Z 
2025-07-17T07:51:57.2757570Z inductor/test_auto_functionalize 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_auto_functionalize_1.1_9d6efdf2c47cfca8_.log
2025-07-17T07:51:57.2769620Z Running 39 items in this shard: test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_alias, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_alias2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_alias2_dynamic, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_alias_id_input_to_custom_op, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_alias_id_output, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_can_with_default, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_can_with_none_return, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_extra1, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_extra2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_extra3, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_extra4, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_extra5, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_old, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_on_view, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_optional_old, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_optional_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_self_as_mutate_arg, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_tensorlist, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_with_returns_old, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_with_returns_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_can_auto_functionalize, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_dynamic2_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_dynamic3_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_dynamic_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_graph_input_is_view, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_inference_mode1_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_inference_mode2_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_inference_mode3_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_inference_mode4_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_inference_mode_view, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_recompile, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_scheduling_with_multiple_mutates, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_slice, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_slice_dynamic, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_split, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_split_dynamic, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_try_use_slice, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_unbacked_auto_functionalize_op
2025-07-17T07:51:57.2779990Z 
2025-07-17T07:51:57.6187520Z Running dynamo/test_higher_order_ops 1/1 ... [2025-07-17 07:51:57.618539]
2025-07-17T07:51:57.6187900Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:51:57.6191210Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_higher_order_ops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:51:57.619027]
2025-07-17T07:51:59.5334580Z Running inductor/test_efficient_conv_bn_eval 1/1 ... [2025-07-17 07:51:59.533221]
2025-07-17T07:51:59.5334970Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:51:59.5337660Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_efficient_conv_bn_eval.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:51:59.533586]
2025-07-17T07:52:02.4897270Z 
2025-07-17T07:52:02.4898100Z inductor/test_efficient_conv_bn_eval 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_efficient_conv_bn_eval_1.1_9bef30450d15b6ee_.log
2025-07-17T07:52:02.4898820Z Running 0 items in this shard:
2025-07-17T07:52:02.4898960Z 
2025-07-17T07:52:04.7835230Z Running test_model_exports_to_core_aten 1/1 ... [2025-07-17 07:52:04.783310]
2025-07-17T07:52:04.7836130Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:52:04.7837290Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_model_exports_to_core_aten.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:52:04.783603]
2025-07-17T07:52:07.0157790Z 
2025-07-17T07:52:07.0159640Z test_model_exports_to_core_aten 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_model_exports_to_core_aten_1.1_f8a2f251fb8b283f_.log
2025-07-17T07:52:07.0160630Z Running 1 items in this shard: test/test_model_exports_to_core_aten.py::TestQuantizePT2EModels::test_vit_aten_export
2025-07-17T07:52:07.0160960Z 
2025-07-17T07:52:09.2162180Z Running test_mkldnn 1/1 ... [2025-07-17 07:52:09.216036]
2025-07-17T07:52:09.2162900Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:52:09.2164740Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_mkldnn.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:52:09.216356]
2025-07-17T07:52:11.7226470Z 
2025-07-17T07:52:11.7228580Z test_mkldnn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_1.1_2ea25946edcb5540_.log
2025-07-17T07:52:11.7245370Z Running 90 items in this shard: test/test_mkldnn.py::TestMkldnnCPU::test_0_dimension_tensor_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_adaptive_avg_pool2d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_adaptive_avg_pool2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_add_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_autograd_from_mkldnn_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_autograd_to_mkldnn_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool2d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool2d_stride_none_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool3d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_avg_pool3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_batch_norm_2d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_batch_norm_2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_batch_norm_3d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_batch_norm_3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_clone_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv1d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv1d_functional_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv2d_legacy_jit_model_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_1d_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_1d_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_2d_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_2d_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_3d_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_deconv_3d_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_nhwc_fp32_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_nhwc_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_nhwc_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose1d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose_nhwc_fp32_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose_nhwc_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_conv_transpose_nhwc_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_conversion_byte_char_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_conversion_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_copy_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_default_use_parent_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_detach_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_empty_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_gelu_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_gelu_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_generic_precision_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_invalid_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_is_mkldnn_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_is_mkldnn_jit_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_legacy_new_failure_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_linear_backward_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_linear_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_linear_lowp_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_linear_lowp_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_linear_non_contiguous_weight_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_lstm_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_matmul_lower_precision_cpu_bfloat16, test/test_mkldnn.py::TestMkldnnCPU::test_matmul_lower_precision_cpu_float16, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool2d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool2d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool2d_stride_none_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool3d_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool3d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_max_pool_unsupported_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mkldnn_conv_shapecheck_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mkldnn_error_on_zero_stride_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mkldnn_scaled_mm_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mkldnn_setflags_nowarn_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mlkdnn_get_set_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_mul_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_prelu_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_prelu_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_relu__cpu, test/test_mkldnn.py::TestMkldnnCPU::test_relu_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_relu_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_relu_inplace_bf16_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_repr_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_reshape_backward_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_reshape_blocked_format_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_reshape_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_resnet18_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_resnext50_32x4d_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_set_data_tensorimpl_type_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_sigmoid_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_softmax_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_tanh_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_transpose_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_transpose_invalid_dime_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_unsupported_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_view_cpu, test/test_mkldnn.py::TestMkldnnCPU::test_zero__cpu
2025-07-17T07:52:11.7259930Z 
2025-07-17T07:52:13.9249350Z Running torch_np/numpy_tests/lib/test_function_base 1/1 ... [2025-07-17 07:52:13.924748]
2025-07-17T07:52:13.9249730Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:52:13.9252360Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_function_base.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:52:13.925129]
2025-07-17T07:52:17.5753330Z 
2025-07-17T07:52:17.5754030Z torch_np/numpy_tests/lib/test_function_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_function_base_1.1_11555894354e774e_.log
2025-07-17T07:52:17.5888030Z Running 505 items in this shard: test/torch_np/numpy_tests/lib/test_function_base.py::TestRot90::test_axes, test/torch_np/numpy_tests/lib/test_function_base.py::TestRot90::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestRot90::test_rotation_axes, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_3d_swap_axis0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_3d_swap_axis1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_3d_swap_axis2, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_4d, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_axes, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_basic_lr, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_basic_ud, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_default_axis, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_multiple_axes, test/torch_np/numpy_tests/lib/test_function_base.py::TestAny::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestAny::test_nd, test/torch_np/numpy_tests/lib/test_function_base.py::TestAll::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestAll::test_nd, test/torch_np/numpy_tests/lib/test_function_base.py::TestCopy::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestCopy::test_order, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_average_class_without_dtype, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_basic_keepdims_x0_axis0_expected_avg0_weights0_expected_wavg0_expected_wsum0, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_basic_keepdims_x1_axis_0_expected_avg1_weights1_expected_wavg1_expected_wsum1, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_returned, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_upcasting, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_weights, test/torch_np/numpy_tests/lib/test_function_base.py::TestSelect::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestSelect::test_broadcasting, test/torch_np/numpy_tests/lib/test_function_base.py::TestSelect::test_deprecated_empty, test/torch_np/numpy_tests/lib/test_function_base.py::TestSelect::test_many_arguments, test/torch_np/numpy_tests/lib/test_function_base.py::TestSelect::test_non_bool_deprecation, test/torch_np/numpy_tests/lib/test_function_base.py::TestSelect::test_return_dtype, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_0d, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_index_array_copied, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_index_floats, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_index_out_of_bounds_idx_-4, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_index_out_of_bounds_idx_4, test/torch_np/numpy_tests/lib/test_function_base.py::TestInsert::test_multidim, test/torch_np/numpy_tests/lib/test_function_base.py::TestAmax::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestAmin::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestPtp::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestCumsum::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestProd::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestCumprod::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestDiff::test_append, test/torch_np/numpy_tests/lib/test_function_base.py::TestDiff::test_axis, 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test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype5_expected_dtype5_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype5_expected_dtype5_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype5_expected_dtype5_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype6_expected_dtype6_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype6_expected_dtype6_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype6_expected_dtype6_method_hazen_expected_27_5, 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test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_weibull_expected_26, 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test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_l, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_B, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_b, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_d, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_e, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_f, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_h, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_i, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_l, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nan_behavior, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nan_q, 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test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_b, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_h, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_i, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_l, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_scalar_nan, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_array_like, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_axis_keyword, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_basic_2, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_empty, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_extended_axis, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_extended_axis_invalid, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_2, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis0, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis2, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis3, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis4, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_nan_behavior, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_nan_behavior_2, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_nan_behavior_3, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_out, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_out_nan, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_overwrite_keyword, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_complex, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_B_type_out_F, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_H_type_out_F, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_b_type_out_F, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_g_type_out_G, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_h_type_out_F, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_l_type_out_D
2025-07-17T07:52:17.6019710Z 
2025-07-17T07:52:19.7970730Z Running lazy/test_functionalization 1/1 ... [2025-07-17 07:52:19.796904]
2025-07-17T07:52:19.7971090Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:52:19.7973740Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'lazy/test_functionalization.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:52:19.797239]
2025-07-17T07:52:22.2305810Z 
2025-07-17T07:52:22.2306490Z lazy/test_functionalization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_functionalization_1.1_b8219679ccd2f0fc_.log
2025-07-17T07:52:22.2307620Z Running 2 items in this shard: test/lazy/test_functionalization.py::LazyFuncionalizationTest::test_data_assign, test/lazy/test_functionalization.py::LazyFuncionalizationTest::test_lazy_init_with_view
2025-07-17T07:52:22.2308180Z 
2025-07-17T07:52:24.4526150Z Running test_jit 1/1 ... [2025-07-17 07:52:24.452487]
2025-07-17T07:52:24.4526460Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:52:24.4530400Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_jit.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:52:24.452859]
2025-07-17T07:52:25.3550300Z 
2025-07-17T07:52:25.3550860Z dynamo/test_higher_order_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_higher_order_ops_1.1_b7649f645945945a_.log
2025-07-17T07:52:25.3605770Z Running 217 items in this shard: test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_access_module_attr, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_allow_python_side_effects_utility, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_capture_constants, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_capture_global_num, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_capture_global_num_adds_guard, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_capture_input_num, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_capture_numpy_number, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_capture_tracked, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_capture_tracked_nested, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_capture_untracked_global, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_capture_untracked_global_nested, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_capture_untracked_nonlocal, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_capture_value_created_in_subgraph, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_concat_unbacked_shape_tensor, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_cond_branches_no_arguments, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_cond_branches_no_arguments_no_closure, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_cond_free_variable_in_both_branches, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_cond_graph_break_in_one_branch, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_cond_pytree_operands, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_cond_pytree_operands_with_non_tensor_leaves, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_cond_side_effect_in_one_branches, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_cond_source_fn_stack, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_cond_subgraph_name_is_valid, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_cond_with_constant_pred, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_cond_with_empty_operands, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_dynamic_shapes_over_vmap_batch_size, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_enum_arg, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_error_message_sane, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_fallback_on_graph_break_complicated, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_fallback_on_graph_break_simple, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_fallback_on_python_primitives_output, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_flat_list_output, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_fn_with_kwargs_in_torch_ops, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_freevars_as_inputs_to_wrap, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_grad_source_fn_stack, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_hints_wrapper, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_hints_wrapper_incorrect_type, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_hints_wrapper_no_hints, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_hints_wrapper_pytree_inputs, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_hooks, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_hopify_generic_wrap, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_inlined_functions, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_internal_nonlocal, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_lift_tensor_constant, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_lift_tensors_with_compound_expressions, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_lift_tensors_with_shared_symbols, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_make_closure, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_map_example_value_metadata_consistent_with_eager, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_map_graph_break, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_map_kwargs, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_map_lowers_to_graph, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_map_multi_return, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_map_pytree_return, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_map_side_effect, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_map_source_fn_stack, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_map_subgraph_name_is_valid, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_map_symint_input, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_modules, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_nested_tuple_output, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_nested_wrap, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_no_freevars, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_output_with_dict, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_register_mode, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_register_subclass, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_return_captured_var, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_return_captured_var_used_multiple_times, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_return_captured_vars, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_same_freevar_twice, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_del_existing_attr_global_module, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_del_existing_attr_global_obj, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_del_existing_attr_nonlocal_module, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_del_existing_attr_nonlocal_obj, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_in_body, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_local_list_append_no_graph_break, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_mutate_global_list, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_mutate_global_num, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_mutate_global_num_builtin, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_mutate_global_tensor, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_mutate_global_tensor_builtin, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_mutate_nonlocal_num, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_mutate_nonlocal_num_builtin, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_mutate_nonlocal_tensor, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_mutate_nonlocal_tensor_builtin, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_nested_nonlocal_list_append_graph_break, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_nonlocal_list_append_graph_break, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_set_existing_attr_global_module, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_set_existing_attr_global_obj, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_set_existing_attr_nonlocal_module, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_set_existing_attr_nonlocal_obj, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_set_new_attr_global_module, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_set_new_attr_global_obj, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_set_new_attr_nonlocal_module, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_side_effect_set_new_attr_nonlocal_obj, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_symint_in_slice, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_symint_input, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_tensor_and_unbacked_symbol_closure, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_tensor_to_list_closure, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_tensor_with_unbacked_shape_closure, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_unbacked_symbol_closure, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_vmap_multiply_scalar, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_vmap_source_fn_stack, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_all_kwarg, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_allow_local_assign_in_body_fn, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_kwarg, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_kwarg_default, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_kwarg_default_else_branch, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_kwarg_default_if_branch, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_kwarg_int, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_kwarg_only, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_kwarg_recompile, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_pytree_args_nested, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_pytree_args_not_const_symint_tensor, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_pytree_args_with_symint_constant, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_pytree_kwargs, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_source_fn_stack, test/dynamo/test_higher_order_ops.py::HigherOrderOpTests::test_wrap_subgraph_name_is_valid, test/dynamo/test_higher_order_ops.py::HigherOrderOpVmapGuardTests::test_dual_level_guard, test/dynamo/test_higher_order_ops.py::HigherOrderOpVmapGuardTests::test_emit_functorch_guard_if_active, test/dynamo/test_higher_order_ops.py::HigherOrderOpVmapGuardTests::test_grad_guard_fail, test/dynamo/test_higher_order_ops.py::HigherOrderOpVmapGuardTests::test_jvp_guard_fail, test/dynamo/test_higher_order_ops.py::HigherOrderOpVmapGuardTests::test_linearize_recompiles, test/dynamo/test_higher_order_ops.py::HigherOrderOpVmapGuardTests::test_vmap_grad_guard_ok, test/dynamo/test_higher_order_ops.py::HigherOrderOpVmapGuardTests::test_vmap_grad_vmap_guard_fail, test/dynamo/test_higher_order_ops.py::HigherOrderOpVmapGuardTests::test_vmap_guard_fail, test/dynamo/test_higher_order_ops.py::HigherOrderOpVmapGuardTests::test_vmap_guard_fail_different_state, test/dynamo/test_higher_order_ops.py::HigherOrderOpVmapGuardTests::test_vmap_guard_ok, test/dynamo/test_higher_order_ops.py::HigherOrderOpVmapGuardTests::test_vmap_recompile_different_states, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_functional_call, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_functional_call_disable_inline_nn_module, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_functional_call_sequential_params_and_buffers, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_call_compiled_backward_fn, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_call_torch_compile_fn, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_capture_tensor, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_closure_scalar, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_fn_with_kwargs, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_freevar_python_scalar, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_freevar_tensor, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_has_aux, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_non_tensor_input, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_over_grad, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_pytree, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_recompile, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_two_tensor_all_grad_has_aux, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_two_tensor_has_aux, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_with_graph_break, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_grad_with_side_effect, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_hessian, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_hessian_argnums, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jacfwd, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jacfwd_has_aux, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jacfwd_randomness, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jacfwd_two_tensors_argnums, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jacrev, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jacrev_has_aux, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jacrev_two_tensors_argnums, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jvp_call_torch_compile_fn, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jvp_freevar_python_scalar, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jvp_freevar_tensor, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jvp_has_aux, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jvp_jvp, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jvp_simple, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jvp_two_tensors_disable_enable_disable_grad, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jvp_two_tensors_disable_grad, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_jvp_two_tensors_has_aux, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_linearize_jvp_fn, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vjp, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vjp_call_compiled_backward_fn, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vjp_has_aux, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vjp_multiple_outputs, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vjp_multiple_outputs_python_struct, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_call_compiled_backward_fn, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_call_torch_compile_fn, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_free_const, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_free_tensor, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_get_wrapped, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_kwargs, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_multiple_invocation_in_dims, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_multiple_invocation_out_dims, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_multiple_outputs, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_multiple_outputs_diff_dims, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_multiple_outputs_out_dims_tuple, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_new_tensor_implicit_via_op, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_new_tensor_in_body, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_new_tensor_unused_in_body, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_out_dims_None, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_over_vmap_captured, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_over_vmap_two_inputs, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_previous_illegal_op_no_graph_break, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_pytree_inputs, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_recompile, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_recompile_different_config, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_recompile_same_config, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_recompile_with_randomness, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_side_effects, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_side_effects_append_input, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_two_inputs, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_two_inputs_tuple_in_dims, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_with_conditional_graph_break, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_with_graph_break, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_with_graph_break_2, test/dynamo/test_higher_order_ops.py::FuncTorchHigherOrderOpTests::test_vmap_with_graph_break_lambda, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_cond_with_invalid_kwargs, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_cond_with_kwargs, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_cond_with_mismatched_output, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_dropout, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_dropout_inductor, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_fallback, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_flop_counter_for_cond, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_flop_counter_for_cond_unbalanced_branches, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_flop_counter_for_nested_cond, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_function, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_function_with_kwargs, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_module, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_non_aliasing_util, test/dynamo/test_higher_order_ops.py::ActivationCheckpointingTests::test_override_fallthrough_dispatch_key
2025-07-17T07:52:25.3659530Z 
2025-07-17T07:52:27.5403950Z Running dynamo/test_aot_autograd_cache 1/1 ... [2025-07-17 07:52:27.540157]
2025-07-17T07:52:27.5404330Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:52:27.5406780Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_aot_autograd_cache.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:52:27.540515]
2025-07-17T07:53:03.5257930Z 
2025-07-17T07:53:03.5258810Z dynamo/test_aot_autograd_cache 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_aot_autograd_cache_1.1_dfb3d212d1c74de7_.log
2025-07-17T07:53:03.5292790Z Running 94 items in this shard: test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_aot_runtime_trace_joint, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_autograd_function, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_autograd_guard_single_entry_device_mps_bfloat16, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_autograd_guard_single_entry_device_mps_float16, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_autograd_inductor_guards_device_mps_bfloat16_requires_grad_False, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_autograd_inductor_guards_device_mps_bfloat16_requires_grad_True, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_autograd_inductor_guards_device_mps_float16_requires_grad_False, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_autograd_inductor_guards_device_mps_float16_requires_grad_True, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_autograd_lazy_backward, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_autograd_no_dynamo_trace_backward, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_basic, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_cache_hot_load_device_cpu_bfloat16_dynamic_False, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_cache_hot_load_device_cpu_bfloat16_dynamic_True, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_cache_hot_load_device_cpu_float32_dynamic_False, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_cache_hot_load_device_cpu_float32_dynamic_True, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_cache_hot_load_device_mps_bfloat16_dynamic_False, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_cache_hot_load_device_mps_bfloat16_dynamic_True, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_cache_hot_load_device_mps_float32_dynamic_False, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_cache_hot_load_device_mps_float32_dynamic_True, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_cache_lazy_backward_for_compiled_autograd, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_clear_fx_graph_cache, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_compiled_autograd_bypass, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_constant_tensor_device_guards, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_custom_autograd_function, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_custom_autograd_function_miss, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_custom_autograd_function_with_custom_triton_kernel, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_dynamic_shapes_different_sizes, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_fx_graph_cache_off, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_inference_graph_cache_hit_with_compiled_autograd_enabled, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_invoke_subgraph, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_multi_graph_specialization, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_multiple_compile_triton_kernels, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_nn_module_with_params_global_constant, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_non_bundled_to_bundled_config_change, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_saved_tensors_hooks_autograd_cache, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_saved_tensors_hooks_autograd_cache_symbolic, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_symbol_specialization, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_unsafe_mark_cacheable_fn_select_allow_in_graph, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_unsafe_mark_cacheable_fn_select_tag_activation_checkpoint, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheTests::test_view_replay_bypass, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_aot_runtime_trace_joint, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_autograd_function, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_autograd_guard_single_entry_device_mps_bfloat16, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_autograd_guard_single_entry_device_mps_float16, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_autograd_inductor_guards_device_mps_bfloat16_requires_grad_False, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_autograd_inductor_guards_device_mps_bfloat16_requires_grad_True, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_autograd_inductor_guards_device_mps_float16_requires_grad_False, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_autograd_inductor_guards_device_mps_float16_requires_grad_True, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_autograd_lazy_backward, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_autograd_no_dynamo_trace_backward, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_basic, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_cache_hot_load_device_cpu_bfloat16_dynamic_False, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_cache_hot_load_device_cpu_bfloat16_dynamic_True, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_cache_hot_load_device_cpu_float32_dynamic_False, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_cache_hot_load_device_cpu_float32_dynamic_True, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_cache_hot_load_device_mps_bfloat16_dynamic_False, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_cache_hot_load_device_mps_bfloat16_dynamic_True, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_cache_hot_load_device_mps_float32_dynamic_False, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_cache_hot_load_device_mps_float32_dynamic_True, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_cache_lazy_backward_for_compiled_autograd, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_clear_fx_graph_cache, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_compiled_autograd_bypass, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_constant_tensor_device_guards, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_custom_autograd_function, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_custom_autograd_function_miss, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_custom_autograd_function_with_custom_triton_kernel, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_dynamic_shapes_different_sizes, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_fx_graph_cache_off, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_inference_graph_cache_hit_with_compiled_autograd_enabled, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_invoke_subgraph, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_multi_graph_specialization, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_multiple_compile_triton_kernels, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_nn_module_with_params_global_constant, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_non_bundled_to_bundled_config_change, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_saved_tensors_hooks_autograd_cache, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_saved_tensors_hooks_autograd_cache_symbolic, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_symbol_specialization, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_unsafe_mark_cacheable_fn_select_allow_in_graph, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_unsafe_mark_cacheable_fn_select_tag_activation_checkpoint, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCacheBundledTests::test_view_replay_bypass, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_basic_hash_key, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_different_configs, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_different_global_configs, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_different_graphs, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_different_inputs, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_freezing, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_identical_graphs_and_configs, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_incompatible_function, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_nn_module_with_params, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_normal_torch_function, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_private_builtin, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_private_namespace, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_safe_torchfunction, test/dynamo/test_aot_autograd_cache.py::AOTAutogradCachePicklerTests::test_sanitize_gm_for_cache
2025-07-17T07:53:03.5322740Z 
2025-07-17T07:53:05.7875850Z Running dynamo/test_einops 1/1 ... [2025-07-17 07:53:05.787315]
2025-07-17T07:53:05.7877910Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:53:05.7878910Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_einops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:53:05.787724]
2025-07-17T07:53:08.0617800Z 
2025-07-17T07:53:08.0618970Z dynamo/test_einops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_einops_1.1_239f5fa75925d756_.log
2025-07-17T07:53:08.0620310Z Running 3 items in this shard: test/dynamo/test_einops.py::TestEinops::test_functions_version_none, test/dynamo/test_einops.py::TestEinops::test_layers_version_none, test/dynamo/test_einops.py::TestEinops::test_no_recompile_on_lazy_state_version_none
2025-07-17T07:53:08.0621040Z 
2025-07-17T07:53:10.3249240Z Running dynamo/test_compiler_bisector 1/1 ... [2025-07-17 07:53:10.324669]
2025-07-17T07:53:10.3250080Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:53:10.3251820Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'dynamo/test_compiler_bisector.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:53:10.325008]
2025-07-17T07:53:13.3059540Z 
2025-07-17T07:53:13.3060250Z dynamo/test_compiler_bisector 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_compiler_bisector_1.1_7ac88f191e0fbe08_.log
2025-07-17T07:53:13.3063240Z Running 7 items in this shard: test/dynamo/test_compiler_bisector.py::TestCompilerBisector::test_bad_decomp, test/dynamo/test_compiler_bisector.py::TestCompilerBisector::test_bad_lowering, test/dynamo/test_compiler_bisector.py::TestCompilerBisector::test_crossref, test/dynamo/test_compiler_bisector.py::TestCompilerBisector::test_eager_backend, test/dynamo/test_compiler_bisector.py::TestCompilerBisector::test_emulate_precision_casts, test/dynamo/test_compiler_bisector.py::TestCompilerBisector::test_joint_graph, test/dynamo/test_compiler_bisector.py::TestCompilerBisector::test_rng
2025-07-17T07:53:13.3065620Z 
2025-07-17T07:53:15.5671270Z Running test_modules 1/1 ... [2025-07-17 07:53:15.566915]
2025-07-17T07:53:15.5671950Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:53:15.5677790Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_modules.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:53:15.567600]
2025-07-17T07:53:16.3598610Z 
2025-07-17T07:53:16.3599740Z test_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_1.1_d50d95d867192a1f_.log
2025-07-17T07:53:16.4010950Z Running 2458 items in this shard: test/test_jit.py::TestTracer::test_call_traced_fn_from_traced_module, test/test_jit.py::TestTracer::test_call_traced_module_from_traced_module, test/test_jit.py::TestTracer::test_canonicalize_tensor_iterator, test/test_jit.py::TestTracer::test_constant, test/test_jit.py::TestTracer::test_conv, test/test_jit.py::TestTracer::test_export_no_reorder, test/test_jit.py::TestTracer::test_force_outplace_check_fill, test/test_jit.py::TestTracer::test_force_outplace_check_zero, test/test_jit.py::TestTracer::test_ge, test/test_jit.py::TestTracer::test_ge_cuda, test/test_jit.py::TestTracer::test_ge_optimized, test/test_jit.py::TestTracer::test_ge_unoptimized, test/test_jit.py::TestTracer::test_index_put, test/test_jit.py::TestTracer::test_index_put_trace_with_view, test/test_jit.py::TestTracer::test_index_put_trace_without_view, test/test_jit.py::TestTracer::test_inplace_check, test/test_jit.py::TestTracer::test_inplace_copy, test/test_jit.py::TestTracer::test_inplace_copy_force_outplace, test/test_jit.py::TestTracer::test_inplace_flags, test/test_jit.py::TestTracer::test_inplace_transplant, test/test_jit.py::TestTracer::test_inplace_warn, test/test_jit.py::TestTracer::test_input_dict_checkTrace_mut, test/test_jit.py::TestTracer::test_input_dict_empty, test/test_jit.py::TestTracer::test_input_dict_empty_list, test/test_jit.py::TestTracer::test_input_dict_insertion_order, test/test_jit.py::TestTracer::test_input_dict_of_dicts, test/test_jit.py::TestTracer::test_input_dict_of_lists, test/test_jit.py::TestTracer::test_input_dict_recursive, test/test_jit.py::TestTracer::test_input_dict_remembers_keys, test/test_jit.py::TestTracer::test_input_dict_unify, test/test_jit.py::TestTracer::test_input_flatten, test/test_jit.py::TestTracer::test_input_list_mixed_type, test/test_jit.py::TestTracer::test_input_list_of_tuples, test/test_jit.py::TestTracer::test_input_list_toplevel_flatten, test/test_jit.py::TestTracer::test_input_list_toplevel_flatten_direct, test/test_jit.py::TestTracer::test_input_tuple_of_dicts, test/test_jit.py::TestTracer::test_interpolate_trace, test/test_jit.py::TestTracer::test_large_nbr_kernel_args, test/test_jit.py::TestTracer::test_lhs_index_fails, test/test_jit.py::TestTracer::test_lhs_index_trivial, test/test_jit.py::TestTracer::test_max_pool, test/test_jit.py::TestTracer::test_nested_inplace, test/test_jit.py::TestTracer::test_non_tensor_tracing, test/test_jit.py::TestTracer::test_output_unflatten, test/test_jit.py::TestTracer::test_python_function, test/test_jit.py::TestTracer::test_python_function_tup, test/test_jit.py::TestTracer::test_repeated_input, test/test_jit.py::TestTracer::test_repeated_output, test/test_jit.py::TestTracer::test_shared_param, test/test_jit.py::TestTracer::test_simple, test/test_jit.py::TestTracer::test_tensor_with_grad_as_constant, test/test_jit.py::TestTracer::test_trace_aliased_parameter, test/test_jit.py::TestTracer::test_trace_annotation, test/test_jit.py::TestTracer::test_trace_arange, test/test_jit.py::TestTracer::test_trace_arange_with_grad, test/test_jit.py::TestTracer::test_trace_autograd_function, test/test_jit.py::TestTracer::test_trace_casts, test/test_jit.py::TestTracer::test_trace_checker_control_flow, test/test_jit.py::TestTracer::test_trace_checker_dot_data, test/test_jit.py::TestTracer::test_trace_checker_dropout_notrain, test/test_jit.py::TestTracer::test_trace_checker_dropout_train, test/test_jit.py::TestTracer::test_trace_checker_inplace_on_view, test/test_jit.py::TestTracer::test_trace_checker_memoization, test/test_jit.py::TestTracer::test_trace_checker_slice_lhs, test/test_jit.py::TestTracer::test_trace_checking_with_deprecated_name, test/test_jit.py::TestTracer::test_trace_checking_with_global_name, test/test_jit.py::TestTracer::test_trace_contiguous, test/test_jit.py::TestTracer::test_trace_contiguous_short_circuit, test/test_jit.py::TestTracer::test_trace_detach, test/test_jit.py::TestTracer::test_trace_detach_inplace, test/test_jit.py::TestTracer::test_trace_detach_inplace_redispatch, test/test_jit.py::TestTracer::test_trace_detach_redispatch, test/test_jit.py::TestTracer::test_trace_dict_input, test/test_jit.py::TestTracer::test_trace_dict_output, test/test_jit.py::TestTracer::test_trace_export_fns, test/test_jit.py::TestTracer::test_trace_export_fns_recursive, test/test_jit.py::TestTracer::test_trace_fork_join_and_module, test/test_jit.py::TestTracer::test_trace_full_dynamic_shape, test/test_jit.py::TestTracer::test_trace_func_argument_names_captured, test/test_jit.py::TestTracer::test_trace_index, test/test_jit.py::TestTracer::test_trace_index_constant, test/test_jit.py::TestTracer::test_trace_indexed_assignment, test/test_jit.py::TestTracer::test_trace_inline_shape, test/test_jit.py::TestTracer::test_trace_inverse, test/test_jit.py::TestTracer::test_trace_invert_module_hierarchy, test/test_jit.py::TestTracer::test_trace_legacy_ctor, test/test_jit.py::TestTracer::test_trace_module_argument_names_captured, test/test_jit.py::TestTracer::test_trace_modulelist, test/test_jit.py::TestTracer::test_trace_multi_output_function, test/test_jit.py::TestTracer::test_trace_namedtuple, test/test_jit.py::TestTracer::test_trace_nested_datatypes, test/test_jit.py::TestTracer::test_trace_nested_fn, test/test_jit.py::TestTracer::test_trace_no_duplicated_lifted_input_output, test/test_jit.py::TestTracer::test_trace_numel, test/test_jit.py::TestTracer::test_trace_optioanl_dtype, test/test_jit.py::TestTracer::test_trace_optional, test/test_jit.py::TestTracer::test_trace_out_operator_with_two_output, test/test_jit.py::TestTracer::test_trace_partial_func_argument_names_captured, test/test_jit.py::TestTracer::test_trace_random, test/test_jit.py::TestTracer::test_trace_records_names, test/test_jit.py::TestTracer::test_trace_save, test/test_jit.py::TestTracer::test_trace_save_load_copy, test/test_jit.py::TestTracer::test_trace_single_tuple, test/test_jit.py::TestTracer::test_trace_size, test/test_jit.py::TestTracer::test_trace_size_with_grad, test/test_jit.py::TestTracer::test_trace_skip_none_submodule, test/test_jit.py::TestTracer::test_trace_slice, test/test_jit.py::TestTracer::test_trace_slice_expr_complete_type, test/test_jit.py::TestTracer::test_trace_slice_full_dim, test/test_jit.py::TestTracer::test_trace_slice_setitem_dynamic_shape, test/test_jit.py::TestTracer::test_trace_slice_with_grad, test/test_jit.py::TestTracer::test_trace_tensor_factory, test/test_jit.py::TestTracer::test_trace_topk, test/test_jit.py::TestTracer::test_trace_tuple, test/test_jit.py::TestTracer::test_trace_variable_instantiation, test/test_jit.py::TestTracer::test_trace_warn, test/test_jit.py::TestTracer::test_trace_with_conditional_property, test/test_jit.py::TestTracer::test_trace_with_nested_strided_tensor_output, test/test_jit.py::TestTracer::test_trace_with_nested_tensor_list_output, test/test_jit.py::TestTracer::test_trace_with_number_list_output, test/test_jit.py::TestTracer::test_trace_with_tensor_list_output, test/test_jit.py::TestTracer::test_trace_with_tuple_tensor, test/test_jit.py::TestTracer::test_traced_module_cuda, test/test_jit.py::TestTracer::test_tracing_backward_hook_error, test/test_jit.py::TestTracer::test_tracing_hooks, test/test_jit.py::TestTracer::test_tracing_multiple_methods, test/test_jit.py::TestTracer::test_type_same_device, test/test_jit.py::TestTracer::test_typeas_trace_check, test/test_jit.py::TestTracer::test_wrapped_number, test/test_jit.py::TestMixTracingScripting::test_call_script_fn_from_traced_module, test/test_jit.py::TestMixTracingScripting::test_call_script_module_from_traced_module, test/test_jit.py::TestMixTracingScripting::test_call_traced_fn_from_script_fn, test/test_jit.py::TestMixTracingScripting::test_call_traced_mod_from_script_fn, test/test_jit.py::TestMixTracingScripting::test_call_tracing_fn_from_script_module, test/test_jit.py::TestMixTracingScripting::test_call_tracing_mod_from_script_module, test/test_jit.py::TestMixTracingScripting::test_jit_trace_callfunction_return_shapes, test/test_jit.py::TestMixTracingScripting::test_script_inline_trace_multiple_args, test/test_jit.py::TestMixTracingScripting::test_trace_dict_mix_script, test/test_jit.py::TestMixTracingScripting::test_trace_hierarchy, test/test_jit.py::TestMixTracingScripting::test_trace_linear, test/test_jit.py::TestMixTracingScripting::test_trace_mixed_by_script_with_dict_output, test/test_jit.py::TestMixTracingScripting::test_trace_of_script, test/test_jit.py::TestMixTracingScripting::test_trace_parameter, test/test_jit.py::TestMixTracingScripting::test_trace_returning_dict_with_tensor_tuples, test/test_jit.py::TestMixTracingScripting::test_trace_script, test/test_jit.py::TestMixTracingScripting::test_trace_script_returning_complex_dict, test/test_jit.py::TestMixTracingScripting::test_trace_with_size, test/test_jit.py::TestMixTracingScripting::test_traced_module_contains_scripted_interface_types, test/test_jit.py::TestMixTracingScripting::test_traced_module_implements_interface, test/test_jit.py::TestMixTracingScripting::test_tracing_indexing, test/test_jit.py::TestMixTracingScripting::test_tracing_slicing, test/test_jit.py::TestRecursiveScript::test_attributes, test/test_jit.py::TestRecursiveScript::test_class_compile, test/test_jit.py::TestRecursiveScript::test_constants_with_final, test/test_jit.py::TestRecursiveScript::test_dir, test/test_jit.py::TestRecursiveScript::test_error_stack, test/test_jit.py::TestRecursiveScript::test_error_stack_annotation, test/test_jit.py::TestRecursiveScript::test_error_stack_class, test/test_jit.py::TestRecursiveScript::test_error_stack_module, test/test_jit.py::TestRecursiveScript::test_failed_function_compilation, test/test_jit.py::TestRecursiveScript::test_function_attribute_in_submodule, test/test_jit.py::TestRecursiveScript::test_ignore_class, test/test_jit.py::TestRecursiveScript::test_inferred_nonetype, test/test_jit.py::TestRecursiveScript::test_init_error, test/test_jit.py::TestRecursiveScript::test_inner_traced_module, test/test_jit.py::TestRecursiveScript::test_iterable_modules, test/test_jit.py::TestRecursiveScript::test_method_call, test/test_jit.py::TestRecursiveScript::test_module_basic, test/test_jit.py::TestRecursiveScript::test_module_function_export, test/test_jit.py::TestRecursiveScript::test_module_name, test/test_jit.py::TestRecursiveScript::test_module_repr, test/test_jit.py::TestRecursiveScript::test_optional_module, test/test_jit.py::TestRecursiveScript::test_override_instance_method_ignore, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_basic, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_cycle, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_escape_hatch, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_iterable_modules, test/test_jit.py::TestRecursiveScript::test_python_function_attribute, test/test_jit.py::TestRecursiveScript::test_repeated_error_stack, test/test_jit.py::TestRecursiveScript::test_script_after_eval, test/test_jit.py::TestRecursiveScript::test_script_basic, test/test_jit.py::TestRecursiveScript::test_script_function_attribute, test/test_jit.py::TestRecursiveScript::test_script_loaded_module, test/test_jit.py::TestTypeSharing::test_assign_python_attr, test/test_jit.py::TestTypeSharing::test_basic, test/test_jit.py::TestTypeSharing::test_builtin_function_different, test/test_jit.py::TestTypeSharing::test_builtin_function_same, test/test_jit.py::TestTypeSharing::test_constants, test/test_jit.py::TestTypeSharing::test_diff_attr_values, test/test_jit.py::TestTypeSharing::test_failed_attribute_compilation, test/test_jit.py::TestTypeSharing::test_ignored_fns, test/test_jit.py::TestTypeSharing::test_linear, test/test_jit.py::TestTypeSharing::test_loaded_modules_work, test/test_jit.py::TestTypeSharing::test_module_dict_same_type_different_name, test/test_jit.py::TestTypeSharing::test_mutate_attr_value, test/test_jit.py::TestTypeSharing::test_param_vs_attribute, test/test_jit.py::TestTypeSharing::test_python_function_attribute_different, test/test_jit.py::TestTypeSharing::test_python_function_attribute_same, test/test_jit.py::TestTypeSharing::test_same_but_different_classes, test/test_jit.py::TestTypeSharing::test_script_function_attribute_different, test/test_jit.py::TestTypeSharing::test_script_function_attribute_same, test/test_jit.py::TestTypeSharing::test_script_module_containing_traced_module, test/test_jit.py::TestTypeSharing::test_submodules, test/test_jit.py::TestTypeSharing::test_tracing_gives_different_types, test/test_jit.py::TestTypeSharing::test_type_not_shared_ignored_attributes, test/test_jit.py::TestTypeSharing::test_type_shared_ignored_attributes, test/test_jit.py::TestTypeSharing::test_type_sharing_define_in_init, test/test_jit.py::TestTypeSharing::test_type_sharing_disabled, test/test_jit.py::TestLogging::test_bump_numeric_counter, test/test_jit.py::TestLogging::test_counter_aggregation, test/test_jit.py::TestLogging::test_logging_levels_set, test/test_jit.py::TestLogging::test_time_measurement_counter, test/test_jit.py::TestLogging::test_time_measurement_counter_script, test/test_jit.py::TestLogging::test_trace_numeric_counter, test/test_jit.py::TestBackends::test_errors, test/test_jit.py::TestBackends::test_execution, test/test_jit.py::TestBackends::test_save_load, test/test_jit.py::TestBackendsWithCompiler::test_errors, test/test_jit.py::TestBackendsWithCompiler::test_execution, test/test_jit.py::TestNnapiBackend::test_adaptive_avg_pool2d, test/test_jit.py::TestNnapiBackend::test_avg_pool2d, test/test_jit.py::TestNnapiBackend::test_cat, test/test_jit.py::TestNnapiBackend::test_compile_spec_santiy, test/test_jit.py::TestNnapiBackend::test_conv2d, test/test_jit.py::TestNnapiBackend::test_conv2d_transpose, test/test_jit.py::TestNnapiBackend::test_dequantize, test/test_jit.py::TestNnapiBackend::test_detach, test/test_jit.py::TestNnapiBackend::test_flatten, test/test_jit.py::TestNnapiBackend::test_hardtanh, test/test_jit.py::TestNnapiBackend::test_linear, test/test_jit.py::TestNnapiBackend::test_log_softmax, test/test_jit.py::TestNnapiBackend::test_max_pool2d, test/test_jit.py::TestNnapiBackend::test_mean, test/test_jit.py::TestNnapiBackend::test_multi_output, test/test_jit.py::TestNnapiBackend::test_pointwise_binary, test/test_jit.py::TestNnapiBackend::test_pointwise_binary_const, test/test_jit.py::TestNnapiBackend::test_pointwise_unary, test/test_jit.py::TestNnapiBackend::test_prelu, test/test_jit.py::TestNnapiBackend::test_qadd, test/test_jit.py::TestNnapiBackend::test_qlinear, test/test_jit.py::TestNnapiBackend::test_quantize, test/test_jit.py::TestNnapiBackend::test_reshape, test/test_jit.py::TestNnapiBackend::test_seblock_mul, test/test_jit.py::TestNnapiBackend::test_slice, test/test_jit.py::TestNnapiBackend::test_softmax, test/test_jit.py::TestNnapiBackend::test_tensor_input, test/test_jit.py::TestNnapiBackend::test_to, test/test_jit.py::TestNnapiBackend::test_unsqueeze, test/test_jit.py::TestNnapiBackend::test_upsample_nearest2d, test/test_jit.py::TestList::test_comprehension_iterable, test/test_jit.py::TestList::test_comprehension_out_type_not_in_type, test/test_jit.py::TestList::test_comprehensions_basic, test/test_jit.py::TestList::test_comprehensions_basic_float, test/test_jit.py::TestList::test_comprehensions_two_comps, test/test_jit.py::TestList::test_copy_list_immutable, test/test_jit.py::TestList::test_copy_list_mutable, test/test_jit.py::TestList::test_del, test/test_jit.py::TestList::test_dict_keyword_is_correctly_typed, test/test_jit.py::TestList::test_dict_keyword_with_dict_comprehension, test/test_jit.py::TestList::test_dict_keyword_with_dict_comprehension_and_kwargs, test/test_jit.py::TestList::test_dict_keyword_with_empty_dict_comprehension, test/test_jit.py::TestList::test_dict_keyword_with_empty_iterable, test/test_jit.py::TestList::test_dict_keyword_with_internal_aggregate_function, test/test_jit.py::TestList::test_dict_keyword_with_iterable, test/test_jit.py::TestList::test_dict_keyword_with_kwargs, test/test_jit.py::TestList::test_dict_keyword_with_kwargs_using_container_values, test/test_jit.py::TestList::test_dict_keyword_with_mapping, test/test_jit.py::TestList::test_dict_keyword_with_mapping_and_kwargs, test/test_jit.py::TestList::test_dict_keyword_with_mismatched_annotations, test/test_jit.py::TestList::test_dict_keyword_with_nested_call, test/test_jit.py::TestList::test_dict_keyword_with_previously_declared_variable, test/test_jit.py::TestList::test_dict_keyword_with_previously_declared_variable_and_kwargs, test/test_jit.py::TestList::test_extend_list_immutable, test/test_jit.py::TestList::test_extend_list_mutable, test/test_jit.py::TestList::test_in_check, test/test_jit.py::TestList::test_list_bool_conversion, test/test_jit.py::TestList::test_list_count, test/test_jit.py::TestList::test_list_count_not_existing, test/test_jit.py::TestList::test_list_gather, test/test_jit.py::TestList::test_list_index, test/test_jit.py::TestList::test_list_index_not_existing, test/test_jit.py::TestList::test_list_keyword, test/test_jit.py::TestList::test_list_len, test/test_jit.py::TestList::test_list_literal, test/test_jit.py::TestList::test_list_none, test/test_jit.py::TestList::test_list_ops, test/test_jit.py::TestList::test_list_slice, test/test_jit.py::TestList::test_list_sort, test/test_jit.py::TestList::test_list_unification_hint, test/test_jit.py::TestList::test_list_variance, test/test_jit.py::TestList::test_min_bool_list, test/test_jit.py::TestList::test_min_max_list, test/test_jit.py::TestList::test_min_max_single_list, test/test_jit.py::TestList::test_mutable_list_append, test/test_jit.py::TestList::test_mutable_list_append_2, test/test_jit.py::TestList::test_mutable_list_append_if, test/test_jit.py::TestList::test_mutable_list_append_if_else, test/test_jit.py::TestList::test_mutable_list_append_loop, test/test_jit.py::TestList::test_mutable_list_append_loop_if, test/test_jit.py::TestList::test_mutable_list_clear, test/test_jit.py::TestList::test_mutable_list_clear_empty, test/test_jit.py::TestList::test_mutable_list_function_inline, test/test_jit.py::TestList::test_mutable_list_insert, test/test_jit.py::TestList::test_mutable_list_insert_neg_out_of_bounds, test/test_jit.py::TestList::test_mutable_list_insert_negative, test/test_jit.py::TestList::test_mutable_list_insert_out_of_bounds, test/test_jit.py::TestList::test_mutable_list_nested_loop, test/test_jit.py::TestList::test_mutable_list_pop, test/test_jit.py::TestList::test_mutable_list_pop2, test/test_jit.py::TestList::test_mutable_list_pop_at, test/test_jit.py::TestList::test_mutable_list_pop_at2, test/test_jit.py::TestList::test_mutable_list_pop_at_negative, test/test_jit.py::TestList::test_mutable_list_pop_at_negative2, test/test_jit.py::TestList::test_mutable_list_pop_empty, test/test_jit.py::TestList::test_mutable_list_pop_slice, test/test_jit.py::TestList::test_mutable_list_remove, test/test_jit.py::TestList::test_mutable_list_remove2, test/test_jit.py::TestList::test_mutable_list_remove_not_existing, test/test_jit.py::TestList::test_mutable_list_remove_tensor, test/test_jit.py::TestList::test_mutable_list_reverse, test/test_jit.py::TestList::test_mutable_list_reverse_empty, test/test_jit.py::TestList::test_mutable_tensor_list_reverse, test/test_jit.py::TestList::test_no_element_type_annotation, test/test_jit.py::TestList::test_slice_index, test/test_jit.py::TestList::test_tensor_list_count, test/test_jit.py::TestList::test_tensor_list_count_not_existing, test/test_jit.py::TestList::test_tensor_list_index, test/test_jit.py::TestList::test_tensor_list_index_not_existing, test/test_jit.py::TestList::test_to_list, test/test_jit.py::TestList::test_to_list_gpu, test/test_jit.py::TestDict::test_aug_assign, test/test_jit.py::TestDict::test_basic, test/test_jit.py::TestDict::test_clear, test/test_jit.py::TestDict::test_copy, test/test_jit.py::TestDict::test_del, test/test_jit.py::TestDict::test_dict_bool_conversion, test/test_jit.py::TestDict::test_dict_preserves_order, test/test_jit.py::TestDict::test_dict_to_python, test/test_jit.py::TestDict::test_dict_variance, test/test_jit.py::TestDict::test_get, test/test_jit.py::TestDict::test_get_boolkey, test/test_jit.py::TestDict::test_items, test/test_jit.py::TestDict::test_key_type, test/test_jit.py::TestDict::test_keys, test/test_jit.py::TestDict::test_len, test/test_jit.py::TestDict::test_loop, test/test_jit.py::TestDict::test_membership, test/test_jit.py::TestDict::test_mutability, test/test_jit.py::TestDict::test_optional_dict_construct, test/test_jit.py::TestDict::test_ordered_dict, test/test_jit.py::TestDict::test_pop, test/test_jit.py::TestDict::test_popitem, test/test_jit.py::TestDict::test_setdefault, test/test_jit.py::TestDict::test_type_annotation_missing_contained_type, test/test_jit.py::TestDict::test_update, test/test_jit.py::TestDict::test_update_existing_key, test/test_jit.py::TestDict::test_values, test/test_jit.py::TestDict::test_view, test/test_jit.py::TestNamedTuple::test_namedtuple, test/test_jit.py::TestNamedTuple::test_namedtuple_as_attr, test/test_jit.py::TestNamedTuple::test_namedtuple_constant, test/test_jit.py::TestNamedTuple::test_namedtuple_input_forwardref, test/test_jit.py::TestNamedTuple::test_namedtuple_inside_forwardref, test/test_jit.py::TestNamedTuple::test_namedtuple_kwarg_construct, test/test_jit.py::TestNamedTuple::test_namedtuple_lower, test/test_jit.py::TestNamedTuple::test_namedtuple_resolution, test/test_jit.py::TestNamedTuple::test_namedtuple_resolution_forwardref, test/test_jit.py::TestNamedTuple::test_namedtuple_serialization, test/test_jit.py::TestNamedTuple::test_namedtuple_slice_unpack, test/test_jit.py::TestNamedTuple::test_namedtuple_type_annotation, test/test_jit.py::TestNamedTuple::test_namedtuple_wrong_types, test/test_jit.py::TestNamedTuple::test_return_named_tuple, test/test_jit.py::TestScriptDict::test_bool, test/test_jit.py::TestScriptDict::test_contains, test/test_jit.py::TestScriptDict::test_delitem, test/test_jit.py::TestScriptDict::test_getitem, test/test_jit.py::TestScriptDict::test_items, test/test_jit.py::TestScriptDict::test_iter, test/test_jit.py::TestScriptDict::test_len, test/test_jit.py::TestScriptDict::test_nested, test/test_jit.py::TestScriptDict::test_reference_semantics, test/test_jit.py::TestScriptDict::test_repr, test/test_jit.py::TestScriptDict::test_setitem, test/test_jit.py::TestScriptList::test_append, test/test_jit.py::TestScriptList::test_bool, test/test_jit.py::TestScriptList::test_clear, test/test_jit.py::TestScriptList::test_contains, test/test_jit.py::TestScriptList::test_count, test/test_jit.py::TestScriptList::test_defaultdict, test/test_jit.py::TestScriptList::test_delitem, test/test_jit.py::TestScriptList::test_extend, test/test_jit.py::TestScriptList::test_getitem, test/test_jit.py::TestScriptList::test_insert, test/test_jit.py::TestScriptList::test_iter, test/test_jit.py::TestScriptList::test_len, test/test_jit.py::TestScriptList::test_nested, test/test_jit.py::TestScriptList::test_pop, test/test_jit.py::TestScriptList::test_reference_semantics, test/test_jit.py::TestScriptList::test_remove, test/test_jit.py::TestScriptList::test_repr, test/test_jit.py::TestScriptList::test_setitem, test/test_jit.py::TestAsync::test_async_future_type_python, test/test_jit.py::TestAsync::test_async_grad_guard_no_grad, test/test_jit.py::TestAsync::test_async_grad_guard_with_grad, test/test_jit.py::TestAsync::test_async_kwargs, test/test_jit.py::TestAsync::test_async_parsing, test/test_jit.py::TestAsync::test_async_python, test/test_jit.py::TestAsync::test_async_script, test/test_jit.py::TestAsync::test_async_script_capture, test/test_jit.py::TestAsync::test_async_script_error, test/test_jit.py::TestAsync::test_async_script_multi_forks, test/test_jit.py::TestAsync::test_async_script_multi_waits, test/test_jit.py::TestAsync::test_async_script_nested, test/test_jit.py::TestAsync::test_async_script_no_script_mod, test/test_jit.py::TestAsync::test_async_script_trace, test/test_jit.py::TestAsync::test_future_subtyping, test/test_jit.py::TestAsync::test_no_future_subtype_message, test/test_jit.py::TestAsync::test_trace_fork_wait, test/test_jit.py::TestAsync::test_trace_fork_wait_inline, test/test_jit.py::TestAsync::test_trace_fork_wait_leaking, test/test_jit.py::TestAsync::test_trace_fork_wait_list_modulecalls, test/test_jit.py::TestAsync::test_trace_modulecalls_with_different_output_types, test/test_jit.py::TestAwait::test_await_class_arg, test/test_jit.py::TestAwait::test_await_class_return, test/test_jit.py::TestAwait::test_await_eager_lazy, test/test_jit.py::TestAwait::test_await_func_arg, test/test_jit.py::TestAwait::test_await_getattr_implicit_convertion, test/test_jit.py::TestAwait::test_await_isinstance, test/test_jit.py::TestAwait::test_await_multiout_save, test/test_jit.py::TestAwait::test_await_nested, test/test_jit.py::TestAwait::test_await_out_of_interpreter, test/test_jit.py::TestAwait::test_await_python, test/test_jit.py::TestAwait::test_await_type_python, test/test_jit.py::TestAwait::test_awaitable_to_await, test/test_jit.py::TestAwait::test_eager_await_non_scriptable, test/test_jit.py::TestAwait::test_jit_trace, test/test_jit.py::TestAwait::test_nowait, test/test_jit.py::TestAwait::test_nowait_class, test/test_jit.py::TestAwait::test_script, test/test_jit.py::TestDataParallel::test_python_submodule_script, test/test_jit.py::TestDataParallel::test_shared_module, test/test_jit.py::TestDataParallel::test_tensor_sharing, test/test_jit.py::TestDataParallel::test_tensor_sharing_with_forward, test/test_jit.py::TestDataParallel::test_traced_module, test/test_jit.py::TestModels::test_alexnet, test/test_jit.py::TestModels::test_dcgan_models, test/test_jit.py::TestModels::test_dcgan_models_cuda, test/test_jit.py::TestModels::test_mnist, test/test_jit.py::TestModels::test_mnist_cuda, test/test_jit.py::TestModels::test_mnist_training_leaks_no_memory_cuda, test/test_jit.py::TestModels::test_neural_style, test/test_jit.py::TestModels::test_neural_style_cuda, test/test_jit.py::TestModels::test_reinforcement_learning, test/test_jit.py::TestModels::test_reinforcement_learning_cuda, test/test_jit.py::TestModels::test_script_module_script_resnet, test/test_jit.py::TestModels::test_script_module_trace_resnet18, test/test_jit.py::TestModels::test_snli, test/test_jit.py::TestModels::test_snli_cuda, test/test_jit.py::TestModels::test_super_resolution, test/test_jit.py::TestModels::test_super_resolution_cuda, test/test_jit.py::TestModels::test_time_sequence_prediction, test/test_jit.py::TestModels::test_vae, test/test_jit.py::TestModels::test_vae_cuda, test/test_jit.py::TestModules::test_script_module_with_constants_list, test/test_jit.py::TestAutodiffJit::test_autodiff_requires_grad_nograd, test/test_jit.py::TestAutodiffJit::test_requires_grad_outputs, test/test_jit.py::TestAutodiffJit::test_requires_grad_outputs_profiled_twice, test/test_jit.py::TestAutodiffJit::test_requires_grad_outputs_side_effects, test/test_jit.py::TestAutodiffJit::test_undefined_tensor_lists, test/test_jit.py::TestAutodiffSubgraphSlicing::test_aliased_outputs, test/test_jit.py::TestAutodiffSubgraphSlicing::test_bias_as_arg, test/test_jit.py::TestAutodiffSubgraphSlicing::test_bias_as_module_attr, test/test_jit.py::TestAutodiffSubgraphSlicing::test_chunk_constant_script_ad, test/test_jit.py::TestAutodiffSubgraphSlicing::test_constructed_bias, test/test_jit.py::TestAutodiffSubgraphSlicing::test_diff_graph_inline_threshold, test/test_jit.py::TestAutodiffSubgraphSlicing::test_differentiable_graph_ops_requires_grad, test/test_jit.py::TestAutodiffSubgraphSlicing::test_does_not_create_cycles, test/test_jit.py::TestAutodiffSubgraphSlicing::test_does_not_merge_unrelated, test/test_jit.py::TestAutodiffSubgraphSlicing::test_has_profiled_info_aliasing_outputs, test/test_jit.py::TestAutodiffSubgraphSlicing::test_merge_respects_aliasing, test/test_jit.py::TestAutodiffSubgraphSlicing::test_merges_dense, test/test_jit.py::TestAutodiffSubgraphSlicing::test_merges_down, test/test_jit.py::TestAutodiffSubgraphSlicing::test_merges_up, test/test_jit.py::TestAutodiffSubgraphSlicing::test_merges_without_cycles, test/test_jit.py::TestAutodiffSubgraphSlicing::test_prune_grad, test/test_jit.py::TestAutodiffSubgraphSlicing::test_requires_grad_for_tensor_list, test/test_jit.py::TestAutodiffSubgraphSlicing::test_respects_lexical_scoping, test/test_jit.py::TestAutodiffSubgraphSlicing::test_simple_merge, test/test_jit.py::TestAutodiffSubgraphSlicing::test_simple_no_merge, test/test_jit.py::TestCustomOperators::test_calling_scripted_custom_op, test/test_jit.py::TestCustomOperators::test_calling_traced_custom_op, test/test_jit.py::TestCustomOperators::test_default_arguments_are_used, test/test_jit.py::TestCustomOperators::test_dynamic_op_registry, test/test_jit.py::TestCustomOperators::test_generic_list, test/test_jit.py::TestCustomOperators::test_getting_invalid_attr, test/test_jit.py::TestCustomOperators::test_passing_and_returning_lists, test/test_jit.py::TestCustomOperators::test_passing_one_positional_but_not_the_second, test/test_jit.py::TestCustomOperators::test_passing_too_few_args, test/test_jit.py::TestCustomOperators::test_passing_too_many_args, test/test_jit.py::TestCustomOperators::test_passing_unknown_kwargs, test/test_jit.py::TestCustomOperators::test_script_graph_contains_custom_op, test/test_jit.py::TestCustomOperators::test_script_graph_for_custom_ops_matches_traced_graph, test/test_jit.py::TestCustomOperators::test_simply_calling_an_operator, test/test_jit.py::TestCustomOperators::test_where_no_scalar, test/test_jit.py::TestGraphRewritePasses::test_fuse_linear, test/test_jit.py::TestClassType::test_cast_overloads, test/test_jit.py::TestClassType::test_class_attribute_wrong_type, test/test_jit.py::TestClassType::test_class_constant, test/test_jit.py::TestClassType::test_class_constructs_itself, test/test_jit.py::TestClassType::test_class_inheritance, test/test_jit.py::TestClassType::test_class_inheritance_implicit, test/test_jit.py::TestClassType::test_class_sorting, test/test_jit.py::TestClassType::test_class_specialization, test/test_jit.py::TestClassType::test_class_type_as_param, test/test_jit.py::TestClassType::test_classmethod, test/test_jit.py::TestClassType::test_conditional_set_attr, test/test_jit.py::TestClassType::test_custom_delete, test/test_jit.py::TestClassType::test_default_args, test/test_jit.py::TestClassType::test_get_attr, test/test_jit.py::TestClassType::test_get_attr_not_initialized, test/test_jit.py::TestClassType::test_get_with_method, test/test_jit.py::TestClassType::test_imported_classes, test/test_jit.py::TestClassType::test_in, test/test_jit.py::TestClassType::test_init_compiled_first, test/test_jit.py::TestClassType::test_interface, test/test_jit.py::TestClassType::test_optional_type_promotion, test/test_jit.py::TestClassType::test_out_of_order_methods, test/test_jit.py::TestClassType::test_overloaded_fn, test/test_jit.py::TestClassType::test_properties, test/test_jit.py::TestClassType::test_py_class_to_ivalue_missing_attribute, test/test_jit.py::TestClassType::test_python_interop, test/test_jit.py::TestClassType::test_recursive_class, test/test_jit.py::TestClassType::test_recursive_script_builtin_type_resolution, test/test_jit.py::TestClassType::test_recursive_script_module_builtin_type_resolution, test/test_jit.py::TestClassType::test_recursive_scripting, test/test_jit.py::TestClassType::test_recursive_scripting_failed, test/test_jit.py::TestClassType::test_reference_semantics, test/test_jit.py::TestClassType::test_save_load_with_classes, test/test_jit.py::TestClassType::test_save_load_with_classes_nested, test/test_jit.py::TestClassType::test_save_load_with_classes_returned, test/test_jit.py::TestClassType::test_schema_human_readable, test/test_jit.py::TestClassType::test_self_referential_method, test/test_jit.py::TestClassType::test_set_attr_in_method, test/test_jit.py::TestClassType::test_set_attr_non_initialized, test/test_jit.py::TestClassType::test_set_attr_type_mismatch, test/test_jit.py::TestClassType::test_staticmethod, test/test_jit.py::TestClassType::test_type_annotation, test/test_jit.py::TestClassType::test_type_annotations, test/test_jit.py::TestClassType::test_unresolved_class_attributes, test/test_jit.py::TestClassType::test_unused_method, test/test_jit.py::TestBuiltins::test_del, test/test_jit.py::TestBuiltins::test_del_multiple_operands, test/test_jit.py::TestBuiltins::test_has_attr, test/test_jit.py::TestBuiltins::test_has_attr_invalid_args, test/test_jit.py::TestTensorBuiltins::test_method_on_number, test/test_jit.py::TestTensorBuiltins::test_scalar_to_num_conversions, test/test_jit.py::TestTensorBuiltins::test_tensor_item, test/test_jit.py::TestTensorBuiltins::test_tensor_properties, test/test_jit.py::TestTensorBuiltins::test_tensor_subscript_assign, test/test_jit.py::TestTensorBuiltins::test_tensor_subscript_assign_device, test/test_jit.py::TestIgnoreContextManager::test_with_ignore_context_manager_with_inp_out, test/test_jit.py::TestIgnoreContextManager::test_with_ignore_context_manager_with_just_inp, test/test_jit.py::TestIgnoreContextManager::test_with_ignore_context_manager_with_just_out, test/test_jit.py::TestSymbolicShapeAnalysis::test_adaptive_avg_pool2d, test/test_jit.py::TestSymbolicShapeAnalysis::test_arange_shape, test/test_jit.py::TestSymbolicShapeAnalysis::test_binary_shape_fns_inplace, test/test_jit.py::TestSymbolicShapeAnalysis::test_binary_shape_functions, test/test_jit.py::TestSymbolicShapeAnalysis::test_conv_deconv, test/test_jit.py::TestSymbolicShapeAnalysis::test_convolution_backward, test/test_jit.py::TestSymbolicShapeAnalysis::test_cross_entropy_loss, test/test_jit.py::TestSymbolicShapeAnalysis::test_if_propagation, test/test_jit.py::TestSymbolicShapeAnalysis::test_partial_eval_graph_conv, test/test_jit.py::TestSymbolicShapeAnalysis::test_partial_eval_stitching, test/test_jit.py::TestSymbolicShapeAnalysis::test_refinement_through_graph_stitching, test/test_jit.py::TestSymbolicShapeAnalysis::test_register_function_error_checking, test/test_jit.py::TestSymbolicShapeAnalysis::test_returning_input_symbolic_shapes, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_analysis, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_concat, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_embedding_bag, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_function_includes, test/test_jit.py::TestSymbolicShapeAnalysis::test_shared_shape_graph, test/test_jit.py::TestSymbolicShapeAnalysis::test_size_and_sizes, test/test_jit.py::TestSymbolicShapeAnalysis::test_squeeze_dims, test/test_jit.py::TestSymbolicShapeAnalysis::test_stitching_concat, test/test_jit.py::TestSymbolicShapeAnalysis::test_stitching_multi_output, test/test_jit.py::TestSymbolicShapeAnalysis::test_sym_ir_parsing, test/test_jit.py::TestSymbolicShapeAnalysis::test_unary_shape_fns_inplace, test/test_jit.py::TestSymbolicShapeAnalysis::test_unary_shape_functions, test/test_jit.py::TestSymbolicShapeAnalysis::test_write, test/test_jit.py::TestOpDecompositions::test_op_decomposition, test/test_jit.py::TestOpDecompositions::test_registered_decomposition, test/test_jit.py::TestUnsupportedOps::test_factory_ops_requires_grad_fail, test/test_jit.py::TestUnsupportedOps::test_init_ops, test/test_jit.py::TestFreezing::test_freeze_interface_swapping_two_methods, test/test_jit.py::TestFreezing::test_freeze_interface_within_object, test/test_jit.py::TestFreezing::test_freeze_module, test/test_jit.py::TestFreezing::test_freeze_module_detach_gradient, test/test_jit.py::TestFreezing::test_freeze_module_in_training_mode, test/test_jit.py::TestFreezing::test_freeze_module_inlining, test/test_jit.py::TestFreezing::test_freeze_module_no_forward, test/test_jit.py::TestFreezing::test_freeze_module_return_self, test/test_jit.py::TestFreezing::test_freeze_module_return_sub_module, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_attr, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_attr2, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_attr3, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_tensor_attr, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_tensor_attr2, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_tensor_attr3, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_tensor_attr4, test/test_jit.py::TestFreezing::test_freeze_module_with_call_method, test/test_jit.py::TestFreezing::test_freeze_module_with_fork, test/test_jit.py::TestFreezing::test_freeze_module_with_fork2, test/test_jit.py::TestFreezing::test_freeze_module_with_fork_calling_module_method, test/test_jit.py::TestFreezing::test_freeze_module_with_helperfunction, test/test_jit.py::TestFreezing::test_freeze_module_with_inplace_mutable, test/test_jit.py::TestFreezing::test_freeze_module_with_list, test/test_jit.py::TestFreezing::test_freeze_module_with_mutable_dict, test/test_jit.py::TestFreezing::test_freeze_module_with_mutable_list, test/test_jit.py::TestFreezing::test_freeze_module_with_mutable_tensor, test/test_jit.py::TestFreezing::test_freeze_module_with_nested_fork, test/test_jit.py::TestFreezing::test_freeze_module_with_nestedaliasing, test/test_jit.py::TestFreezing::test_freeze_module_with_nestedaliasingscalar, test/test_jit.py::TestFreezing::test_freeze_module_with_non_static_module_container_index, test/test_jit.py::TestFreezing::test_freeze_module_with_overlapping_attrs, test/test_jit.py::TestFreezing::test_freeze_module_with_preserve_sub_module, test/test_jit.py::TestFreezing::test_freeze_module_with_preserve_sub_module_and_mutation, test/test_jit.py::TestFreezing::test_freeze_module_with_sharedclasstype, test/test_jit.py::TestFreezing::test_freeze_module_with_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_tensor, test/test_jit.py::TestFreezing::test_freeze_module_with_tuple, test/test_jit.py::TestFreezing::test_freeze_module_with_tupleoutput_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_attr, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_attribute_on_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_attribute_on_unused_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_method, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_method2, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_method_on_submodule, test/test_jit.py::TestFreezing::test_freeze_no_forward, test/test_jit.py::TestFreezing::test_freeze_non_interface_module_swap, test/test_jit.py::TestFreezing::test_freeze_non_module_class_getattr, test/test_jit.py::TestFreezing::test_freeze_recursive_interfaces, test/test_jit.py::TestFreezing::test_freeze_recursive_interfaces_same_name, test/test_jit.py::TestFreezing::test_freeze_recursive_interfaces_with_reassignment, test/test_jit.py::TestFreezing::test_freeze_with_interface_mutable, test/test_jit.py::TestFreezing::test_freeze_with_swapping_interfaces, test/test_jit.py::TestFreezing::test_module_getattr_indirection, test/test_jit.py::TestFreezing::test_module_with_shared_type_instances, test/test_jit.py::TestFrozenOptimizations::test_bn_not_broadcast_with_linear, test/test_jit.py::TestFrozenOptimizations::test_collapse_adjacent_conversions, test/test_jit.py::TestFrozenOptimizations::test_conv_add_folding, test/test_jit.py::TestFrozenOptimizations::test_conv_bn_folding, test/test_jit.py::TestFrozenOptimizations::test_conv_bn_folding_autocast_scenario_cuda, test/test_jit.py::TestFrozenOptimizations::test_conv_bn_folding_not_forward, test/test_jit.py::TestFrozenOptimizations::test_conv_hardswish, test/test_jit.py::TestFrozenOptimizations::test_conv_mul_add_bn, test/test_jit.py::TestFrozenOptimizations::test_conv_to_mkldnn, test/test_jit.py::TestFrozenOptimizations::test_conv_to_mkldnn_no_mkldnn, test/test_jit.py::TestFrozenOptimizations::test_freeze_conv_relu_fusion, test/test_jit.py::TestFrozenOptimizations::test_freeze_conv_relu_fusion_not_forward, test/test_jit.py::TestFrozenOptimizations::test_freeze_mkdlnn, test/test_jit.py::TestFrozenOptimizations::test_freeze_remove_dropout, test/test_jit.py::TestFrozenOptimizations::test_freeze_remove_feature_dropout, test/test_jit.py::TestFrozenOptimizations::test_hardswish_hardsigmoid, test/test_jit.py::TestFrozenOptimizations::test_incompatible_perf_formats, test/test_jit.py::TestFrozenOptimizations::test_linear_bn_folding, test/test_jit.py::TestFrozenOptimizations::test_linear_bn_folding_autocast_scenario_cuda, test/test_jit.py::TestFrozenOptimizations::test_linear_concat, test/test_jit.py::TestFrozenOptimizations::test_linear_concat_complex, test/test_jit.py::TestFrozenOptimizations::test_linear_concat_different_input, test/test_jit.py::TestFrozenOptimizations::test_linear_multiple_blocks, test/test_jit.py::TestFrozenOptimizations::test_linear_non_constant_weight, test/test_jit.py::TestFrozenOptimizations::test_linear_transpose, test/test_jit.py::TestFrozenOptimizations::test_maxpool_mkldnn, test/test_jit.py::TestFrozenOptimizations::test_mkldnn_fuser_broadcasting, test/test_jit.py::TestFrozenOptimizations::test_mkldnn_inplace_removal, test/test_jit.py::TestFrozenOptimizations::test_numel_less_than_size_with_padding, test/test_jit.py::TestFrozenOptimizations::test_optimize_freeze_module, test/test_jit.py::TestFrozenOptimizations::test_pool2d_batchnorm, test/test_jit.py::TestFrozenOptimizations::test_pool3d_batchnorm, test/test_jit.py::TestFrozenOptimizations::test_remove_detach, test/test_jit.py::TestFrozenOptimizations::test_remove_detach_not_applied, test/test_jit.py::TestFrozenOptimizations::test_scalar_mul, test/test_jit.py::TestMKLDNNReinplacing::test_always_alive_values, test/test_jit.py::TestMKLDNNReinplacing::test_merge_liveness, test/test_jit.py::TestMKLDNNReinplacing::test_successful, test/test_jit.py::TestMKLDNNReinplacing::test_switch_inputs_to_inplace, test/test_jit.py::TestPeephole::test_conv_dim_folding, test/test_jit.py::TestPeephole::test_integer_refinement, test/test_jit.py::TestPeephole::test_noop_peephole, test/test_jit.py::TestPeephole::test_normalized_is_op, test/test_jit.py::TestPeephole::test_normalized_isnot_op, test/test_jit.py::TestPeephole::test_normalized_rsub, test/test_jit.py::TestPeephole::test_optimize_out_comparison_same_value, test/test_jit.py::TestPeephole::test_peephole, test/test_jit.py::TestPeephole::test_peephole_add_zero, test/test_jit.py::TestPeephole::test_peephole_arith, test/test_jit.py::TestPeephole::test_peephole_cuda, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_dict_modified, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_get_input_arg, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_keys_might_overlap, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_missing_key, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_overlapping_keys, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_unsupported_type, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_simple, test/test_jit.py::TestPeephole::test_peephole_dict_len, test/test_jit.py::TestPeephole::test_peephole_dict_len_no_optimization_keys_might_overlap, test/test_jit.py::TestPeephole::test_peephole_dict_len_no_optimization_overlapping_keys, test/test_jit.py::TestPeephole::test_peephole_dict_len_no_optimization_unsupported_type, test/test_jit.py::TestPeephole::test_peephole_dynamic, test/test_jit.py::TestPeephole::test_peephole_int, test/test_jit.py::TestPeephole::test_peephole_len_list, test/test_jit.py::TestPeephole::test_peephole_list_len, test/test_jit.py::TestPeephole::test_peephole_list_ops, test/test_jit.py::TestPeephole::test_peephole_no_output_aliasing, test/test_jit.py::TestPeephole::test_peephole_optional_refine, test/test_jit.py::TestPeephole::test_peephole_slice_all_three_args, test/test_jit.py::TestPeephole::test_peephole_slice_one_empty_arg, test/test_jit.py::TestPeephole::test_peephole_slice_optimization_not_applied_list_modified, test/test_jit.py::TestPeephole::test_peephole_slice_optimization_not_applied_non_const_args, test/test_jit.py::TestPeephole::test_peephole_slice_two_empty_args, test/test_jit.py::TestPeephole::test_peephole_type_refinements, test/test_jit.py::TestPeephole::test_peephole_with_non_output_writes, test/test_jit.py::TestPeephole::test_peephole_with_writes, test/test_jit.py::TestPeephole::test_refine_integer_values, test/test_jit.py::TestPeephole::test_short_circuit_optimization, test/test_jit.py::TestAliasAnalysis::test_becomes_wildcard_annotations, test/test_jit.py::TestAliasAnalysis::test_multiple_compilation_units, test/test_jit.py::TestAliasAnalysis::test_nested_list_construct_not_wildcard, test/test_jit.py::TestAliasAnalysis::test_recursive_calls, test/test_jit.py::TestSaveLoad::test_different_functions, test/test_jit.py::TestSaveLoad::test_different_interfaces, test/test_jit.py::TestSaveLoad::test_different_modules, test/test_jit.py::TestSaveLoad::test_many_collisions, test/test_jit.py::TestSaveLoad::test_save_load_large_string_attribute, test/test_jit.py::TestSaveLoad::test_save_load_meta_tensors, test/test_jit.py::TestSaveLoad::test_save_load_meta_tensors_to_device, test/test_jit.py::TestSaveLoad::test_save_load_params_buffers_submodules, test/test_jit.py::TestSaveLoad::test_save_load_using_pathlib, test/test_jit.py::TestSaveLoad::test_save_load_with_extra_files, test/test_jit.py::TestSaveLoad::test_save_load_with_saved_traced_inputs, test/test_jit.py::TestSaveLoad::test_save_namedtuple_input_only, test/test_jit.py::TestSaveLoad::test_save_namedtuple_input_only_forwardref, test/test_jit.py::TestSaveLoad::test_save_namedtuple_output_only, test/test_jit.py::TestSaveLoad::test_save_nonexit_file, test/test_jit.py::TestSaveLoadFlatbuffer::test_different_functions, test/test_jit.py::TestSaveLoadFlatbuffer::test_different_interfaces, test/test_jit.py::TestSaveLoadFlatbuffer::test_different_modules, test/test_jit.py::TestSaveLoadFlatbuffer::test_many_collisions, test/test_jit.py::TestSaveLoadFlatbuffer::test_module_info_flatbuffer, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_load_params_buffers_submodules, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_load_using_pathlib, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_load_with_extra_files, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_namedtuple_input_only, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_namedtuple_output_only, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar_inplace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar_reciprocal, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar_scalar, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_tensor, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_tensor_inplace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_tensor_out, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_linspace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_linspace_out, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_logspace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_logspace_out, test/test_jit.py::TestModuleContainers::test_custom_container_forward, test/test_jit.py::TestModuleContainers::test_empty_dict_override_contains, test/test_jit.py::TestModuleContainers::test_module_inplace_construct, test/test_jit.py::TestModuleContainers::test_module_interface_special_methods, test/test_jit.py::TestModuleContainers::test_module_properties, test/test_jit.py::TestModuleContainers::test_moduledict, test/test_jit.py::TestModuleContainers::test_moduledict_getitem, test/test_jit.py::TestModuleContainers::test_moduledict_keyerror, test/test_jit.py::TestModuleContainers::test_normal_list_attribute_with_modules_error, test/test_jit.py::TestModuleContainers::test_parameterdict_script_getitem, test/test_jit.py::TestModuleContainers::test_parameterlist_script_getitem, test/test_jit.py::TestModuleContainers::test_parameterlist_script_iter, test/test_jit.py::TestModuleContainers::test_script_module_list_sequential, test/test_jit.py::TestModuleContainers::test_script_modulelist_index, test/test_jit.py::TestModuleContainers::test_sequential_intermediary_types, test/test_jit.py::TestModuleContainers::test_special_method_with_override, test/test_jit.py::TestModuleContainers::test_typed_module_dict, test/test_jit.py::TestModuleContainers::test_typed_module_list, test/test_jit.py::TestPythonBindings::test_add_input, test/test_jit.py::TestPythonBindings::test_aliasdb, test/test_jit.py::TestPythonBindings::test_canonicalize, test/test_jit.py::TestPythonBindings::test_cu_create_function, test/test_jit.py::TestPythonBindings::test_cu_get_functions, test/test_jit.py::TestPythonBindings::test_graph_create, test/test_jit.py::TestPythonBindings::test_graph_iterator_keepalive, test/test_jit.py::TestPythonBindings::test_invalidation, test/test_jit.py::TestPythonIr::test_param_strides, test/test_jit.py::TestPythonIr::test_permute_inputs_binding, test/test_jit.py::TestPythonIr::test_python_ir_utils, test/test_jit.py::TestPythonIr::test_python_ir_utils_graph, test/test_jit.py::TestFunctionalBlocks::test_subgraph_creation, test/test_jit.py::TestRemoveMutation::test_aten_inplace, test/test_jit.py::TestRemoveMutation::test_common_pytorch_list_ops, test/test_jit.py::TestRemoveMutation::test_if_output, test/test_jit.py::TestRemoveMutation::test_if_output_fail, test/test_jit.py::TestRemoveMutation::test_list_indexing_removal, test/test_jit.py::TestRemoveMutation::test_lists_append, test/test_jit.py::TestRemoveMutation::test_lists_insert, test/test_jit.py::TestRemoveMutation::test_special_mapped_op, test/test_jit.py::TestTorchbind::test_default_args, test/test_jit.py::TestTorchbind::test_hasattr, test/test_jit.py::TestTorchbind::test_lambda_as_constructor, test/test_jit.py::TestTorchbind::test_profiler_custom_op, test/test_jit.py::TestTorchbind::test_staticmethod, test/test_jit.py::TestTorchbind::test_torchbind, test/test_jit.py::TestTorchbind::test_torchbind_attr_exception, test/test_jit.py::TestTorchbind::test_torchbind_class_attr_recursive, test/test_jit.py::TestTorchbind::test_torchbind_class_attribute, test/test_jit.py::TestTorchbind::test_torchbind_deepcopy, test/test_jit.py::TestTorchbind::test_torchbind_def_property_getter_setter, test/test_jit.py::TestTorchbind::test_torchbind_def_property_just_getter, test/test_jit.py::TestTorchbind::test_torchbind_def_property_readwrite, test/test_jit.py::TestTorchbind::test_torchbind_getattr, test/test_jit.py::TestTorchbind::test_torchbind_getstate, test/test_jit.py::TestTorchbind::test_torchbind_instantiate_missing_class, test/test_jit.py::TestTorchbind::test_torchbind_lambda_method, test/test_jit.py::TestTorchbind::test_torchbind_no_init, test/test_jit.py::TestTorchbind::test_torchbind_optional_explicit_attr, test/test_jit.py::TestTorchbind::test_torchbind_pass_wrong_type, test/test_jit.py::TestTorchbind::test_torchbind_pickle_serialization, test/test_jit.py::TestTorchbind::test_torchbind_python_deepcopy, test/test_jit.py::TestTorchbind::test_torchbind_return_instance, test/test_jit.py::TestTorchbind::test_torchbind_return_instance_from_method, test/test_jit.py::TestTorchbind::test_torchbind_return_tuple, test/test_jit.py::TestTorchbind::test_torchbind_save_load, test/test_jit.py::TestTorchbind::test_torchbind_take_as_arg, test/test_jit.py::TestTorchbind::test_torchbind_take_instance_as_method_arg, test/test_jit.py::TestTorchbind::test_torchbind_tracing, test/test_jit.py::TestTorchbind::test_torchbind_tracing_nested, test/test_jit.py::TestModuleInterface::test_freeze_module_with_inplace_mutation_in_interface, test/test_jit.py::TestModuleInterface::test_freeze_module_with_interface, test/test_jit.py::TestModuleInterface::test_freeze_module_with_interface_and_fork, test/test_jit.py::TestModuleInterface::test_freeze_module_with_mutated_interface, test/test_jit.py::TestModuleInterface::test_freeze_module_with_setattr_in_interface, test/test_jit.py::TestModuleInterface::test_module_apis_interface, test/test_jit.py::TestModuleInterface::test_module_doc_string, test/test_jit.py::TestModuleInterface::test_module_interface, test/test_jit.py::TestModuleInterface::test_module_interface_inheritance, test/test_jit.py::TestModuleInterface::test_module_interface_subtype, test/test_jit.py::TestModuleInterface::test_module_swap, test/test_jit.py::TestModuleInterface::test_module_swap_no_lazy_compile, test/test_jit.py::TestModuleInterface::test_module_swap_no_module_interface, test/test_jit.py::TestModuleInterface::test_module_swap_wrong_module, test/test_jit.py::TestModuleInterface::test_not_submodule_interface_call, test/test_jit.py::TestModuleInterface::test_script_module_as_interface_swap, test/test_jit.py::TestWith::test_with_as, test/test_jit.py::TestWith::test_with_errors, test/test_jit.py::TestWith::test_with_exceptions, test/test_jit.py::TestWith::test_with_no_as, test/test_jit.py::TestWith::test_with_no_grad, test/test_jit.py::TestWith::test_with_record_function, test/test_jit.py::TestEnum::test_closed_over_enum_constant, test/test_jit.py::TestEnum::test_enum_as_const, test/test_jit.py::TestEnum::test_enum_as_module_attribute, test/test_jit.py::TestEnum::test_enum_comp, test/test_jit.py::TestEnum::test_enum_comp_diff_classes, test/test_jit.py::TestEnum::test_enum_explicit_script, test/test_jit.py::TestEnum::test_enum_iterate, test/test_jit.py::TestEnum::test_enum_ivalue_type, test/test_jit.py::TestEnum::test_enum_module_return, test/test_jit.py::TestEnum::test_enum_name, test/test_jit.py::TestEnum::test_enum_return, test/test_jit.py::TestEnum::test_enum_value, test/test_jit.py::TestEnum::test_enum_value_types, test/test_jit.py::TestEnum::test_heterogenous_value_type_enum_error, test/test_jit.py::TestEnum::test_non_existent_enum_value, test/test_jit.py::TestEnum::test_string_enum_as_module_attribute, test/test_jit.py::TestEnum::test_typed_enum, test/test_jit.py::TestStringFormatting::test_modulo_operator, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_alternate_digit_placeholder, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_capital_exponent_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_char_placeholder_and_char_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_char_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_char_placeholder_and_true_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_digit_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_digit_placeholder_and_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_double_percent_in_string, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_exponent_placeholder_and_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_float_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_float_placeholder_and_float_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_lowercase_exponent_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_multiple_placeholders, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_percent_in_string, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_string_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_string_placeholder_and_format_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_string_placeholder_and_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_subscript, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_too_few_arguments, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_too_many_arguments, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_unknown_format_specifier, test/test_jit.py::TestProfiler::test_aliasing_merge, test/test_jit.py::TestProfiler::test_autograd_fallback_graph, test/test_jit.py::TestProfiler::test_fallback_graph_not_specialized, test/test_jit.py::TestProfiler::test_iterative_fusion, test/test_jit.py::TestProfiler::test_local_fusion_strategy, test/test_jit.py::TestProfiler::test_not_fusing_scalar_ops, test/test_jit.py::TestProfiler::test_not_optimizing_property, test/test_jit.py::TestProfiler::test_specialize_backward, test/test_jit.py::TestProfiler::test_specialized_types, test/test_jit.py::TestProfiler::test_tensor_constant, test/test_jit.py::TestProfiler::test_tensor_type_not_determined_by_inputs, test/test_jit.py::TestProfiler::test_use_not_profiled, test/test_jit.py::TestSlice::test_module_list_slicing, test/test_jit.py::TestSlice::test_slice_as_variable, test/test_jit.py::TestSlice::test_slice_dynamic_index, test/test_jit.py::TestSlice::test_slice_kwarg, test/test_jit.py::TestSlice::test_slice_one_none, test/test_jit.py::TestSlice::test_slice_start_stop, test/test_jit.py::TestSlice::test_slice_start_stop_step, test/test_jit.py::TestSlice::test_slice_start_stop_with_none, test/test_jit.py::TestSlice::test_slice_stop_clipped, test/test_jit.py::TestSlice::test_slice_stop_only, test/test_jit.py::TestSlice::test_slice_stop_only_with_nones, test/test_jit.py::TestSlice::test_slice_string, test/test_jit.py::TestSlice::test_slice_tensor, test/test_jit.py::TestSlice::test_slice_tensor_multidim, test/test_jit.py::TestSlice::test_slice_tensor_multidim_with_dots, test/test_jit.py::TestSlice::test_slice_three_nones, test/test_jit.py::TestSlice::test_slice_two_nones, test/test_jit.py::TestSlice::test_tuple_slicing, test/test_jit.py::TestIgnorableArgs::test_add_out_ignorable_args, test/test_jit.py::TestIgnorableArgs::test_slice_ignorable_args_for_slice, test/test_jit.py::TestHooks::test_forward_tuple_input, test/test_jit.py::TestHooks::test_hook_compilation_hint, test/test_jit.py::TestHooks::test_hook_hook_name_collision, test/test_jit.py::TestHooks::test_hook_method_name_collision, test/test_jit.py::TestHooks::test_module_direct_forward_invocation, test/test_jit.py::TestHooks::test_module_forward_multiple_inputs, test/test_jit.py::TestHooks::test_module_forward_single_input, test/test_jit.py::TestHooks::test_module_hook_return_nothing, test/test_jit.py::TestHooks::test_module_multiple_hooks_multiple_inputs, test/test_jit.py::TestHooks::test_module_multiple_hooks_single_input, test/test_jit.py::TestHooks::test_module_no_forward_input, test/test_jit.py::TestHooks::test_module_same_hook_repeated, test/test_jit.py::TestHooks::test_submodule_called_directly_with_hooks, test/test_jit.py::TestHooks::test_submodule_direct_forward_invocation, test/test_jit.py::TestHooks::test_submodule_forward_multiple_inputs, test/test_jit.py::TestHooks::test_submodule_forward_single_input, test/test_jit.py::TestHooks::test_submodule_forward_single_input_return_not_tupled, test/test_jit.py::TestHooks::test_submodule_hook_return_nothing, test/test_jit.py::TestHooks::test_submodule_multiple_hooks_multiple_inputs, test/test_jit.py::TestHooks::test_submodule_multiple_hooks_single_input, test/test_jit.py::TestHooks::test_submodule_no_forward_input, test/test_jit.py::TestHooks::test_submodule_same_hook_repeated, test/test_jit.py::TestHooks::test_wrong_hook_signatures, test/test_jit.py::TestHooks::test_wrong_pre_hook_signatures, test/test_jit.py::TestWarn::test_warn, test/test_jit.py::TestWarn::test_warn_multiple_calls_multiple_warnings, test/test_jit.py::TestWarn::test_warn_multiple_calls_same_func_diff_stack, test/test_jit.py::TestWarn::test_warn_once_per_func, test/test_jit.py::TestWarn::test_warn_once_per_func_in_loop, test/test_jit.py::TestWarn::test_warn_only_once, test/test_jit.py::TestWarn::test_warn_only_once_in_loop_func, test/test_jit.py::TestIsinstance::test_bool, test/test_jit.py::TestIsinstance::test_dict, test/test_jit.py::TestIsinstance::test_dict_nested, test/test_jit.py::TestIsinstance::test_dict_no_contained_type, test/test_jit.py::TestIsinstance::test_dict_tensor, test/test_jit.py::TestIsinstance::test_empty_container_special_cases, test/test_jit.py::TestIsinstance::test_empty_container_throws_warning_in_eager, test/test_jit.py::TestIsinstance::test_float, test/test_jit.py::TestIsinstance::test_if_else, test/test_jit.py::TestIsinstance::test_in_if, test/test_jit.py::TestIsinstance::test_in_while_loop, test/test_jit.py::TestIsinstance::test_int, test/test_jit.py::TestIsinstance::test_list, test/test_jit.py::TestIsinstance::test_list_nested, test/test_jit.py::TestIsinstance::test_list_no_contained_type, test/test_jit.py::TestIsinstance::test_list_tensor, test/test_jit.py::TestIsinstance::test_list_tensor_type_true, test/test_jit.py::TestIsinstance::test_nontuple_container_rhs_throws_in_eager, test/test_jit.py::TestIsinstance::test_optional, test/test_jit.py::TestIsinstance::test_optional_nested, test/test_jit.py::TestIsinstance::test_optional_no_contained_type, test/test_jit.py::TestIsinstance::test_optional_none, test/test_jit.py::TestIsinstance::test_tensor_type_false, test/test_jit.py::TestIsinstance::test_tuple, test/test_jit.py::TestIsinstance::test_tuple_nested, test/test_jit.py::TestIsinstance::test_tuple_no_contained_type, test/test_jit.py::TestIsinstance::test_tuple_rhs, test/test_jit.py::TestIsinstance::test_tuple_tensor, test/test_jit.py::TestIsinstance::test_type_refinement, test/test_jit.py::TestPythonBuiltinOP::test_add, test/test_jit.py::TestPythonBuiltinOP::test_adv_indexing_list, test/test_jit.py::TestPythonBuiltinOP::test_advancedindex, test/test_jit.py::TestPythonBuiltinOP::test_gather, test/test_jit.py::TestPythonBuiltinOP::test_index, test/test_jit.py::TestPythonBuiltinOP::test_index_ellipses, test/test_jit.py::TestPythonBuiltinOP::test_inf, test/test_jit.py::TestPythonBuiltinOP::test_matmul_py3, test/test_jit.py::TestPythonBuiltinOP::test_mul, test/test_jit.py::TestPythonBuiltinOP::test_pow, test/test_jit.py::TestPythonBuiltinOP::test_random, test/test_jit.py::TestPythonBuiltinOP::test_slice, test/test_jit.py::TestPythonBuiltinOP::test_stepped_tuple_slicing, test/test_jit.py::TestPythonBuiltinOP::test_str_to_float, test/test_jit.py::TestPythonBuiltinOP::test_triple, test/test_jit.py::TestTyping::test_bool_list_io, test/test_jit.py::TestTyping::test_dict_comprehension, test/test_jit.py::TestTyping::test_dict_comprehension_scope, test/test_jit.py::TestTyping::test_dict_comprehension_with_type_annotation, test/test_jit.py::TestTyping::test_dict_in_not_in, test/test_jit.py::TestTyping::test_dict_invalid_annotations, test/test_jit.py::TestTyping::test_dict_type_refinement_annotation_key_mismatch, test/test_jit.py::TestTyping::test_dict_type_refinement_annotation_value_mismatch, test/test_jit.py::TestTyping::test_for_in_dict, test/test_jit.py::TestTyping::test_for_in_string, test/test_jit.py::TestTyping::test_for_tuple_assign, test/test_jit.py::TestTyping::test_for_tuple_unpack, test/test_jit.py::TestTyping::test_inherited_annotations_python_310, test/test_jit.py::TestTyping::test_list_io, test/test_jit.py::TestTyping::test_list_iterables, test/test_jit.py::TestTyping::test_list_sum, test/test_jit.py::TestTyping::test_list_type_refinement_annotation_element_mismatch, test/test_jit.py::TestTyping::test_list_unification, test/test_jit.py::TestTyping::test_multiple_assign, test/test_jit.py::TestTyping::test_namedtuple_error_source_attribution, test/test_jit.py::TestTyping::test_namedtuple_good_error, test/test_jit.py::TestTyping::test_namedtuple_py2, test/test_jit.py::TestTyping::test_namedtuple_redefine, test/test_jit.py::TestTyping::test_nested_list, test/test_jit.py::TestTyping::test_opt_opt_refinement, test/test_jit.py::TestTyping::test_optional_conversion, test/test_jit.py::TestTyping::test_optional_refinement, test/test_jit.py::TestTyping::test_optional_tuple, test/test_jit.py::TestTyping::test_singleton_tuple_unpack, test/test_jit.py::TestTyping::test_sum_list_diff_elms, test/test_jit.py::TestTyping::test_sum_list_empty, test/test_jit.py::TestTyping::test_sum_list_literal, test/test_jit.py::TestTyping::test_sum_list_one, test/test_jit.py::TestTyping::test_sum_list_wrong_type, test/test_jit.py::TestTyping::test_tuple_assignments, test/test_jit.py::TestTyping::test_tuple_create_return, test/test_jit.py::TestTyping::test_tuple_io, test/test_jit.py::TestTyping::test_tuple_keyword, test/test_jit.py::TestTyping::test_tuple_specialization, test/test_jit.py::TestHash::test_hash_bool, test/test_jit.py::TestHash::test_hash_device, test/test_jit.py::TestHash::test_hash_float, test/test_jit.py::TestHash::test_hash_int, test/test_jit.py::TestHash::test_hash_none, test/test_jit.py::TestHash::test_hash_string, test/test_jit.py::TestHash::test_hash_tensor, test/test_jit.py::TestHash::test_hash_tuple, test/test_jit.py::TestHash::test_hash_tuple_nested_unhashable_type, test/test_jit.py::TestComplex::test_binary_op_complex_tensor, test/test_jit.py::TestComplex::test_comparison_ops, test/test_jit.py::TestComplex::test_complex_constants_and_ops, test/test_jit.py::TestComplex::test_complex_constructor, test/test_jit.py::TestComplex::test_complex_list_sum, test/test_jit.py::TestComplex::test_complex_parse, test/test_jit.py::TestComplex::test_complexdict, test/test_jit.py::TestComplex::test_complexlist, test/test_jit.py::TestComplex::test_div, test/test_jit.py::TestComplex::test_infj_nanj_pickle, test/test_jit.py::TestComplex::test_pickle, test/test_jit.py::TestComplex::test_script, test/test_jit.py::TestComplex::test_tensor_attributes, test/test_jit.py::TestComplex::test_torch_complex_constructor_with_tensor, test/test_jit.py::TestJitUtils::test_checkscriptassertraisesregex, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_hybrid, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_keyword_only, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_positional_only, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_positional_or_keyword, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_var_keyword, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_var_positional, test/test_jit.py::TestJitUtils::test_no_tracer_warn_context_manager, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_class_level_annotation_and_init_annotation, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_class_level_annotation_only, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_class_level_jit_annotation, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_dict, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_dict_lowercase, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_list, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_list_lowercase, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_optional, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_tensor, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_falsy_base_type, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_nonempty_container, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_attribute, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_dict, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_dict_lowercase, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_list, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_list_lowercase, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_optional, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_torch_jit_import, test/test_jit.py::TestTypesAndAnnotation::test_annotate_outside_init, test/test_jit.py::TestTypesAndAnnotation::test_bad_types, test/test_jit.py::TestTypesAndAnnotation::test_ignore_with_types, test/test_jit.py::TestTypesAndAnnotation::test_ignoring_fn_with_nonscriptable_types, test/test_jit.py::TestTypesAndAnnotation::test_ignoring_module_attributes, test/test_jit.py::TestTypesAndAnnotation::test_inferred_type_error_message, test/test_jit.py::TestTypesAndAnnotation::test_mismatched_annotation, test/test_jit.py::TestTypesAndAnnotation::test_optional_no_element_type_annotation, test/test_jit.py::TestTypesAndAnnotation::test_parser_bug, test/test_jit.py::TestTypesAndAnnotation::test_pep585_type, test/test_jit.py::TestTypesAndAnnotation::test_python_callable, test/test_jit.py::TestTypesAndAnnotation::test_reannotate, test/test_jit.py::TestTypesAndAnnotation::test_tuple_no_element_type_annotation, test/test_jit.py::TestTypesAndAnnotation::test_type_annotate_py3, test/test_jit.py::TestTypesAndAnnotation::test_types_as_values, test/test_jit.py::TestTypesAndAnnotation::test_unimported_type_resolution, test/test_jit.py::TestMisc::test_broadcasting_list, test/test_jit.py::TestMisc::test_export_opnames_interface, test/test_jit.py::TestMisc::test_future_isinstance, test/test_jit.py::TestMisc::test_hacked_twin, test/test_jit.py::TestMisc::test_if_returning_any, test/test_jit.py::TestMisc::test_jit_get_operation_order, test/test_jit.py::TestMisc::test_joined_str, test/test_jit.py::TestMisc::test_kwarg_support, test/test_jit.py::TestMisc::test_legacy_tensor_constructor, test/test_jit.py::TestMisc::test_list_literal_infer, test/test_jit.py::TestMisc::test_math_inf, test/test_jit.py::TestMisc::test_parse_ir_annotate, test/test_jit.py::TestMisc::test_parse_ir_single_element_tensor_negative, test/test_jit.py::TestMisc::test_parse_ir_single_element_tensor_positive, test/test_jit.py::TestMisc::test_pow_multiple_dtype, test/test_jit.py::TestMisc::test_script_many_decorators, test/test_jit.py::TestMisc::test_str_refine_any, test/test_jit.py::TestMisc::test_subexpression_Dict_int_Future, test/test_jit.py::TestMisc::test_subexpression_Future_annotate, test/test_jit.py::TestMisc::test_subexpression_List_Future, test/test_jit.py::TestMisc::test_subexpression_Optional, test/test_jit.py::TestMisc::test_subexpression_Tuple_int_int_Future, test/test_jit.py::TestMisc::test_tuple_subscripted_assign, test/test_jit.py::TestMisc::test_unsafe_hacked_twin, test/test_jit.py::TestUpgraders::test_add_value_to_version_map, test/test_jit.py::TestUpgraders::test_aten_div_scalar_at_3, test/test_jit.py::TestUpgraders::test_aten_div_tensor_at_3, test/test_jit.py::TestUpgraders::test_aten_div_tensor_out_at_3, test/test_jit.py::TestUpgraders::test_aten_full_at_4, test/test_jit.py::TestUpgraders::test_aten_full_other_variants, test/test_jit.py::TestUpgraders::test_aten_full_out_at_4, 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test/test_jit.py::TestScript::test_script_forward_method_replacement, test/test_jit.py::TestScript::test_script_get_device_cuda, test/test_jit.py::TestScript::test_script_get_tracing_state, test/test_jit.py::TestScript::test_script_is_tracing, test/test_jit.py::TestScript::test_script_kwargs_fn_call, test/test_jit.py::TestScript::test_script_method_docstring, test/test_jit.py::TestScript::test_script_method_torch_function_overload, test/test_jit.py::TestScript::test_script_module, test/test_jit.py::TestScript::test_script_module_call_noscript, test/test_jit.py::TestScript::test_script_module_const, test/test_jit.py::TestScript::test_script_module_const_submodule_fail, test/test_jit.py::TestScript::test_script_module_export_blocks, test/test_jit.py::TestScript::test_script_module_export_shared_storage, test/test_jit.py::TestScript::test_script_module_export_submodule, test/test_jit.py::TestScript::test_script_module_export_tensor_cuda, 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test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_legacy_enum, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_Bilinear, test/test_jit.py::TestJitGeneratedModule::test_nn_CELU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_circular_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_groups, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad1, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad1size1, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad2size1, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad_same, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad_same2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad_same_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad_valid, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_reflect_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_replicate_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_stride, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_zero_batch, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_zeros_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_circular_stride2_pad2, 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test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_replicate_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_strided, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_zero_batch, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_zeros_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_1x1x1_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_circular_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_dilated_strided, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_groups, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_pad_same, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_pad_same_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_pad_valid, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_replicate_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_stride, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_stride_padding, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_zero_batch, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_zeros_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose1d, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose1d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose1d_groups, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose1d_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d_groups, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose3d, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose3d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_CosineEmbeddingLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_CosineEmbeddingLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_CosineEmbeddingLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_CrossMapLRN2d, test/test_jit.py::TestJitGeneratedModule::test_nn_ELU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Embedding, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_discontiguous, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_max, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_max_padding_idx, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_mean_padding_idx, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_sparse, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_sum_padding_idx, test/test_jit.py::TestJitGeneratedModule::test_nn_Embedding_discontiguous, test/test_jit.py::TestJitGeneratedModule::test_nn_Embedding_sparse, test/test_jit.py::TestJitGeneratedModule::test_nn_Flatten, test/test_jit.py::TestJitGeneratedModule::test_nn_Flatten_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold_int_input, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold_no_batch_dim_input, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold_no_batch_dim_int_input, test/test_jit.py::TestJitGeneratedModule::test_nn_GELU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_GLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_GRUCell, 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test/test_jit.py::TestJitGeneratedModule::test_nn_HuberLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_reduce_log_target, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_reduce_scalar_log_target, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_with_log_target_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_with_target_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_reduce_complex, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_LSTMCell, test/test_jit.py::TestJitGeneratedModule::test_nn_LayerNorm_3d_no_affine_large_feature, test/test_jit.py::TestJitGeneratedModule::test_nn_LeakyReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Linear, test/test_jit.py::TestJitGeneratedModule::test_nn_Linear_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Linear_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_LogSigmoid_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_MarginRankingLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_MarginRankingLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_MarginRankingLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_Mish_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_0d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_1d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_index_neg, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_weights_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_1d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_margin_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_p_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_weights_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiheadAttention, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss2d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss2d_no_reduce_ignore_index, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss2d_no_reduce_weights, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLossNd_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLossNd_no_reduce_ignore_index, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLossNd_no_reduce_weights, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_ignore_index, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_weights, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_weights_ignore_index, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_weights_ignore_index_neg, test/test_jit.py::TestJitGeneratedModule::test_nn_PReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_broadcast_lhs, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_broadcast_rhs, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_with_non_default_args, test/test_jit.py::TestJitGeneratedModule::test_nn_PixelShuffle, test/test_jit.py::TestJitGeneratedModule::test_nn_PixelUnshuffle, test/test_jit.py::TestJitGeneratedModule::test_nn_PoissonNLLLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_PoissonNLLLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_PoissonNLLLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_PoissonNLLLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_RNNCell, test/test_jit.py::TestJitGeneratedModule::test_nn_RReLU, test/test_jit.py::TestJitGeneratedModule::test_nn_RReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_RReLU_with_up_down, test/test_jit.py::TestJitGeneratedModule::test_nn_RReLU_with_up_down_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_ReLU6_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_ReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_ReplicationPad3d, test/test_jit.py::TestJitGeneratedModule::test_nn_ReplicationPad3d_complex, test/test_jit.py::TestJitGeneratedModule::test_nn_ReplicationPad3d_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_SELU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_SiLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Sigmoid_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_beta, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_zero_beta, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_Softplus_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Softshrink_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Softsign_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Tanh_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Tanhshrink_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Threshold_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Transformer, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerDecoderLayer_gelu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerDecoderLayer_relu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerEncoderLayer_gelu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerEncoderLayer_relu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_Transformer_multilayer_coder, test/test_jit.py::TestJitGeneratedModule::test_nn_TripletMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_TripletMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_TripletMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_Unflatten_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Unfold, test/test_jit.py::TestJitGeneratedModule::test_nn_Unfold_int_input, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_2d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_scale_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_scale_tuple_shared_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_scale_tuple_skewed_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_scale_tuple_skewed_2d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_tuple_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_tuple_2d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_2d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_scale_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_scale_tuple_shared_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_scale_tuple_skewed_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_scale_tuple_skewed_2d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_tuple_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_tuple_2d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_1d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_1d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_scale_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_scale_1d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_tuple_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_1d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_2d_launch_configs, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_2d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_3d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_scale_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_scale_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_scale_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_tuple_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_tuple_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_tuple_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_3d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_scale_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_scale_3d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_tuple_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_tuple_3d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_dim0, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_dim3, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_lastdim, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_spatial, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_spatial_special, test/test_jit.py::TestJitGeneratedModule::test_nn_multimarginloss_1d_input_0d_target_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_functional_dim0, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_functional_dim3, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_functional_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_lastdim, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_lastdim_dtype, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_spatial, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_spatial_dtype, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_spatial_special, test/test_jit.py::TestProducerVersion::test_version
2025-07-17T07:53:16.4404990Z 
2025-07-17T07:53:18.5530910Z Running inductor/test_cpu_repro 1/1 ... [2025-07-17 07:53:18.552949]
2025-07-17T07:53:18.5531220Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:53:18.5533880Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'inductor/test_cpu_repro.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:53:18.553286]
2025-07-17T07:53:21.2157830Z 
2025-07-17T07:53:21.2158370Z inductor/test_cpu_repro 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_repro_1.1_75de5ee90f7de6aa_.log
2025-07-17T07:53:21.2158810Z 
2025-07-17T07:53:23.3443000Z Running optim/test_swa_utils 1/1 ... [2025-07-17 07:53:23.344123]
2025-07-17T07:53:23.3443360Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:53:23.3445290Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'optim/test_swa_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:53:23.344410]
2025-07-17T07:53:25.3245690Z 
2025-07-17T07:53:25.3246900Z optim/test_swa_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/optim.test_swa_utils_1.1_3b9216c60c95faf5_.log
2025-07-17T07:53:25.3247340Z 
2025-07-17T07:53:27.3511980Z Running test_rename_privateuse1_to_existing_device 1/1 ... [2025-07-17 07:53:27.351086]
2025-07-17T07:53:27.3512350Z SCRIBE_GRAPHQL_ACCESS_TOKEN is NOT set
2025-07-17T07:53:27.3514930Z Executing ['/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/python', '-bb', 'test_rename_privateuse1_to_existing_device.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-07-17 07:53:27.351390]
2025-07-17T07:53:29.5607810Z 
2025-07-17T07:53:29.5608620Z test_rename_privateuse1_to_existing_device 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_rename_privateuse1_to_existing_device_1.1_ac1a27c111024b66_.log
2025-07-17T07:53:29.5610040Z Running 1 items in this shard: test/test_rename_privateuse1_to_existing_device.py::TestRenamePrivateuseoneToExistingBackend::test_external_module_register_with_existing_backend
2025-07-17T07:53:29.5610540Z 
2025-07-17T07:54:06.5172390Z 
2025-07-17T07:54:06.5173040Z test_optim 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_optim_1.1_8ee1281075475115_.log
2025-07-17T07:54:06.5633850Z Running 1713 items in this shard: test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_T_cur_reset, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr1_T_mult_1, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr1_T_mult_2, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr1_T_mult_4, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr2, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr3, test/test_optim.py::TestLRScheduler::test_CosineAnnealingWarmRestarts_lr_state_dict, test/test_optim.py::TestLRScheduler::test_add_param_group_does_not_break_reduce_lr_on_plateau_min_lr_list, test/test_optim.py::TestLRScheduler::test_add_param_group_does_not_break_reduce_lr_on_plateau_min_lr_scalar, test/test_optim.py::TestLRScheduler::test_add_param_group_errors_reduce_lr_on_plateau, test/test_optim.py::TestLRScheduler::test_chained_lr1, test/test_optim.py::TestLRScheduler::test_chained_lr2, test/test_optim.py::TestLRScheduler::test_chained_lr2_get_last_lr_before_step, test/test_optim.py::TestLRScheduler::test_chained_lr3, test/test_optim.py::TestLRScheduler::test_chained_lr4, test/test_optim.py::TestLRScheduler::test_chained_lr5, test/test_optim.py::TestLRScheduler::test_closed_form_constantlr, test/test_optim.py::TestLRScheduler::test_closed_form_cos_anneal_lr, test/test_optim.py::TestLRScheduler::test_closed_form_exp_lr, test/test_optim.py::TestLRScheduler::test_closed_form_linearlr, test/test_optim.py::TestLRScheduler::test_closed_form_multi_step_lr, test/test_optim.py::TestLRScheduler::test_closed_form_poly_lr, test/test_optim.py::TestLRScheduler::test_closed_form_step_lr, test/test_optim.py::TestLRScheduler::test_compound_cosanneal_and_exp_lr, test/test_optim.py::TestLRScheduler::test_compound_cosanneal_and_linearlr, test/test_optim.py::TestLRScheduler::test_compound_cosanneal_and_multistep_lr, test/test_optim.py::TestLRScheduler::test_compound_cosanneal_and_step_lr, test/test_optim.py::TestLRScheduler::test_compound_exp_and_linearlr, test/test_optim.py::TestLRScheduler::test_compound_exp_and_multistep_lr, test/test_optim.py::TestLRScheduler::test_compound_linearlr_and_multistep_lr, test/test_optim.py::TestLRScheduler::test_compound_reduce_lr_on_plateau1, test/test_optim.py::TestLRScheduler::test_compound_reduce_lr_on_plateau2, test/test_optim.py::TestLRScheduler::test_compound_reduce_lr_on_plateau3, test/test_optim.py::TestLRScheduler::test_compound_reduce_lr_on_plateau4, test/test_optim.py::TestLRScheduler::test_compound_reduce_lr_on_plateau5, test/test_optim.py::TestLRScheduler::test_compound_step_and_constantlr, test/test_optim.py::TestLRScheduler::test_compound_step_and_exp_lr, test/test_optim.py::TestLRScheduler::test_compound_step_and_multistep_lr, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass0, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass1, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass2, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass3, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass4, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass5, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass6, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass7, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass8, test/test_optim.py::TestLRScheduler::test_constant_initial_lr_LRClass9, test/test_optim.py::TestLRScheduler::test_constant_initial_params_cyclelr, test/test_optim.py::TestLRScheduler::test_constant_initial_params_onecyclelr, test/test_optim.py::TestLRScheduler::test_constant_initial_params_swalr, test/test_optim.py::TestLRScheduler::test_constantlr, test/test_optim.py::TestLRScheduler::test_constantlr_is_constant_for_constant_epoch, test/test_optim.py::TestLRScheduler::test_constantlr_with_epoch, test/test_optim.py::TestLRScheduler::test_cos_anneal_lr, test/test_optim.py::TestLRScheduler::test_cos_anneal_lr_continue, test/test_optim.py::TestLRScheduler::test_cosine_lr_state_dict, test/test_optim.py::TestLRScheduler::test_cosine_then_cyclic, test/test_optim.py::TestLRScheduler::test_cycle_lr_cycle_momentum_fail_with_momentumless_optimizer, test/test_optim.py::TestLRScheduler::test_cycle_lr_cycle_momentum_with_beta1_optimizer, test/test_optim.py::TestLRScheduler::test_cycle_lr_exp_range_mode, test/test_optim.py::TestLRScheduler::test_cycle_lr_exp_range_mode_one_lr, test/test_optim.py::TestLRScheduler::test_cycle_lr_exp_range_mode_step_size_up_down, test/test_optim.py::TestLRScheduler::test_cycle_lr_invalid_mode, test/test_optim.py::TestLRScheduler::test_cycle_lr_removed_after_out_of_scope, test/test_optim.py::TestLRScheduler::test_cycle_lr_scale_fn_restored_from_state_dict, test/test_optim.py::TestLRScheduler::test_cycle_lr_state_dict_picklable, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular2_mode, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular2_mode_one_lr, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular2_mode_step_size_up_down, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular_mode, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular_mode_one_lr, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular_mode_one_lr_no_momentum, test/test_optim.py::TestLRScheduler::test_cycle_lr_triangular_mode_step_size_up_down, test/test_optim.py::TestLRScheduler::test_cycle_lr_with_adam, test/test_optim.py::TestLRScheduler::test_cycle_lr_with_momentumless_optimizer, test/test_optim.py::TestLRScheduler::test_error_when_getlr_has_epoch, test/test_optim.py::TestLRScheduler::test_exp_lr, test/test_optim.py::TestLRScheduler::test_exp_step_lr_state_dict, test/test_optim.py::TestLRScheduler::test_exponential_lr_is_constant_for_constant_epoch, test/test_optim.py::TestLRScheduler::test_get_last_lr_constantlr, test/test_optim.py::TestLRScheduler::test_get_last_lr_linearlr, test/test_optim.py::TestLRScheduler::test_get_last_lr_multi_step_lr, test/test_optim.py::TestLRScheduler::test_get_last_lr_sequentiallr, test/test_optim.py::TestLRScheduler::test_get_last_lr_step_lr, test/test_optim.py::TestLRScheduler::test_lambda_lr, test/test_optim.py::TestLRScheduler::test_lambda_lr_state_dict_fn, test/test_optim.py::TestLRScheduler::test_lambda_lr_state_dict_obj, test/test_optim.py::TestLRScheduler::test_linear_linearlr_is_constant_for_constant_epoch, test/test_optim.py::TestLRScheduler::test_linearlr, test/test_optim.py::TestLRScheduler::test_linearlr_start_factor_limits1, test/test_optim.py::TestLRScheduler::test_linearlr_start_factor_limits2, test/test_optim.py::TestLRScheduler::test_linearlr_with_epoch, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass0, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass1, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass10, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass11, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass12, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass2, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass3, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass4, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass5, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass6, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass7, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass8, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_LRClass9, test/test_optim.py::TestLRScheduler::test_lr_scheduler_checkpoint_on_plateau, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass0_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass0_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass10_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass10_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass11_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass11_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass12_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass12_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass13_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass13_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass14_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass14_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass1_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass1_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass2_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass2_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass3_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass3_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass4_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass4_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass5_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass5_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass6_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass6_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass7_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass7_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass8_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass8_weights_only_True, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass9_weights_only_False, test/test_optim.py::TestLRScheduler::test_lr_scheduler_state_dict_load_LRClass9_weights_only_True, test/test_optim.py::TestLRScheduler::test_multi_step_lr, test/test_optim.py::TestLRScheduler::test_multi_step_lr_state_dict, test/test_optim.py::TestLRScheduler::test_multi_step_lr_with_epoch, test/test_optim.py::TestLRScheduler::test_multiplicative_lr, test/test_optim.py::TestLRScheduler::test_multiplicative_lr_with_lr_lambda, test/test_optim.py::TestLRScheduler::test_new_pattern_no_warning, test/test_optim.py::TestLRScheduler::test_new_pattern_no_warning_with_arg, test/test_optim.py::TestLRScheduler::test_new_pattern_no_warning_with_overridden_optim_step, test/test_optim.py::TestLRScheduler::test_no_cyclic_references, test/test_optim.py::TestLRScheduler::test_no_cyclic_references_in_step, test/test_optim.py::TestLRScheduler::test_old_pattern_warning, test/test_optim.py::TestLRScheduler::test_old_pattern_warning_resuming, test/test_optim.py::TestLRScheduler::test_old_pattern_warning_resuming_with_arg, test/test_optim.py::TestLRScheduler::test_old_pattern_warning_with_arg, test/test_optim.py::TestLRScheduler::test_old_pattern_warning_with_overridden_optim_step, test/test_optim.py::TestLRScheduler::test_onecycle_lr_cannot_calculate_total_steps, test/test_optim.py::TestLRScheduler::test_onecycle_lr_cosine_annealing, test/test_optim.py::TestLRScheduler::test_onecycle_lr_invalid_anneal_strategy, test/test_optim.py::TestLRScheduler::test_onecycle_lr_invalid_pct_start, test/test_optim.py::TestLRScheduler::test_onecycle_lr_legacy_state_dict, test/test_optim.py::TestLRScheduler::test_onecycle_lr_linear_annealing, test/test_optim.py::TestLRScheduler::test_onecycle_lr_linear_annealing_three_phases, test/test_optim.py::TestLRScheduler::test_poly_lr, test/test_optim.py::TestLRScheduler::test_polynomial_lr_is_constant_for_constant_epoch, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau1, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau2, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau3, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau4, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau5, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau6, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau7, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau8, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau_get_last_lr_before_step, test/test_optim.py::TestLRScheduler::test_reduce_lr_on_plateau_state_dict, test/test_optim.py::TestLRScheduler::test_sequentiallr1, test/test_optim.py::TestLRScheduler::test_sequentiallr2, test/test_optim.py::TestLRScheduler::test_sequentiallr3, test/test_optim.py::TestLRScheduler::test_sequentiallr4, test/test_optim.py::TestLRScheduler::test_sequentiallr5, test/test_optim.py::TestLRScheduler::test_step_lr, test/test_optim.py::TestLRScheduler::test_step_lr_is_constant_for_constant_epoch, test/test_optim.py::TestLRScheduler::test_step_lr_state_dict, test/test_optim.py::TestLRScheduler::test_swa_lr_state_dict, test/test_optim.py::TestLRScheduler::test_swalr_cosine_anneal_after_multiplicative, test/test_optim.py::TestLRScheduler::test_swalr_hypers, test/test_optim.py::TestLRScheduler::test_swalr_linear_anneal_after_multiplicative, test/test_optim.py::TestLRScheduler::test_swalr_no_anneal, test/test_optim.py::TestDifferentiableOptimizer::test_adadelta, test/test_optim.py::TestDifferentiableOptimizer::test_adagrad, test/test_optim.py::TestDifferentiableOptimizer::test_adam, test/test_optim.py::TestDifferentiableOptimizer::test_adam_differentiable_all_hyperparams, test/test_optim.py::TestDifferentiableOptimizer::test_adam_differentiable_betas, test/test_optim.py::TestDifferentiableOptimizer::test_adam_differentiable_lr, test/test_optim.py::TestDifferentiableOptimizer::test_adam_differentiable_weight_decay, test/test_optim.py::TestDifferentiableOptimizer::test_adamax, test/test_optim.py::TestDifferentiableOptimizer::test_adamw, test/test_optim.py::TestDifferentiableOptimizer::test_adamw_differentiable_all_hyperparams, test/test_optim.py::TestDifferentiableOptimizer::test_adamw_differentiable_betas, test/test_optim.py::TestDifferentiableOptimizer::test_adamw_differentiable_lr, test/test_optim.py::TestDifferentiableOptimizer::test_adamw_differentiable_weight_decay, test/test_optim.py::TestDifferentiableOptimizer::test_asgd, test/test_optim.py::TestDifferentiableOptimizer::test_differentiable_lr, test/test_optim.py::TestDifferentiableOptimizer::test_differentiable_weight_decay, test/test_optim.py::TestDifferentiableOptimizer::test_differentiable_weight_decay_and_lr, test/test_optim.py::TestDifferentiableOptimizer::test_nadam, test/test_optim.py::TestDifferentiableOptimizer::test_radam, test/test_optim.py::TestDifferentiableOptimizer::test_rmsprop, test/test_optim.py::TestDifferentiableOptimizer::test_rprop, test/test_optim.py::TestDifferentiableOptimizer::test_sgd, test/test_optim.py::TestSWAUtils::test_averaged_model_all_devices_ema_False, test/test_optim.py::TestSWAUtils::test_averaged_model_all_devices_ema_True, test/test_optim.py::TestSWAUtils::test_averaged_model_default_avg_fn_picklable, test/test_optim.py::TestSWAUtils::test_averaged_model_exponential_use_multi_avg_fn_False_use_buffers_False, test/test_optim.py::TestSWAUtils::test_averaged_model_exponential_use_multi_avg_fn_False_use_buffers_True, test/test_optim.py::TestSWAUtils::test_averaged_model_exponential_use_multi_avg_fn_True_use_buffers_False, test/test_optim.py::TestSWAUtils::test_averaged_model_exponential_use_multi_avg_fn_True_use_buffers_True, test/test_optim.py::TestSWAUtils::test_averaged_model_mixed_device_ema_False, test/test_optim.py::TestSWAUtils::test_averaged_model_mixed_device_ema_True, 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test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_Adafactor_cpu_float32, 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test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_False_is_named_optim1_True_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Adafactor_cpu_float32, 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test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_non_empty_state_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optim_infos_do_not_specify_global_cliquey_kwargs_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_optimizer_can_be_printed_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_group_with_lrscheduler_goes_right_direction_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_lr_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_param_groups_weight_decay_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_peak_memory_foreach_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_rosenbrock_sparse_with_lrsched_False_Adagrad_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_rosenbrock_sparse_with_lrsched_False_SGD_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_rosenbrock_sparse_with_lrsched_False_SparseAdam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_rosenbrock_sparse_with_lrsched_True_Adagrad_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_rosenbrock_sparse_with_lrsched_True_SGD_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_rosenbrock_sparse_with_lrsched_True_SparseAdam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_False_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_save_load_equality_with_weights_only_is_named_optim_True_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_second_order_optims_return_consistent_types_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_ASGD_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Adadelta_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Adafactor_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Adagrad_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_AdamW_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Adam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Adamax_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_NAdam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_RAdam_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_RMSprop_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_Rprop_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_set_default_dtype_works_with_foreach_SGD_cpu_float64, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_SparseAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_ASGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adadelta_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adafactor_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adagrad_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_AdamW_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adamax_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_LBFGS_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_NAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_RAdam_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_RMSprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Rprop_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_SGD_cpu_float32, test/test_optim.py::TestOptimRenewedCPU::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_SparseAdam_cpu_float32, 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test/test_optim.py::TestOptimRenewedMPS::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_can_load_from_to_named_state_dict_is_named_optim0_True_is_named_optim1_False_RAdam_mps_float32, 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test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_load_state_dict_pre_post_hook_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_foreach_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_foreach_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_foreach_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_foreach_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_foreach_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_foreach_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_foreach_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_foreach_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_foreach_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_foreach_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_foreach_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_foreach_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_fused_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_fused_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_fused_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_fused_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_fused_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_fused_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_fused_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_fused_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_fused_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_fused_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_fused_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_mixed_device_dtype_impl_fused_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_non_empty_state_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optim_infos_do_not_specify_global_cliquey_kwargs_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_optimizer_can_be_printed_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_group_with_lrscheduler_goes_right_direction_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_lr_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_param_groups_weight_decay_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_peak_memory_foreach_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_peak_memory_foreach_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_peak_memory_foreach_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_peak_memory_foreach_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_peak_memory_foreach_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_peak_memory_foreach_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_peak_memory_foreach_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_peak_memory_foreach_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_peak_memory_foreach_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_peak_memory_foreach_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_peak_memory_foreach_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_peak_memory_foreach_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_rosenbrock_sparse_with_lrsched_False_Adagrad_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_rosenbrock_sparse_with_lrsched_False_SGD_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_rosenbrock_sparse_with_lrsched_False_SparseAdam_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_rosenbrock_sparse_with_lrsched_True_Adagrad_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_rosenbrock_sparse_with_lrsched_True_SGD_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_rosenbrock_sparse_with_lrsched_True_SparseAdam_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_False_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_save_load_equality_with_weights_only_is_named_optim_True_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_second_order_optims_return_consistent_types_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_set_default_dtype_works_with_foreach_ASGD_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_set_default_dtype_works_with_foreach_Adadelta_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_set_default_dtype_works_with_foreach_Adafactor_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_set_default_dtype_works_with_foreach_Adagrad_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_set_default_dtype_works_with_foreach_AdamW_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_set_default_dtype_works_with_foreach_Adam_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_set_default_dtype_works_with_foreach_Adamax_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_set_default_dtype_works_with_foreach_NAdam_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_set_default_dtype_works_with_foreach_RAdam_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_set_default_dtype_works_with_foreach_RMSprop_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_set_default_dtype_works_with_foreach_Rprop_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_set_default_dtype_works_with_foreach_SGD_mps_float64, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_False_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_False_is_named_optim1_True_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_False_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_deterministic_is_named_optim0_True_is_named_optim1_True_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_post_hook_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_hook_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_pre_post_hook_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_state_dict_with_cuda_params_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_AdamW_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_Adam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_Adamax_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_LBFGS_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_NAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_RAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_RMSprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_Rprop_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_SGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_all_hooks_SparseAdam_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_is_noop_for_zero_grads_ASGD_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_is_noop_for_zero_grads_Adadelta_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_is_noop_for_zero_grads_Adafactor_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_is_noop_for_zero_grads_Adagrad_mps_float32, test/test_optim.py::TestOptimRenewedMPS::test_step_is_noop_for_zero_grads_AdamW_mps_float32, 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2025-07-17T07:54:06.6078840Z 
2025-07-17T07:58:22.9884410Z 
2025-07-17T07:58:22.9884900Z test_modules 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_modules_1.1_6d0b7fe65662be19_.log
2025-07-17T07:58:23.1385130Z Running 6841 items in this shard: test/test_modules.py::TestModuleCPU::test_check_inplace_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_check_inplace_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_AdaptiveAvgPool1d_cpu_float32, 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test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_cpu_gpu_parity_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_device_ctx_init_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_errors_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_errors_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_factory_kwargs_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_forward_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_forward_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_forward_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_forward_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_forward_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_grad_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_gradgrad_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BatchNorm1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BatchNorm1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BatchNorm2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BatchNorm2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BatchNorm3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_BatchNorm3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GRU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GRU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_InstanceNorm1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_InstanceNorm1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_InstanceNorm2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_InstanceNorm2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_InstanceNorm3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_InstanceNorm3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LSTM_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LSTM_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiheadAttention_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_MultiheadAttention_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_RNN_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_RNN_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_TransformerEncoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_TransformerEncoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_TransformerEncoder_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_TransformerEncoder_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_if_train_and_eval_modes_differ_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_memory_format_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_multiple_device_transfer_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_CrossEntropyLoss_cpu_float32, 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test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_non_contiguous_tensors_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_repr_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_repr_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_repr_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_repr_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_repr_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveAvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveAvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveAvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveAvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveAvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveAvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveMaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveMaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AdaptiveMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AvgPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AvgPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AvgPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AvgPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_AvgPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_AvgPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BCELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BCELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BCEWithLogitsLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BCEWithLogitsLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_BatchNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Bilinear_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Bilinear_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_CELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CTCLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_CTCLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CircularPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_CircularPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CircularPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_CircularPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CircularPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_CircularPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConstantPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConstantPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConstantPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConstantPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConstantPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConstantPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Conv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Conv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Conv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Conv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Conv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Conv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose1d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose1d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose1d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose2d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose2d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose2d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose3d_cpu_complex128, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose3d_cpu_complex32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose3d_cpu_complex64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CosineEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_CosineEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_CrossEntropyLoss_cpu_float16, test/test_modules.py::TestModuleCPU::test_save_load_nn_CrossEntropyLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_CrossEntropyLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Embedding_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Embedding_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_FractionalMaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_FractionalMaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_FractionalMaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_FractionalMaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GRUCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GRUCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GRU_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GRU_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GRU_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GRU_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GaussianNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GaussianNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_GroupNorm_cpu_bfloat16, test/test_modules.py::TestModuleCPU::test_save_load_nn_GroupNorm_cpu_float16, test/test_modules.py::TestModuleCPU::test_save_load_nn_GroupNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_GroupNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Hardshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Hardshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Hardswish_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Hardswish_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Hardtanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Hardtanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_HingeEmbeddingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_HingeEmbeddingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_HuberLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_HuberLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm1d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm1d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm1d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm1d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm2d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm2d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm2d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm2d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm3d_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm3d_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm3d_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_InstanceNorm3d_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_KLDivLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_KLDivLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_L1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_L1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LPPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LPPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LPPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LPPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LPPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LPPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LSTMCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LSTMCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LSTM_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LSTM_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LSTM_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LSTM_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LayerNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LayerNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConv1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConv1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConv2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConv2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConv3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConv3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConvTranspose1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConvTranspose1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConvTranspose2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConvTranspose2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConvTranspose3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LazyConvTranspose3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LeakyReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LeakyReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Linear_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Linear_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LocalResponseNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LocalResponseNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LogSigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LogSigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_LogSoftmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_LogSoftmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MSELoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MSELoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MarginRankingLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MarginRankingLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MaxPool1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MaxPool1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MaxPool2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MaxPool2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MaxPool3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MaxPool3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Mish_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Mish_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiLabelMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiLabelMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiLabelSoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiLabelSoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiheadAttention_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiheadAttention_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiheadAttention_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_MultiheadAttention_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_NLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_NLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_PReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_PReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_PoissonNLLLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_PoissonNLLLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_RMSNorm_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_RMSNorm_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_RNNCell_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_RNNCell_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_RNN_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_RNN_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_RNN_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_RNN_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReLU6_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReLU6_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReflectionPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReflectionPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReflectionPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReflectionPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReflectionPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReflectionPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReplicationPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReplicationPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReplicationPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReplicationPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReplicationPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ReplicationPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_SELU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_SELU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_SiLU_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_SiLU_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Sigmoid_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Sigmoid_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_SmoothL1Loss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_SmoothL1Loss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_SoftMarginLoss_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_SoftMarginLoss_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softmax2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softmax2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softmax_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softmax_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softmin_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softmin_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softplus_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softplus_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softsign_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Softsign_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Tanh_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Tanh_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Tanhshrink_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Tanhshrink_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Threshold_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Threshold_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerDecoderLayer_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerDecoderLayer_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoderLayer_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoderLayer_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoderLayer_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoder_eval_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoder_eval_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoder_train_mode_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_TransformerEncoder_train_mode_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_Transformer_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_Transformer_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ZeroPad1d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ZeroPad1d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ZeroPad2d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ZeroPad2d_cpu_float64, test/test_modules.py::TestModuleCPU::test_save_load_nn_ZeroPad3d_cpu_float32, test/test_modules.py::TestModuleCPU::test_save_load_nn_ZeroPad3d_cpu_float64, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveAvgPool1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveAvgPool1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveAvgPool2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveAvgPool2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveAvgPool3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveAvgPool3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveMaxPool1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveMaxPool1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveMaxPool2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveMaxPool2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveMaxPool3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AdaptiveMaxPool3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AvgPool1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AvgPool1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AvgPool2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AvgPool2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AvgPool3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_AvgPool3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BCELoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BCELoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BCEWithLogitsLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BCEWithLogitsLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm1d_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm1d_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm1d_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm1d_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm2d_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm2d_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm2d_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm2d_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm3d_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm3d_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm3d_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_BatchNorm3d_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Bilinear_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Bilinear_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CELU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CELU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CTCLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CTCLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CircularPad1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CircularPad1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CircularPad2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CircularPad2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CircularPad3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CircularPad3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConstantPad1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConstantPad1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConstantPad2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConstantPad2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConstantPad3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConstantPad3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Conv1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Conv1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Conv2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Conv2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Conv3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Conv3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConvTranspose1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConvTranspose1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConvTranspose2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConvTranspose2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConvTranspose3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ConvTranspose3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CosineEmbeddingLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CosineEmbeddingLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CrossEntropyLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_CrossEntropyLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ELU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ELU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Embedding_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Embedding_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_FractionalMaxPool2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_FractionalMaxPool2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_FractionalMaxPool3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_FractionalMaxPool3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GELU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GELU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GLU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GLU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GRUCell_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GRUCell_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GRU_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GRU_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GRU_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GRU_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GaussianNLLLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GaussianNLLLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GroupNorm_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_GroupNorm_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Hardshrink_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Hardshrink_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Hardswish_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Hardswish_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Hardtanh_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Hardtanh_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_HingeEmbeddingLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_HingeEmbeddingLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_HuberLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_HuberLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm1d_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm1d_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm1d_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm1d_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm2d_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm2d_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm2d_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm2d_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm3d_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm3d_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm3d_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_InstanceNorm3d_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_KLDivLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_KLDivLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_L1Loss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_L1Loss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LPPool1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LPPool1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LPPool2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LPPool2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LPPool3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LPPool3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LSTMCell_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LSTMCell_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LSTM_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LSTM_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LSTM_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LSTM_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LayerNorm_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LayerNorm_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LeakyReLU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LeakyReLU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Linear_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Linear_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LocalResponseNorm_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LocalResponseNorm_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LogSigmoid_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LogSigmoid_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LogSoftmax_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_LogSoftmax_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MSELoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MSELoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MarginRankingLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MarginRankingLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MaxPool1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MaxPool1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MaxPool2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MaxPool2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MaxPool3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MaxPool3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Mish_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Mish_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiLabelMarginLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiLabelMarginLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiLabelSoftMarginLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiLabelSoftMarginLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiMarginLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiMarginLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiheadAttention_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiheadAttention_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiheadAttention_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_MultiheadAttention_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_NLLLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_NLLLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_PReLU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_PReLU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_PoissonNLLLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_PoissonNLLLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RMSNorm_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RMSNorm_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RNNCell_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RNNCell_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RNN_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RNN_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RNN_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_RNN_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReLU6_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReLU6_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReLU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReLU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReflectionPad1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReflectionPad1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReflectionPad2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReflectionPad2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReflectionPad3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReflectionPad3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReplicationPad1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReplicationPad1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReplicationPad2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReplicationPad2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReplicationPad3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ReplicationPad3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SELU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SELU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SiLU_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SiLU_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Sigmoid_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Sigmoid_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SmoothL1Loss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SmoothL1Loss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SoftMarginLoss_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_SoftMarginLoss_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softmax2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softmax2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softmax_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softmax_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softmin_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softmin_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softplus_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softplus_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softshrink_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softshrink_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softsign_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Softsign_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Tanh_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Tanh_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Tanhshrink_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Tanhshrink_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Threshold_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Threshold_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerDecoderLayer_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerDecoderLayer_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoderLayer_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoderLayer_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoderLayer_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoderLayer_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoder_eval_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoder_eval_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoder_train_mode_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_TransformerEncoder_train_mode_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Transformer_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_Transformer_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ZeroPad1d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ZeroPad1d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ZeroPad2d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ZeroPad2d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ZeroPad3d_swap_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_empty_nn_ZeroPad3d_swap_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveAvgPool3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AdaptiveMaxPool3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_AvgPool3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCELoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCELoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCELoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCELoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCEWithLogitsLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCEWithLogitsLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCEWithLogitsLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BCEWithLogitsLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm1d_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm2d_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_BatchNorm3d_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Bilinear_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Bilinear_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Bilinear_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Bilinear_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CELU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CELU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CELU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CELU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CTCLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CTCLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CTCLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CTCLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CircularPad3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConstantPad3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Conv3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ConvTranspose3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CosineEmbeddingLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CosineEmbeddingLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CosineEmbeddingLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CosineEmbeddingLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CrossEntropyLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CrossEntropyLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CrossEntropyLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_CrossEntropyLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ELU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ELU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ELU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ELU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Embedding_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Embedding_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Embedding_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Embedding_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_FractionalMaxPool3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GELU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GELU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GELU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GELU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GLU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GLU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GLU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GLU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRUCell_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRUCell_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRUCell_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRUCell_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GRU_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GaussianNLLLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GaussianNLLLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GaussianNLLLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GaussianNLLLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GroupNorm_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GroupNorm_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GroupNorm_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_GroupNorm_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardshrink_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardshrink_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardshrink_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardshrink_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardswish_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardswish_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardswish_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardswish_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardtanh_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardtanh_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardtanh_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Hardtanh_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HingeEmbeddingLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HingeEmbeddingLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HingeEmbeddingLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HingeEmbeddingLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HuberLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HuberLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HuberLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_HuberLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm1d_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm2d_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_InstanceNorm3d_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_KLDivLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_KLDivLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_KLDivLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_KLDivLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_L1Loss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_L1Loss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_L1Loss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_L1Loss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LPPool3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTMCell_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTMCell_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTMCell_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTMCell_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LSTM_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LayerNorm_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LayerNorm_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LayerNorm_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LayerNorm_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LeakyReLU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LeakyReLU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LeakyReLU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LeakyReLU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Linear_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Linear_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Linear_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Linear_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LocalResponseNorm_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LocalResponseNorm_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LocalResponseNorm_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LocalResponseNorm_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSigmoid_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSigmoid_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSigmoid_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSigmoid_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSoftmax_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSoftmax_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSoftmax_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_LogSoftmax_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MSELoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MSELoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MSELoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MSELoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MarginRankingLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MarginRankingLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MarginRankingLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MarginRankingLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MaxPool3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Mish_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Mish_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Mish_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Mish_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelMarginLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelMarginLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelMarginLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelMarginLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelSoftMarginLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelSoftMarginLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelSoftMarginLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiLabelSoftMarginLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiMarginLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiMarginLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiMarginLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiMarginLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_MultiheadAttention_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_NLLLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_NLLLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_NLLLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_NLLLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PReLU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PReLU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PReLU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PReLU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PoissonNLLLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PoissonNLLLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PoissonNLLLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_PoissonNLLLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RMSNorm_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RMSNorm_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RMSNorm_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RMSNorm_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNNCell_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNNCell_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNNCell_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNNCell_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_RNN_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU6_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU6_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU6_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU6_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReLU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReflectionPad3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ReplicationPad3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SELU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SELU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SELU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SELU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SiLU_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SiLU_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SiLU_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SiLU_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Sigmoid_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Sigmoid_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Sigmoid_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Sigmoid_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SmoothL1Loss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SmoothL1Loss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SmoothL1Loss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SmoothL1Loss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SoftMarginLoss_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SoftMarginLoss_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SoftMarginLoss_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_SoftMarginLoss_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmax_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmin_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmin_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmin_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softmin_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softplus_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softplus_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softplus_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softplus_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softshrink_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softshrink_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softshrink_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softshrink_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softsign_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softsign_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softsign_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Softsign_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanh_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanh_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanh_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanh_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanhshrink_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanhshrink_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanhshrink_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Tanhshrink_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Threshold_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Threshold_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Threshold_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Threshold_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerDecoderLayer_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerDecoderLayer_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerDecoderLayer_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerDecoderLayer_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoderLayer_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_eval_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_eval_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_eval_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_eval_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_train_mode_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_train_mode_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_train_mode_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_TransformerEncoder_train_mode_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Transformer_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Transformer_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Transformer_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_Transformer_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad1d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad1d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad1d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad1d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad2d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad2d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad2d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad2d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad3d_swap_False_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad3d_swap_False_set_grad_True_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad3d_swap_True_set_grad_False_cpu_float32, test/test_modules.py::TestModuleCPU::test_to_nn_ZeroPad3d_swap_True_set_grad_True_cpu_float32, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_CELU_mps_float16, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_CELU_mps_float32, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_ELU_mps_float16, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_ELU_mps_float32, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_Hardswish_mps_float16, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_Hardswish_mps_float32, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_Hardtanh_mps_float16, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_Hardtanh_mps_float32, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_LeakyReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_LeakyReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_Mish_mps_float16, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_Mish_mps_float32, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_ReLU6_mps_float16, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_ReLU6_mps_float32, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_ReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_ReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_SELU_mps_float16, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_SELU_mps_float32, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_SiLU_mps_float16, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_SiLU_mps_float32, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_Threshold_mps_float16, test/test_modules.py::TestModuleMPS::test_check_inplace_nn_Threshold_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AdaptiveAvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AdaptiveAvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AdaptiveAvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AdaptiveAvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AdaptiveAvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AdaptiveAvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AdaptiveMaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AdaptiveMaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AdaptiveMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AdaptiveMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AdaptiveMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AdaptiveMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_AvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BCELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BCELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BCEWithLogitsLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BCEWithLogitsLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BatchNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BatchNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BatchNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BatchNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BatchNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BatchNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BatchNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BatchNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BatchNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BatchNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BatchNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_BatchNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Bilinear_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Bilinear_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CELU_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CELU_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CTCLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CTCLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CircularPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CircularPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CircularPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CircularPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CircularPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CircularPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ConstantPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ConstantPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ConstantPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ConstantPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ConstantPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ConstantPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Conv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Conv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Conv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Conv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Conv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Conv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CosineEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CosineEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CrossEntropyLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_CrossEntropyLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ELU_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ELU_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Embedding_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Embedding_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_FractionalMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_FractionalMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_FractionalMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_FractionalMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GELU_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GELU_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GLU_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GLU_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GRUCell_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GRUCell_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GRU_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GRU_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GRU_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GRU_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GaussianNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GaussianNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GroupNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_GroupNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Hardshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Hardshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Hardswish_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Hardswish_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Hardtanh_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Hardtanh_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_HingeEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_HingeEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_HuberLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_HuberLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_InstanceNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_InstanceNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_InstanceNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_InstanceNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_InstanceNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_InstanceNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_InstanceNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_InstanceNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_InstanceNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_InstanceNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_InstanceNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_InstanceNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_KLDivLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_KLDivLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_L1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_L1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LPPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LPPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LPPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LPPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LPPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LPPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LSTMCell_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LSTMCell_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LSTM_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LSTM_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LSTM_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LSTM_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LayerNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LayerNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LazyConv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LazyConv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LazyConv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LazyConv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LazyConv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LazyConv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LazyConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LazyConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LazyConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LazyConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LazyConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LazyConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LeakyReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LeakyReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Linear_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Linear_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LocalResponseNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LocalResponseNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LogSigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LogSigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LogSoftmax_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_LogSoftmax_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MSELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MSELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MarginRankingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MarginRankingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Mish_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Mish_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MultiLabelMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MultiLabelMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MultiLabelSoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MultiLabelSoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MultiMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MultiMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MultiheadAttention_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MultiheadAttention_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MultiheadAttention_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_MultiheadAttention_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_NLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_NLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_PReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_PReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_PoissonNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_PoissonNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_RMSNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_RMSNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_RNNCell_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_RNNCell_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_RNN_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_RNN_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_RNN_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_RNN_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReLU6_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReLU6_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReflectionPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReflectionPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReflectionPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReflectionPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReflectionPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReflectionPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReplicationPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReplicationPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReplicationPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReplicationPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReplicationPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ReplicationPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_SELU_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_SELU_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_SiLU_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_SiLU_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Sigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Sigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_SmoothL1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_SmoothL1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_SoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_SoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Softmax2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Softmax2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Softmax_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Softmax_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Softmin_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Softmin_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Softplus_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Softplus_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Softshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Softshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Softsign_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Softsign_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Tanh_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Tanh_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Tanhshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Tanhshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Threshold_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Threshold_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_TransformerDecoderLayer_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_TransformerDecoderLayer_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_TransformerEncoderLayer_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_TransformerEncoderLayer_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_TransformerEncoderLayer_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_TransformerEncoderLayer_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_TransformerEncoder_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_TransformerEncoder_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_TransformerEncoder_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_TransformerEncoder_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Transformer_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_Transformer_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ZeroPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ZeroPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ZeroPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ZeroPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ZeroPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_cpu_gpu_parity_nn_ZeroPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AdaptiveAvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AdaptiveAvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AdaptiveAvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AdaptiveAvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AdaptiveAvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AdaptiveAvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AdaptiveMaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AdaptiveMaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AdaptiveMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AdaptiveMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AdaptiveMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AdaptiveMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_AvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BCELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BCELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BCEWithLogitsLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BCEWithLogitsLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BatchNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BatchNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BatchNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BatchNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BatchNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BatchNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BatchNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BatchNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BatchNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BatchNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BatchNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_BatchNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Bilinear_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Bilinear_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CELU_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CELU_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CTCLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CTCLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CircularPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CircularPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CircularPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CircularPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CircularPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CircularPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ConstantPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ConstantPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ConstantPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ConstantPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ConstantPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ConstantPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Conv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Conv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Conv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Conv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Conv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Conv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CosineEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CosineEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CrossEntropyLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_CrossEntropyLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ELU_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ELU_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Embedding_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Embedding_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_FractionalMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_FractionalMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_FractionalMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_FractionalMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GELU_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GELU_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GLU_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GLU_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GRUCell_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GRUCell_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GRU_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GRU_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GRU_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GRU_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GaussianNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GaussianNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GroupNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_GroupNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Hardshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Hardshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Hardswish_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Hardswish_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Hardtanh_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Hardtanh_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_HingeEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_HingeEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_HuberLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_HuberLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_InstanceNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_InstanceNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_InstanceNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_InstanceNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_InstanceNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_InstanceNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_InstanceNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_InstanceNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_InstanceNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_InstanceNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_InstanceNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_InstanceNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_KLDivLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_KLDivLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_L1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_L1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LPPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LPPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LPPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LPPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LPPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LPPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LSTMCell_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LSTMCell_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LSTM_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LSTM_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LSTM_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LSTM_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LayerNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LayerNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LazyConv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LazyConv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LazyConv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LazyConv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LazyConv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LazyConv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LazyConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LazyConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LazyConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LazyConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LazyConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LazyConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LeakyReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LeakyReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Linear_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Linear_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LocalResponseNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LocalResponseNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LogSigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LogSigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LogSoftmax_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_LogSoftmax_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MSELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MSELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MarginRankingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MarginRankingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Mish_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Mish_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MultiLabelMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MultiLabelMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MultiLabelSoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MultiLabelSoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MultiMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MultiMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MultiheadAttention_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MultiheadAttention_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MultiheadAttention_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_MultiheadAttention_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_NLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_NLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_PReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_PReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_PoissonNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_PoissonNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_RMSNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_RMSNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_RNNCell_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_RNNCell_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_RNN_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_RNN_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_RNN_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_RNN_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReLU6_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReLU6_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReflectionPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReflectionPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReflectionPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReflectionPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReflectionPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReflectionPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReplicationPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReplicationPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReplicationPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReplicationPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReplicationPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ReplicationPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_SELU_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_SELU_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_SiLU_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_SiLU_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Sigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Sigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_SmoothL1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_SmoothL1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_SoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_SoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Softmax2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Softmax2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Softmax_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Softmax_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Softmin_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Softmin_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Softplus_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Softplus_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Softshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Softshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Softsign_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Softsign_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Tanh_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Tanh_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Tanhshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Tanhshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Threshold_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Threshold_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_TransformerDecoderLayer_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_TransformerDecoderLayer_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_TransformerEncoderLayer_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_TransformerEncoderLayer_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_TransformerEncoderLayer_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_TransformerEncoderLayer_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_TransformerEncoder_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_TransformerEncoder_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_TransformerEncoder_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_TransformerEncoder_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Transformer_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_Transformer_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ZeroPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ZeroPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ZeroPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ZeroPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ZeroPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_device_ctx_init_nn_ZeroPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_errors_nn_CircularPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_errors_nn_CircularPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_errors_nn_CircularPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_errors_nn_CircularPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_errors_nn_CircularPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_errors_nn_CircularPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_errors_nn_GRUCell_mps_float16, test/test_modules.py::TestModuleMPS::test_errors_nn_GRUCell_mps_float32, test/test_modules.py::TestModuleMPS::test_errors_nn_GRU_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_errors_nn_GRU_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_errors_nn_GRU_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_errors_nn_GRU_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_errors_nn_LSTMCell_mps_float16, test/test_modules.py::TestModuleMPS::test_errors_nn_LSTMCell_mps_float32, test/test_modules.py::TestModuleMPS::test_errors_nn_LSTM_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_errors_nn_LSTM_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_errors_nn_LSTM_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_errors_nn_LSTM_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_errors_nn_RNNCell_mps_float16, test/test_modules.py::TestModuleMPS::test_errors_nn_RNNCell_mps_float32, test/test_modules.py::TestModuleMPS::test_errors_nn_RNN_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_errors_nn_RNN_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_errors_nn_RNN_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_errors_nn_RNN_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AdaptiveAvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AdaptiveAvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AdaptiveAvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AdaptiveAvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AdaptiveAvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AdaptiveAvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AdaptiveMaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AdaptiveMaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AdaptiveMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AdaptiveMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AdaptiveMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AdaptiveMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_AvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BCELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BCELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BCEWithLogitsLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BCEWithLogitsLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BatchNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BatchNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BatchNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BatchNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BatchNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BatchNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BatchNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BatchNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BatchNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BatchNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BatchNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_BatchNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Bilinear_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Bilinear_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CELU_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CELU_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CTCLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CTCLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CircularPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CircularPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CircularPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CircularPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CircularPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CircularPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ConstantPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ConstantPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ConstantPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ConstantPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ConstantPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ConstantPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Conv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Conv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Conv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Conv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Conv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Conv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CosineEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CosineEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CrossEntropyLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_CrossEntropyLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ELU_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ELU_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Embedding_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Embedding_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_FractionalMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_FractionalMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_FractionalMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_FractionalMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GELU_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GELU_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GLU_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GLU_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GRUCell_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GRUCell_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GRU_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GRU_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GRU_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GRU_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GaussianNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GaussianNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GroupNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_GroupNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Hardshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Hardshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Hardswish_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Hardswish_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Hardtanh_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Hardtanh_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_HingeEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_HingeEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_HuberLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_HuberLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_InstanceNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_InstanceNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_InstanceNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_InstanceNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_InstanceNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_InstanceNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_InstanceNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_InstanceNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_InstanceNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_InstanceNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_InstanceNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_InstanceNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_KLDivLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_KLDivLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_L1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_L1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LPPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LPPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LPPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LPPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LPPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LPPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LSTMCell_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LSTMCell_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LSTM_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LSTM_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LSTM_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LSTM_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LayerNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LayerNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LazyConv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LazyConv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LazyConv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LazyConv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LazyConv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LazyConv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LazyConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LazyConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LazyConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LazyConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LazyConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LazyConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LeakyReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LeakyReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Linear_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Linear_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LocalResponseNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LocalResponseNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LogSigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LogSigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LogSoftmax_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_LogSoftmax_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MSELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MSELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MarginRankingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MarginRankingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Mish_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Mish_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MultiLabelMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MultiLabelMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MultiLabelSoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MultiLabelSoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MultiMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MultiMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MultiheadAttention_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MultiheadAttention_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MultiheadAttention_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_MultiheadAttention_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_NLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_NLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_PReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_PReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_PoissonNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_PoissonNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_RMSNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_RMSNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_RNNCell_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_RNNCell_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_RNN_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_RNN_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_RNN_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_RNN_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReLU6_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReLU6_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReflectionPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReflectionPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReflectionPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReflectionPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReflectionPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReflectionPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReplicationPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReplicationPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReplicationPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReplicationPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReplicationPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ReplicationPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_SELU_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_SELU_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_SiLU_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_SiLU_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Sigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Sigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_SmoothL1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_SmoothL1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_SoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_SoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Softmax2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Softmax2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Softmax_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Softmax_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Softmin_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Softmin_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Softplus_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Softplus_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Softshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Softshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Softsign_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Softsign_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Tanh_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Tanh_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Tanhshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Tanhshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Threshold_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Threshold_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_TransformerDecoderLayer_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_TransformerDecoderLayer_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_TransformerEncoderLayer_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_TransformerEncoderLayer_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_TransformerEncoderLayer_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_TransformerEncoderLayer_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_TransformerEncoder_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_TransformerEncoder_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_TransformerEncoder_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_TransformerEncoder_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Transformer_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_Transformer_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ZeroPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ZeroPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ZeroPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ZeroPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ZeroPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_factory_kwargs_nn_ZeroPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_AdaptiveAvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_AdaptiveAvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_AdaptiveAvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_AdaptiveAvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_AdaptiveAvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_AdaptiveAvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_AdaptiveMaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_AdaptiveMaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_AdaptiveMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_AdaptiveMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_AdaptiveMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_AdaptiveMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_AvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_AvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_AvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_AvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_AvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_AvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_BCELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_BCELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_BCEWithLogitsLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_BCEWithLogitsLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_BatchNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_BatchNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_BatchNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_BatchNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_BatchNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_BatchNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_BatchNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_BatchNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_BatchNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_BatchNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_BatchNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_BatchNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Bilinear_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Bilinear_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_CELU_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_CELU_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_CTCLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_CTCLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_CircularPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_CircularPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_CircularPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_CircularPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_CircularPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_CircularPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ConstantPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ConstantPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ConstantPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ConstantPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ConstantPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ConstantPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Conv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Conv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Conv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Conv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Conv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Conv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_CosineEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_CosineEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_CrossEntropyLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_CrossEntropyLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ELU_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ELU_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Embedding_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Embedding_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_FractionalMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_FractionalMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_FractionalMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_FractionalMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_GELU_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_GELU_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_GLU_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_GLU_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_GRUCell_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_GRUCell_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_GRU_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_GRU_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_GRU_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_GRU_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_GaussianNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_GaussianNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_GroupNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_GroupNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Hardshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Hardshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Hardswish_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Hardswish_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Hardtanh_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Hardtanh_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_HingeEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_HingeEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_HuberLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_HuberLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_InstanceNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_InstanceNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_InstanceNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_InstanceNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_InstanceNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_InstanceNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_InstanceNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_InstanceNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_InstanceNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_InstanceNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_InstanceNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_InstanceNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_KLDivLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_KLDivLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_L1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_L1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LPPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LPPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LPPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LPPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LPPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LPPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LSTMCell_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LSTMCell_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LSTM_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LSTM_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LSTM_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LSTM_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LayerNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LayerNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LazyConv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LazyConv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LazyConv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LazyConv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LazyConv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LazyConv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LazyConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LazyConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LazyConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LazyConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LazyConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LazyConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LeakyReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LeakyReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Linear_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Linear_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LocalResponseNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LocalResponseNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LogSigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LogSigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_LogSoftmax_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_LogSoftmax_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_MSELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_MSELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_MarginRankingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_MarginRankingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_MaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_MaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_MaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_MaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_MaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_MaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Mish_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Mish_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_MultiLabelMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_MultiLabelMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_MultiLabelSoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_MultiLabelSoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_MultiMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_MultiMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_MultiheadAttention_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_MultiheadAttention_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_MultiheadAttention_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_MultiheadAttention_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_NLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_NLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_PReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_PReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_PoissonNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_PoissonNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_RMSNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_RMSNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_RNNCell_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_RNNCell_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_RNN_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_RNN_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_RNN_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_RNN_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ReLU6_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ReLU6_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ReflectionPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ReflectionPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ReflectionPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ReflectionPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ReflectionPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ReflectionPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ReplicationPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ReplicationPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ReplicationPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ReplicationPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ReplicationPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ReplicationPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_SELU_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_SELU_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_SiLU_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_SiLU_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Sigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Sigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_SmoothL1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_SmoothL1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_SoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_SoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Softmax2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Softmax2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Softmax_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Softmax_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Softmin_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Softmin_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Softplus_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Softplus_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Softshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Softshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Softsign_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Softsign_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Tanh_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Tanh_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Tanhshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Tanhshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Threshold_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Threshold_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_TransformerDecoderLayer_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_TransformerDecoderLayer_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_TransformerEncoderLayer_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_TransformerEncoderLayer_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_TransformerEncoderLayer_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_TransformerEncoderLayer_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_TransformerEncoder_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_TransformerEncoder_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_TransformerEncoder_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_TransformerEncoder_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_Transformer_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_Transformer_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ZeroPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ZeroPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ZeroPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ZeroPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_forward_nn_ZeroPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_forward_nn_ZeroPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AdaptiveAvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AdaptiveMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_AvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_BCELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_BCELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_BCEWithLogitsLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_BCEWithLogitsLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_BatchNorm1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_BatchNorm1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_BatchNorm2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_BatchNorm2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_BatchNorm3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_BatchNorm3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Bilinear_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Bilinear_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CELU_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CELU_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CTCLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CTCLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CircularPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CircularPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CircularPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CircularPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CircularPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CircularPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ConstantPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ConstantPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ConstantPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ConstantPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ConstantPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ConstantPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Conv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Conv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Conv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Conv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Conv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Conv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CosineEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CosineEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CrossEntropyLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_CrossEntropyLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ELU_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ELU_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Embedding_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Embedding_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_FractionalMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_GELU_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_GELU_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_GLU_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_GLU_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_GRUCell_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_GRUCell_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_GRU_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_GRU_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_GaussianNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_GaussianNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_GroupNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_GroupNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Hardshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Hardshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Hardswish_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Hardswish_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Hardtanh_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Hardtanh_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_HingeEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_HingeEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_HuberLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_HuberLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_InstanceNorm1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_InstanceNorm1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_InstanceNorm2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_InstanceNorm2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_InstanceNorm3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_InstanceNorm3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_KLDivLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_KLDivLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_L1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_L1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LPPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LPPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LPPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LPPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LPPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LPPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LSTMCell_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LSTMCell_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LSTM_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LSTM_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LayerNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LayerNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LazyConv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LazyConv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LazyConv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LazyConv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LazyConv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LazyConv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LazyConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LeakyReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LeakyReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Linear_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Linear_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LocalResponseNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LocalResponseNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LogSigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LogSigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LogSoftmax_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_LogSoftmax_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MSELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MSELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MarginRankingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MarginRankingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Mish_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Mish_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MultiLabelMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MultiLabelMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MultiLabelSoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MultiLabelSoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MultiMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MultiMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MultiheadAttention_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_MultiheadAttention_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_NLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_NLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_PReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_PReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_PoissonNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_PoissonNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_RMSNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_RMSNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_RNNCell_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_RNNCell_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_RNN_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_RNN_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReLU6_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReLU6_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReflectionPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReflectionPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReflectionPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReflectionPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReflectionPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReflectionPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReplicationPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReplicationPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReplicationPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReplicationPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReplicationPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ReplicationPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_SELU_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_SELU_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_SiLU_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_SiLU_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Sigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Sigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_SmoothL1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_SmoothL1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_SoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_SoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Softmax2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Softmax2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Softmax_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Softmax_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Softmin_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Softmin_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Softplus_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Softplus_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Softshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Softshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Softsign_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Softsign_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Tanh_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Tanh_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Tanhshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Tanhshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Threshold_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Threshold_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_TransformerDecoderLayer_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_TransformerDecoderLayer_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_TransformerEncoderLayer_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_TransformerEncoderLayer_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_TransformerEncoder_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_TransformerEncoder_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Transformer_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_Transformer_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ZeroPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ZeroPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ZeroPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ZeroPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ZeroPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_if_train_and_eval_modes_differ_nn_ZeroPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AdaptiveAvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AdaptiveAvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AdaptiveAvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AdaptiveAvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AdaptiveAvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AdaptiveAvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AdaptiveMaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AdaptiveMaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AdaptiveMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AdaptiveMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AdaptiveMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AdaptiveMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_AvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BCELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BCELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BCEWithLogitsLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BCEWithLogitsLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BatchNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BatchNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BatchNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BatchNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BatchNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BatchNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BatchNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BatchNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BatchNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BatchNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BatchNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_BatchNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Bilinear_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Bilinear_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CELU_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CELU_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CTCLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CTCLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CircularPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CircularPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CircularPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CircularPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CircularPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CircularPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ConstantPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ConstantPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ConstantPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ConstantPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ConstantPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ConstantPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Conv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Conv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Conv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Conv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Conv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Conv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CosineEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CosineEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CrossEntropyLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_CrossEntropyLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ELU_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ELU_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Embedding_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Embedding_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_FractionalMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_FractionalMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_FractionalMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_FractionalMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GELU_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GELU_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GLU_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GLU_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GRUCell_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GRUCell_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GRU_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GRU_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GRU_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GRU_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GaussianNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GaussianNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GroupNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_GroupNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Hardshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Hardshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Hardswish_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Hardswish_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Hardtanh_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Hardtanh_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_HingeEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_HingeEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_HuberLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_HuberLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_InstanceNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_InstanceNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_InstanceNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_InstanceNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_InstanceNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_InstanceNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_InstanceNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_InstanceNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_InstanceNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_InstanceNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_InstanceNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_InstanceNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_KLDivLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_KLDivLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_L1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_L1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LPPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LPPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LPPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LPPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LPPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LPPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LSTMCell_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LSTMCell_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LSTM_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LSTM_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LSTM_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LSTM_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LayerNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LayerNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LazyConv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LazyConv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LazyConv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LazyConv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LazyConv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LazyConv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LazyConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LazyConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LazyConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LazyConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LazyConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LazyConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LeakyReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LeakyReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Linear_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Linear_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LocalResponseNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LocalResponseNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LogSigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LogSigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LogSoftmax_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_LogSoftmax_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MSELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MSELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MarginRankingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MarginRankingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Mish_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Mish_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MultiLabelMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MultiLabelMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MultiLabelSoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MultiLabelSoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MultiMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MultiMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MultiheadAttention_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MultiheadAttention_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MultiheadAttention_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_MultiheadAttention_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_NLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_NLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_PReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_PReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_PoissonNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_PoissonNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_RMSNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_RMSNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_RNNCell_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_RNNCell_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_RNN_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_RNN_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_RNN_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_RNN_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReLU6_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReLU6_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReflectionPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReflectionPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReflectionPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReflectionPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReflectionPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReflectionPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReplicationPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReplicationPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReplicationPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReplicationPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReplicationPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ReplicationPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_SELU_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_SELU_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_SiLU_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_SiLU_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Sigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Sigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_SmoothL1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_SmoothL1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_SoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_SoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Softmax2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Softmax2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Softmax_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Softmax_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Softmin_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Softmin_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Softplus_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Softplus_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Softshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Softshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Softsign_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Softsign_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Tanh_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Tanh_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Tanhshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Tanhshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Threshold_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Threshold_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_TransformerDecoderLayer_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_TransformerDecoderLayer_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_TransformerEncoderLayer_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_TransformerEncoderLayer_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_TransformerEncoderLayer_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_TransformerEncoderLayer_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_TransformerEncoder_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_TransformerEncoder_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_TransformerEncoder_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_TransformerEncoder_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Transformer_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_Transformer_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ZeroPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ZeroPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ZeroPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ZeroPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ZeroPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_memory_format_nn_ZeroPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AdaptiveAvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AdaptiveAvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AdaptiveAvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AdaptiveAvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AdaptiveAvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AdaptiveAvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AdaptiveMaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AdaptiveMaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AdaptiveMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AdaptiveMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AdaptiveMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AdaptiveMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_AvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BCELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BCELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BCEWithLogitsLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BCEWithLogitsLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BatchNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BatchNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BatchNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BatchNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BatchNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BatchNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BatchNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BatchNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BatchNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BatchNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BatchNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_BatchNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Bilinear_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Bilinear_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CELU_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CELU_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CTCLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CTCLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CircularPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CircularPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CircularPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CircularPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CircularPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CircularPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ConstantPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ConstantPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ConstantPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ConstantPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ConstantPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ConstantPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Conv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Conv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Conv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Conv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Conv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Conv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CosineEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CosineEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CrossEntropyLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_CrossEntropyLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ELU_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ELU_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Embedding_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Embedding_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_FractionalMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_FractionalMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_FractionalMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_FractionalMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GELU_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GELU_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GLU_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GLU_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GRUCell_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GRUCell_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GRU_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GRU_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GRU_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GRU_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GaussianNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GaussianNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GroupNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_GroupNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Hardshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Hardshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Hardswish_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Hardswish_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Hardtanh_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Hardtanh_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_HingeEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_HingeEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_HuberLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_HuberLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_InstanceNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_InstanceNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_InstanceNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_InstanceNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_InstanceNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_InstanceNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_InstanceNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_InstanceNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_InstanceNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_InstanceNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_InstanceNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_InstanceNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_KLDivLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_KLDivLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_L1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_L1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LPPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LPPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LPPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LPPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LPPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LPPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LSTMCell_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LSTMCell_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LSTM_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LSTM_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LSTM_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LSTM_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LayerNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LayerNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LazyConv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LazyConv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LazyConv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LazyConv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LazyConv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LazyConv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LazyConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LazyConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LazyConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LazyConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LazyConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LazyConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LeakyReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LeakyReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Linear_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Linear_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LocalResponseNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LocalResponseNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LogSigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LogSigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LogSoftmax_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_LogSoftmax_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MSELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MSELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MarginRankingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MarginRankingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Mish_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Mish_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MultiLabelMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MultiLabelMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MultiLabelSoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MultiLabelSoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MultiMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MultiMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MultiheadAttention_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MultiheadAttention_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MultiheadAttention_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_MultiheadAttention_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_NLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_NLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_PReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_PReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_PoissonNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_PoissonNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_RMSNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_RMSNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_RNNCell_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_RNNCell_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_RNN_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_RNN_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_RNN_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_RNN_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReLU6_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReLU6_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReflectionPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReflectionPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReflectionPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReflectionPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReflectionPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReflectionPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReplicationPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReplicationPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReplicationPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReplicationPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReplicationPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ReplicationPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_SELU_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_SELU_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_SiLU_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_SiLU_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Sigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Sigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_SmoothL1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_SmoothL1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_SoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_SoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Softmax2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Softmax2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Softmax_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Softmax_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Softmin_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Softmin_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Softplus_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Softplus_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Softshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Softshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Softsign_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Softsign_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Tanh_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Tanh_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Tanhshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Tanhshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Threshold_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Threshold_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_TransformerDecoderLayer_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_TransformerDecoderLayer_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_TransformerEncoderLayer_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_TransformerEncoderLayer_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_TransformerEncoderLayer_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_TransformerEncoderLayer_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_TransformerEncoder_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_TransformerEncoder_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_TransformerEncoder_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_TransformerEncoder_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Transformer_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_Transformer_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ZeroPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ZeroPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ZeroPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ZeroPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ZeroPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_multiple_device_transfer_nn_ZeroPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AdaptiveAvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AdaptiveAvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AdaptiveAvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AdaptiveAvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AdaptiveAvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AdaptiveAvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AdaptiveMaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AdaptiveMaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AdaptiveMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AdaptiveMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AdaptiveMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AdaptiveMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_AvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BCELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BCELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BCEWithLogitsLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BCEWithLogitsLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BatchNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BatchNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BatchNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BatchNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BatchNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BatchNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BatchNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BatchNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BatchNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BatchNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BatchNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_BatchNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Bilinear_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Bilinear_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CELU_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CELU_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CTCLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CTCLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CircularPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CircularPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CircularPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CircularPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CircularPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CircularPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ConstantPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ConstantPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ConstantPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ConstantPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ConstantPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ConstantPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Conv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Conv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Conv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Conv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Conv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Conv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CosineEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CosineEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CrossEntropyLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_CrossEntropyLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ELU_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ELU_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Embedding_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Embedding_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_FractionalMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_FractionalMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_FractionalMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_FractionalMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GELU_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GELU_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GLU_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GLU_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GRUCell_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GRUCell_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GRU_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GRU_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GRU_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GRU_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GaussianNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GaussianNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GroupNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_GroupNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Hardshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Hardshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Hardswish_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Hardswish_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Hardtanh_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Hardtanh_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_HingeEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_HingeEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_HuberLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_HuberLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_InstanceNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_InstanceNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_InstanceNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_InstanceNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_InstanceNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_InstanceNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_InstanceNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_InstanceNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_InstanceNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_InstanceNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_InstanceNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_InstanceNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_KLDivLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_KLDivLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_L1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_L1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LPPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LPPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LPPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LPPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LPPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LPPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LSTMCell_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LSTMCell_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LSTM_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LSTM_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LSTM_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LSTM_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LayerNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LayerNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LazyConv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LazyConv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LazyConv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LazyConv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LazyConv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LazyConv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LazyConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LazyConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LazyConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LazyConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LazyConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LazyConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LeakyReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LeakyReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Linear_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Linear_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LocalResponseNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LocalResponseNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LogSigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LogSigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LogSoftmax_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_LogSoftmax_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MSELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MSELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MarginRankingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MarginRankingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Mish_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Mish_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MultiLabelMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MultiLabelMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MultiLabelSoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MultiLabelSoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MultiMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MultiMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MultiheadAttention_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MultiheadAttention_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MultiheadAttention_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_MultiheadAttention_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_NLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_NLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_PReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_PReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_PoissonNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_PoissonNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_RMSNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_RMSNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_RNNCell_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_RNNCell_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_RNN_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_RNN_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_RNN_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_RNN_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReLU6_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReLU6_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReflectionPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReflectionPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReflectionPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReflectionPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReflectionPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReflectionPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReplicationPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReplicationPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReplicationPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReplicationPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReplicationPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ReplicationPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_SELU_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_SELU_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_SiLU_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_SiLU_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Sigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Sigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_SmoothL1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_SmoothL1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_SoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_SoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Softmax2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Softmax2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Softmax_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Softmax_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Softmin_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Softmin_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Softplus_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Softplus_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Softshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Softshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Softsign_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Softsign_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Tanh_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Tanh_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Tanhshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Tanhshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Threshold_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Threshold_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_TransformerDecoderLayer_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_TransformerDecoderLayer_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_TransformerEncoderLayer_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_TransformerEncoderLayer_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_TransformerEncoderLayer_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_TransformerEncoderLayer_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_TransformerEncoder_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_TransformerEncoder_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_TransformerEncoder_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_TransformerEncoder_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Transformer_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_Transformer_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ZeroPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ZeroPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ZeroPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ZeroPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ZeroPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_non_contiguous_tensors_nn_ZeroPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_AdaptiveAvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_AdaptiveAvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_AdaptiveAvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_AdaptiveAvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_AdaptiveAvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_AdaptiveAvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_AdaptiveMaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_AdaptiveMaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_AdaptiveMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_AdaptiveMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_AdaptiveMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_AdaptiveMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_AvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_AvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_AvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_AvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_AvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_AvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_BCELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_BCELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_BCEWithLogitsLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_BCEWithLogitsLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_BatchNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_BatchNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_BatchNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_BatchNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_BatchNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_BatchNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_BatchNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_BatchNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_BatchNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_BatchNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_BatchNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_BatchNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Bilinear_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Bilinear_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_CELU_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_CELU_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_CTCLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_CTCLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_CircularPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_CircularPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_CircularPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_CircularPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_CircularPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_CircularPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ConstantPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ConstantPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ConstantPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ConstantPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ConstantPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ConstantPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Conv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Conv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Conv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Conv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Conv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Conv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_CosineEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_CosineEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_CrossEntropyLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_CrossEntropyLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ELU_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ELU_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Embedding_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Embedding_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_FractionalMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_FractionalMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_FractionalMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_FractionalMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_GELU_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_GELU_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_GLU_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_GLU_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_GRUCell_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_GRUCell_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_GRU_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_GRU_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_GRU_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_GRU_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_GaussianNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_GaussianNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_GroupNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_GroupNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Hardshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Hardshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Hardswish_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Hardswish_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Hardtanh_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Hardtanh_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_HingeEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_HingeEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_HuberLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_HuberLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_InstanceNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_InstanceNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_InstanceNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_InstanceNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_InstanceNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_InstanceNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_InstanceNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_InstanceNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_InstanceNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_InstanceNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_InstanceNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_InstanceNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_KLDivLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_KLDivLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_L1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_L1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LPPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LPPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LPPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LPPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LPPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LPPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LSTMCell_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LSTMCell_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LSTM_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LSTM_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LSTM_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LSTM_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LayerNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LayerNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LazyConv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LazyConv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LazyConv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LazyConv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LazyConv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LazyConv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LazyConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LazyConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LazyConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LazyConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LazyConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LazyConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LeakyReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LeakyReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Linear_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Linear_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LocalResponseNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LocalResponseNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LogSigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LogSigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_LogSoftmax_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_LogSoftmax_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_MSELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_MSELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_MarginRankingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_MarginRankingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_MaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_MaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_MaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_MaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_MaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_MaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Mish_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Mish_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_MultiLabelMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_MultiLabelMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_MultiLabelSoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_MultiLabelSoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_MultiMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_MultiMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_MultiheadAttention_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_MultiheadAttention_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_MultiheadAttention_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_MultiheadAttention_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_NLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_NLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_PReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_PReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_PoissonNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_PoissonNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_RMSNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_RMSNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_RNNCell_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_RNNCell_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_RNN_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_RNN_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_RNN_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_RNN_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ReLU6_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ReLU6_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ReflectionPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ReflectionPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ReflectionPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ReflectionPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ReflectionPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ReflectionPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ReplicationPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ReplicationPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ReplicationPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ReplicationPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ReplicationPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ReplicationPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_SELU_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_SELU_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_SiLU_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_SiLU_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Sigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Sigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_SmoothL1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_SmoothL1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_SoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_SoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Softmax2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Softmax2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Softmax_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Softmax_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Softmin_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Softmin_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Softplus_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Softplus_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Softshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Softshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Softsign_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Softsign_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Tanh_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Tanh_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Tanhshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Tanhshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Threshold_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Threshold_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_TransformerDecoderLayer_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_TransformerDecoderLayer_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_TransformerEncoderLayer_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_TransformerEncoderLayer_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_TransformerEncoderLayer_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_TransformerEncoderLayer_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_TransformerEncoder_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_TransformerEncoder_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_TransformerEncoder_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_TransformerEncoder_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_Transformer_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_Transformer_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ZeroPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ZeroPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ZeroPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ZeroPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_repr_nn_ZeroPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_repr_nn_ZeroPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_AdaptiveAvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_AdaptiveAvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_AdaptiveAvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_AdaptiveAvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_AdaptiveAvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_AdaptiveAvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_AdaptiveMaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_AdaptiveMaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_AdaptiveMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_AdaptiveMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_AdaptiveMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_AdaptiveMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_AvgPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_AvgPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_AvgPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_AvgPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_AvgPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_AvgPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_BCELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_BCELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_BCEWithLogitsLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_BCEWithLogitsLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_BatchNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_BatchNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_BatchNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_BatchNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_BatchNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_BatchNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_BatchNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_BatchNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_BatchNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_BatchNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_BatchNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_BatchNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Bilinear_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Bilinear_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_CELU_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_CELU_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_CTCLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_CTCLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_CircularPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_CircularPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_CircularPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_CircularPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_CircularPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_CircularPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ConstantPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ConstantPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ConstantPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ConstantPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ConstantPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ConstantPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Conv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Conv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Conv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Conv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Conv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Conv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_CosineEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_CosineEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_CrossEntropyLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_CrossEntropyLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ELU_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ELU_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Embedding_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Embedding_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_FractionalMaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_FractionalMaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_FractionalMaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_FractionalMaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_GELU_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_GELU_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_GLU_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_GLU_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_GRUCell_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_GRUCell_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_GRU_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_GRU_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_GRU_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_GRU_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_GaussianNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_GaussianNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_GroupNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_GroupNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Hardshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Hardshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Hardswish_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Hardswish_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Hardtanh_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Hardtanh_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_HingeEmbeddingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_HingeEmbeddingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_HuberLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_HuberLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_InstanceNorm1d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_InstanceNorm1d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_InstanceNorm1d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_InstanceNorm1d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_InstanceNorm2d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_InstanceNorm2d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_InstanceNorm2d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_InstanceNorm2d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_InstanceNorm3d_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_InstanceNorm3d_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_InstanceNorm3d_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_InstanceNorm3d_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_KLDivLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_KLDivLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_L1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_L1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LPPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LPPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LPPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LPPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LPPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LPPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LSTMCell_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LSTMCell_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LSTM_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LSTM_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LSTM_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LSTM_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LayerNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LayerNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LazyConv1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LazyConv1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LazyConv2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LazyConv2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LazyConv3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LazyConv3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LazyConvTranspose1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LazyConvTranspose1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LazyConvTranspose2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LazyConvTranspose2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LazyConvTranspose3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LazyConvTranspose3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LeakyReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LeakyReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Linear_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Linear_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LocalResponseNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LocalResponseNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LogSigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LogSigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_LogSoftmax_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_LogSoftmax_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_MSELoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_MSELoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_MarginRankingLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_MarginRankingLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_MaxPool1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_MaxPool1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_MaxPool2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_MaxPool2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_MaxPool3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_MaxPool3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Mish_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Mish_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_MultiLabelMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_MultiLabelMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_MultiLabelSoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_MultiLabelSoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_MultiMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_MultiMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_MultiheadAttention_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_MultiheadAttention_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_MultiheadAttention_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_MultiheadAttention_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_NLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_NLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_PReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_PReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_PoissonNLLLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_PoissonNLLLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_RMSNorm_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_RMSNorm_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_RNNCell_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_RNNCell_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_RNN_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_RNN_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_RNN_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_RNN_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReLU6_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReLU6_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReLU_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReLU_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReflectionPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReflectionPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReflectionPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReflectionPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReflectionPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReflectionPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReplicationPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReplicationPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReplicationPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReplicationPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReplicationPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ReplicationPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_SELU_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_SELU_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_SiLU_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_SiLU_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Sigmoid_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Sigmoid_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_SmoothL1Loss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_SmoothL1Loss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_SoftMarginLoss_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_SoftMarginLoss_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Softmax2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Softmax2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Softmax_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Softmax_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Softmin_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Softmin_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Softplus_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Softplus_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Softshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Softshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Softsign_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Softsign_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Tanh_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Tanh_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Tanhshrink_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Tanhshrink_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Threshold_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Threshold_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_TransformerDecoderLayer_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_TransformerDecoderLayer_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_TransformerEncoderLayer_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_TransformerEncoderLayer_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_TransformerEncoderLayer_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_TransformerEncoderLayer_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_TransformerEncoder_eval_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_TransformerEncoder_eval_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_TransformerEncoder_train_mode_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_TransformerEncoder_train_mode_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_Transformer_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_Transformer_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ZeroPad1d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ZeroPad1d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ZeroPad2d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ZeroPad2d_mps_float32, test/test_modules.py::TestModuleMPS::test_save_load_nn_ZeroPad3d_mps_float16, test/test_modules.py::TestModuleMPS::test_save_load_nn_ZeroPad3d_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AdaptiveAvgPool1d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AdaptiveAvgPool1d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AdaptiveAvgPool2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AdaptiveAvgPool2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AdaptiveAvgPool3d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AdaptiveAvgPool3d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AdaptiveMaxPool1d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AdaptiveMaxPool1d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AdaptiveMaxPool2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AdaptiveMaxPool2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AdaptiveMaxPool3d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AdaptiveMaxPool3d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AvgPool1d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AvgPool1d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AvgPool2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AvgPool2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AvgPool3d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_AvgPool3d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BCELoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BCELoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BCEWithLogitsLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BCEWithLogitsLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BatchNorm1d_eval_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BatchNorm1d_eval_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BatchNorm1d_train_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BatchNorm1d_train_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BatchNorm2d_eval_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BatchNorm2d_eval_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BatchNorm2d_train_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BatchNorm2d_train_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BatchNorm3d_eval_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BatchNorm3d_eval_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BatchNorm3d_train_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_BatchNorm3d_train_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Bilinear_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Bilinear_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CELU_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CELU_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CTCLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CTCLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CircularPad1d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CircularPad1d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CircularPad2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CircularPad2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CircularPad3d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CircularPad3d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ConstantPad1d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ConstantPad1d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ConstantPad2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ConstantPad2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ConstantPad3d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ConstantPad3d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Conv1d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Conv1d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Conv2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Conv2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Conv3d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Conv3d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ConvTranspose1d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ConvTranspose1d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ConvTranspose2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ConvTranspose2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ConvTranspose3d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ConvTranspose3d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CosineEmbeddingLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CosineEmbeddingLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CrossEntropyLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_CrossEntropyLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ELU_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ELU_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Embedding_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Embedding_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_FractionalMaxPool2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_FractionalMaxPool2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_FractionalMaxPool3d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_FractionalMaxPool3d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GELU_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GELU_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GLU_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GLU_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GRUCell_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GRUCell_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GRU_eval_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GRU_eval_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GRU_train_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GRU_train_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GaussianNLLLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GaussianNLLLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GroupNorm_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_GroupNorm_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Hardshrink_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Hardshrink_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Hardswish_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Hardswish_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Hardtanh_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Hardtanh_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_HingeEmbeddingLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_HingeEmbeddingLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_HuberLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_HuberLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_InstanceNorm1d_eval_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_InstanceNorm1d_eval_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_InstanceNorm1d_train_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_InstanceNorm1d_train_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_InstanceNorm2d_eval_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_InstanceNorm2d_eval_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_InstanceNorm2d_train_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_InstanceNorm2d_train_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_InstanceNorm3d_eval_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_InstanceNorm3d_eval_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_InstanceNorm3d_train_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_InstanceNorm3d_train_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_KLDivLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_KLDivLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_L1Loss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_L1Loss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LPPool1d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LPPool1d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LPPool2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LPPool2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LPPool3d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LPPool3d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LSTMCell_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LSTMCell_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LSTM_eval_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LSTM_eval_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LSTM_train_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LSTM_train_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LayerNorm_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LayerNorm_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LeakyReLU_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LeakyReLU_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Linear_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Linear_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LocalResponseNorm_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LocalResponseNorm_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LogSigmoid_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LogSigmoid_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LogSoftmax_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_LogSoftmax_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MSELoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MSELoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MarginRankingLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MarginRankingLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MaxPool1d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MaxPool1d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MaxPool2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MaxPool2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MaxPool3d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MaxPool3d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Mish_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Mish_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MultiLabelMarginLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MultiLabelMarginLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MultiLabelSoftMarginLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MultiLabelSoftMarginLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MultiMarginLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MultiMarginLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MultiheadAttention_eval_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MultiheadAttention_eval_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MultiheadAttention_train_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_MultiheadAttention_train_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_NLLLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_NLLLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_PReLU_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_PReLU_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_PoissonNLLLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_PoissonNLLLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_RMSNorm_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_RMSNorm_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_RNNCell_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_RNNCell_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_RNN_eval_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_RNN_eval_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_RNN_train_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_RNN_train_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReLU6_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReLU6_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReLU_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReLU_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReflectionPad1d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReflectionPad1d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReflectionPad2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReflectionPad2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReflectionPad3d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReflectionPad3d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReplicationPad1d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReplicationPad1d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReplicationPad2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReplicationPad2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReplicationPad3d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ReplicationPad3d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_SELU_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_SELU_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_SiLU_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_SiLU_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Sigmoid_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Sigmoid_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_SmoothL1Loss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_SmoothL1Loss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_SoftMarginLoss_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_SoftMarginLoss_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Softmax2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Softmax2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Softmax_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Softmax_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Softmin_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Softmin_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Softplus_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Softplus_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Softshrink_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Softshrink_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Softsign_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Softsign_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Tanh_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Tanh_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Tanhshrink_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Tanhshrink_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Threshold_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Threshold_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_TransformerDecoderLayer_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_TransformerDecoderLayer_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_TransformerEncoderLayer_eval_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_TransformerEncoderLayer_eval_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_TransformerEncoderLayer_train_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_TransformerEncoderLayer_train_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_TransformerEncoder_eval_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_TransformerEncoder_eval_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_TransformerEncoder_train_mode_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_TransformerEncoder_train_mode_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Transformer_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_Transformer_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ZeroPad1d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ZeroPad1d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ZeroPad2d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ZeroPad2d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ZeroPad3d_swap_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_empty_nn_ZeroPad3d_swap_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveAvgPool1d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveAvgPool1d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveAvgPool1d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveAvgPool1d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveAvgPool2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveAvgPool2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveAvgPool2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveAvgPool2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveAvgPool3d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveAvgPool3d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveAvgPool3d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveAvgPool3d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveMaxPool1d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveMaxPool1d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveMaxPool1d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveMaxPool1d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveMaxPool2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveMaxPool2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveMaxPool2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveMaxPool2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveMaxPool3d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveMaxPool3d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveMaxPool3d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AdaptiveMaxPool3d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AvgPool1d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AvgPool1d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AvgPool1d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AvgPool1d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AvgPool2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AvgPool2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AvgPool2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AvgPool2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AvgPool3d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AvgPool3d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AvgPool3d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_AvgPool3d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BCELoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BCELoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BCELoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BCELoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BCEWithLogitsLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BCEWithLogitsLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BCEWithLogitsLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BCEWithLogitsLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm1d_eval_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm1d_eval_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm1d_eval_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm1d_eval_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm1d_train_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm1d_train_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm1d_train_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm1d_train_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm2d_eval_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm2d_eval_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm2d_eval_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm2d_eval_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm2d_train_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm2d_train_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm2d_train_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm2d_train_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm3d_eval_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm3d_eval_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm3d_eval_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm3d_eval_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm3d_train_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm3d_train_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm3d_train_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_BatchNorm3d_train_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Bilinear_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Bilinear_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Bilinear_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Bilinear_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CELU_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CELU_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CELU_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CELU_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CTCLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CTCLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CTCLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CTCLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CircularPad1d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CircularPad1d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CircularPad1d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CircularPad1d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CircularPad2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CircularPad2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CircularPad2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CircularPad2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CircularPad3d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CircularPad3d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CircularPad3d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CircularPad3d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConstantPad1d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConstantPad1d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConstantPad1d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConstantPad1d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConstantPad2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConstantPad2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConstantPad2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConstantPad2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConstantPad3d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConstantPad3d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConstantPad3d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConstantPad3d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Conv1d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Conv1d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Conv1d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Conv1d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Conv2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Conv2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Conv2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Conv2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Conv3d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Conv3d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Conv3d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Conv3d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConvTranspose1d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConvTranspose1d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConvTranspose1d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConvTranspose1d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConvTranspose2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConvTranspose2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConvTranspose2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConvTranspose2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConvTranspose3d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConvTranspose3d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConvTranspose3d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ConvTranspose3d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CosineEmbeddingLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CosineEmbeddingLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CosineEmbeddingLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CosineEmbeddingLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CrossEntropyLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CrossEntropyLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CrossEntropyLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_CrossEntropyLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ELU_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ELU_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ELU_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ELU_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Embedding_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Embedding_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Embedding_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Embedding_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_FractionalMaxPool2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_FractionalMaxPool2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_FractionalMaxPool2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_FractionalMaxPool2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_FractionalMaxPool3d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_FractionalMaxPool3d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_FractionalMaxPool3d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_FractionalMaxPool3d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GELU_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GELU_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GELU_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GELU_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GLU_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GLU_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GLU_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GLU_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GRUCell_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GRUCell_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GRUCell_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GRUCell_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GRU_eval_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GRU_eval_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GRU_eval_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GRU_eval_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GRU_train_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GRU_train_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GRU_train_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GRU_train_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GaussianNLLLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GaussianNLLLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GaussianNLLLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GaussianNLLLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GroupNorm_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GroupNorm_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GroupNorm_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_GroupNorm_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Hardshrink_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Hardshrink_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Hardshrink_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Hardshrink_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Hardswish_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Hardswish_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Hardswish_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Hardswish_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Hardtanh_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Hardtanh_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Hardtanh_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Hardtanh_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_HingeEmbeddingLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_HingeEmbeddingLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_HingeEmbeddingLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_HingeEmbeddingLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_HuberLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_HuberLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_HuberLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_HuberLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm1d_eval_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm1d_eval_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm1d_eval_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm1d_eval_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm1d_train_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm1d_train_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm1d_train_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm1d_train_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm2d_eval_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm2d_eval_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm2d_eval_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm2d_eval_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm2d_train_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm2d_train_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm2d_train_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm2d_train_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm3d_eval_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm3d_eval_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm3d_eval_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm3d_eval_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm3d_train_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm3d_train_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm3d_train_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_InstanceNorm3d_train_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_KLDivLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_KLDivLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_KLDivLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_KLDivLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_L1Loss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_L1Loss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_L1Loss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_L1Loss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LPPool1d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LPPool1d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LPPool1d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LPPool1d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LPPool2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LPPool2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LPPool2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LPPool2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LPPool3d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LPPool3d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LPPool3d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LPPool3d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LSTMCell_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LSTMCell_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LSTMCell_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LSTMCell_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LSTM_eval_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LSTM_eval_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LSTM_eval_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LSTM_eval_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LSTM_train_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LSTM_train_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LSTM_train_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LSTM_train_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LayerNorm_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LayerNorm_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LayerNorm_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LayerNorm_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LeakyReLU_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LeakyReLU_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LeakyReLU_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LeakyReLU_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Linear_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Linear_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Linear_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Linear_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LocalResponseNorm_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LocalResponseNorm_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LocalResponseNorm_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LocalResponseNorm_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LogSigmoid_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LogSigmoid_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LogSigmoid_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LogSigmoid_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LogSoftmax_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LogSoftmax_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LogSoftmax_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_LogSoftmax_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MSELoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MSELoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MSELoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MSELoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MarginRankingLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MarginRankingLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MarginRankingLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MarginRankingLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MaxPool1d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MaxPool1d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MaxPool1d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MaxPool1d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MaxPool2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MaxPool2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MaxPool2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MaxPool2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MaxPool3d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MaxPool3d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MaxPool3d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MaxPool3d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Mish_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Mish_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Mish_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Mish_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiLabelMarginLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiLabelMarginLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiLabelMarginLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiLabelMarginLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiLabelSoftMarginLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiLabelSoftMarginLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiLabelSoftMarginLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiLabelSoftMarginLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiMarginLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiMarginLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiMarginLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiMarginLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiheadAttention_eval_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiheadAttention_eval_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiheadAttention_eval_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiheadAttention_eval_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiheadAttention_train_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiheadAttention_train_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiheadAttention_train_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_MultiheadAttention_train_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_NLLLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_NLLLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_NLLLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_NLLLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_PReLU_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_PReLU_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_PReLU_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_PReLU_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_PoissonNLLLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_PoissonNLLLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_PoissonNLLLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_PoissonNLLLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RMSNorm_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RMSNorm_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RMSNorm_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RMSNorm_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RNNCell_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RNNCell_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RNNCell_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RNNCell_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RNN_eval_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RNN_eval_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RNN_eval_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RNN_eval_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RNN_train_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RNN_train_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RNN_train_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_RNN_train_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReLU6_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReLU6_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReLU6_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReLU6_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReLU_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReLU_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReLU_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReLU_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReflectionPad1d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReflectionPad1d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReflectionPad1d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReflectionPad1d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReflectionPad2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReflectionPad2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReflectionPad2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReflectionPad2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReflectionPad3d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReflectionPad3d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReflectionPad3d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReflectionPad3d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReplicationPad1d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReplicationPad1d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReplicationPad1d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReplicationPad1d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReplicationPad2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReplicationPad2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReplicationPad2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReplicationPad2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReplicationPad3d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReplicationPad3d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReplicationPad3d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ReplicationPad3d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SELU_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SELU_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SELU_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SELU_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SiLU_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SiLU_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SiLU_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SiLU_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Sigmoid_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Sigmoid_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Sigmoid_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Sigmoid_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SmoothL1Loss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SmoothL1Loss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SmoothL1Loss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SmoothL1Loss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SoftMarginLoss_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SoftMarginLoss_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SoftMarginLoss_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_SoftMarginLoss_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softmax2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softmax2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softmax2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softmax2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softmax_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softmax_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softmax_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softmax_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softmin_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softmin_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softmin_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softmin_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softplus_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softplus_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softplus_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softplus_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softshrink_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softshrink_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softshrink_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softshrink_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softsign_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softsign_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softsign_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Softsign_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Tanh_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Tanh_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Tanh_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Tanh_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Tanhshrink_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Tanhshrink_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Tanhshrink_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Tanhshrink_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Threshold_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Threshold_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Threshold_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Threshold_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerDecoderLayer_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerDecoderLayer_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerDecoderLayer_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerDecoderLayer_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoderLayer_eval_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoderLayer_eval_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoderLayer_eval_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoderLayer_eval_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoderLayer_train_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoderLayer_train_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoderLayer_train_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoderLayer_train_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoder_eval_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoder_eval_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoder_eval_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoder_eval_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoder_train_mode_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoder_train_mode_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoder_train_mode_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_TransformerEncoder_train_mode_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Transformer_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Transformer_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Transformer_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_Transformer_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ZeroPad1d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ZeroPad1d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ZeroPad1d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ZeroPad1d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ZeroPad2d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ZeroPad2d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ZeroPad2d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ZeroPad2d_swap_True_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ZeroPad3d_swap_False_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ZeroPad3d_swap_False_set_grad_True_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ZeroPad3d_swap_True_set_grad_False_mps_float32, test/test_modules.py::TestModuleMPS::test_to_nn_ZeroPad3d_swap_True_set_grad_True_mps_float32
2025-07-17T07:58:23.2832720Z 
2025-07-17T07:58:23.4528860Z Running test batch 'tests to run' cost 4273.81 seconds
2025-07-17T07:58:23.9013880Z 
2025-07-17T07:58:23.9014300Z real	71m17.771s
2025-07-17T07:58:23.9014730Z user	142m53.789s
2025-07-17T07:58:23.9014930Z sys	21m48.870s
2025-07-17T07:58:23.9015100Z + assert_git_not_dirty
2025-07-17T07:58:23.9015280Z + [[ macos-py3-arm64 != *rocm* ]]
2025-07-17T07:58:23.9015490Z + [[ macos-py3-arm64 != *xla* ]]
2025-07-17T07:58:23.9021970Z ++ git status --porcelain
2025-07-17T07:58:23.9022670Z ++ grep -v '?? third_party'
2025-07-17T07:58:28.9208870Z ++ true
2025-07-17T07:58:28.9210090Z + git_status=
2025-07-17T07:58:28.9210250Z + [[ -n '' ]]
2025-07-17T07:58:28.9210390Z + [[ 1 == 1 ]]
2025-07-17T07:58:28.9210670Z + test_libtorch
2025-07-17T07:58:28.9211000Z + [[ 0 == \1 ]]
2025-07-17T07:58:28.9211140Z + test_custom_script_ops
2025-07-17T07:58:28.9211310Z + print_cmake_info
2025-07-17T07:58:28.9215110Z ++ which cmake
2025-07-17T07:58:28.9246750Z + CMAKE_EXEC=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/cmake
2025-07-17T07:58:28.9247150Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/cmake
2025-07-17T07:58:28.9247490Z + echo /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/cmake
2025-07-17T07:58:28.9249820Z ++ dirname /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/cmake
2025-07-17T07:58:28.9330560Z + CONDA_INSTALLATION_DIR=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin
2025-07-17T07:58:28.9330950Z + ls -la /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/../lib
2025-07-17T07:58:28.9406780Z total 0
2025-07-17T07:58:28.9407170Z drwxr-xr-x  3 ec2-user  staff   96 Jul 17 06:46 .
2025-07-17T07:58:28.9407420Z drwxr-xr-x  8 ec2-user  staff  256 Jul 17 06:46 ..
2025-07-17T07:58:28.9407730Z drwxr-xr-x  3 ec2-user  staff   96 Jul 17 06:46 python3.12
2025-07-17T07:58:28.9408270Z + echo 'Testing custom script operators'
2025-07-17T07:58:28.9408500Z Testing custom script operators
2025-07-17T07:58:28.9408690Z + pushd test/custom_operator
2025-07-17T07:58:28.9408860Z + rm -rf build
2025-07-17T07:58:28.9409130Z ~/runner/_work/pytorch/pytorch/test/custom_operator ~/runner/_work/pytorch/pytorch
2025-07-17T07:58:28.9443540Z + mkdir build
2025-07-17T07:58:28.9463430Z + pushd build
2025-07-17T07:58:28.9463870Z ~/runner/_work/pytorch/pytorch/test/custom_operator/build ~/runner/_work/pytorch/pytorch/test/custom_operator ~/runner/_work/pytorch/pytorch
2025-07-17T07:58:28.9467020Z ++ python -c 'from distutils.sysconfig import get_python_lib; print(get_python_lib())'
2025-07-17T07:58:29.0486620Z + SITE_PACKAGES=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages
2025-07-17T07:58:29.0487210Z + CMAKE_PREFIX_PATH=/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch
2025-07-17T07:58:29.0487670Z + /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/bin/cmake ..
2025-07-17T07:58:29.4910080Z -- The C compiler identification is AppleClang 15.0.0.15000309
2025-07-17T07:58:29.5579460Z -- The CXX compiler identification is AppleClang 15.0.0.15000309
2025-07-17T07:58:29.5975950Z -- Detecting C compiler ABI info
2025-07-17T07:58:29.7260720Z -- Detecting C compiler ABI info - done
2025-07-17T07:58:29.7297790Z -- Check for working C compiler: /Library/Developer/CommandLineTools/usr/bin/clang - skipped
2025-07-17T07:58:29.7307260Z -- Detecting C compile features
2025-07-17T07:58:29.7316830Z -- Detecting C compile features - done
2025-07-17T07:58:29.7518540Z -- Detecting CXX compiler ABI info
2025-07-17T07:58:29.8479230Z -- Detecting CXX compiler ABI info - done
2025-07-17T07:58:29.8517360Z -- Check for working CXX compiler: /Library/Developer/CommandLineTools/usr/bin/clang++ - skipped
2025-07-17T07:58:29.8519520Z -- Detecting CXX compile features
2025-07-17T07:58:29.8522980Z -- Detecting CXX compile features - done
2025-07-17T07:58:29.9135850Z CMake Warning at /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:22 (message):
2025-07-17T07:58:29.9165060Z   static library kineto_LIBRARY-NOTFOUND not found.
2025-07-17T07:58:29.9165300Z Call Stack (most recent call first):
2025-07-17T07:58:29.9165800Z   /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:125 (append_torchlib_if_found)
2025-07-17T07:58:29.9166300Z   CMakeLists.txt:9 (find_package)
2025-07-17T07:58:29.9166420Z 
2025-07-17T07:58:29.9166420Z 
2025-07-17T07:58:29.9166800Z -- Found Torch: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib/libtorch.dylib  
2025-07-17T07:58:29.9167210Z -- Configuring done (0.6s)
2025-07-17T07:58:29.9272430Z -- Generating done (0.0s)
2025-07-17T07:58:29.9298470Z -- Build files have been written to: /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build
2025-07-17T07:58:29.9337920Z + make VERBOSE=1
2025-07-17T07:58:29.9425120Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/cmake/data/bin/cmake -S/Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator -B/Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build --check-build-system CMakeFiles/Makefile.cmake 0
2025-07-17T07:58:29.9473460Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/cmake/data/bin/cmake -E cmake_progress_start /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build/CMakeFiles /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build//CMakeFiles/progress.marks
2025-07-17T07:58:29.9510310Z /Library/Developer/CommandLineTools/usr/bin/make  -f CMakeFiles/Makefile2 all
2025-07-17T07:58:29.9524710Z /Library/Developer/CommandLineTools/usr/bin/make  -f CMakeFiles/custom_ops.dir/build.make CMakeFiles/custom_ops.dir/depend
2025-07-17T07:58:29.9539830Z cd /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build && /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/cmake/data/bin/cmake -E cmake_depends "Unix Makefiles" /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build/CMakeFiles/custom_ops.dir/DependInfo.cmake "--color="
2025-07-17T07:58:29.9600970Z /Library/Developer/CommandLineTools/usr/bin/make  -f CMakeFiles/custom_ops.dir/build.make CMakeFiles/custom_ops.dir/build
2025-07-17T07:58:29.9668970Z [ 25%] Building CXX object CMakeFiles/custom_ops.dir/op.cpp.o
2025-07-17T07:58:29.9672180Z /Library/Developer/CommandLineTools/usr/bin/clang++ -Dcustom_ops_EXPORTS -isystem /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -isystem /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -std=gnu++17 -arch arm64 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -mmacosx-version-min=11.1 -fPIC -F/Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk/System/Library/Frameworks  -MD -MT CMakeFiles/custom_ops.dir/op.cpp.o -MF CMakeFiles/custom_ops.dir/op.cpp.o.d -o CMakeFiles/custom_ops.dir/op.cpp.o -c /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/op.cpp
2025-07-17T07:58:37.5263260Z [ 50%] Linking CXX shared library libcustom_ops.dylib
2025-07-17T07:58:37.5264740Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/cmake/data/bin/cmake -E cmake_link_script CMakeFiles/custom_ops.dir/link.txt --verbose=1
2025-07-17T07:58:37.5301820Z /Library/Developer/CommandLineTools/usr/bin/clang++  -arch arm64 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -mmacosx-version-min=11.1 -dynamiclib -Wl,-headerpad_max_install_names -o libcustom_ops.dylib -install_name @rpath/libcustom_ops.dylib CMakeFiles/custom_ops.dir/op.cpp.o -F/Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk/System/Library/Frameworks  -Wl,-rpath,/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib/libc10.dylib /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib/libtorch.dylib /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib/libtorch_cpu.dylib /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib/libc10.dylib -Xlinker -framework -Xlinker Metal -Xlinker -framework -Xlinker MetalPerformanceShaders -Xlinker -framework -Xlinker Foundation -Xlinker -framework -Xlinker Accelerate 
2025-07-17T07:58:37.6493440Z [ 50%] Built target custom_ops
2025-07-17T07:58:37.6495090Z /Library/Developer/CommandLineTools/usr/bin/make  -f CMakeFiles/test_custom_ops.dir/build.make CMakeFiles/test_custom_ops.dir/depend
2025-07-17T07:58:37.6511340Z cd /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build && /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/cmake/data/bin/cmake -E cmake_depends "Unix Makefiles" /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build/CMakeFiles/test_custom_ops.dir/DependInfo.cmake "--color="
2025-07-17T07:58:37.6571060Z /Library/Developer/CommandLineTools/usr/bin/make  -f CMakeFiles/test_custom_ops.dir/build.make CMakeFiles/test_custom_ops.dir/build
2025-07-17T07:58:37.6638500Z [ 75%] Building CXX object CMakeFiles/test_custom_ops.dir/test_custom_ops.cpp.o
2025-07-17T07:58:37.6641950Z /Library/Developer/CommandLineTools/usr/bin/clang++  -isystem /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include -isystem /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/include/torch/csrc/api/include -std=gnu++17 -arch arm64 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -mmacosx-version-min=11.1 -F/Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk/System/Library/Frameworks  -MD -MT CMakeFiles/test_custom_ops.dir/test_custom_ops.cpp.o -MF CMakeFiles/test_custom_ops.dir/test_custom_ops.cpp.o.d -o CMakeFiles/test_custom_ops.dir/test_custom_ops.cpp.o -c /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/test_custom_ops.cpp
2025-07-17T07:58:41.2182820Z [100%] Linking CXX executable test_custom_ops
2025-07-17T07:58:41.2184520Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/cmake/data/bin/cmake -E cmake_link_script CMakeFiles/test_custom_ops.dir/link.txt --verbose=1
2025-07-17T07:58:41.2222560Z /Library/Developer/CommandLineTools/usr/bin/clang++  -arch arm64 -isysroot /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk -mmacosx-version-min=11.1 -Wl,-search_paths_first -Wl,-headerpad_max_install_names CMakeFiles/test_custom_ops.dir/test_custom_ops.cpp.o -o test_custom_ops -F/Library/Developer/CommandLineTools/SDKs/MacOSX14.sdk/System/Library/Frameworks  -Wl,-rpath,/Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build -Wl,-rpath,/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib libcustom_ops.dylib /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib/libtorch.dylib /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib/libtorch_cpu.dylib /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib/libc10.dylib -Xlinker -framework -Xlinker Metal -Xlinker -framework -Xlinker MetalPerformanceShaders -Xlinker -framework -Xlinker Foundation -Xlinker -framework -Xlinker Accelerate /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/lib/libc10.dylib 
2025-07-17T07:58:41.3107630Z [100%] Built target test_custom_ops
2025-07-17T07:58:41.3111220Z /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/cmake/data/bin/cmake -E cmake_progress_start /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/build/CMakeFiles 0
2025-07-17T07:58:41.3151140Z + popd
2025-07-17T07:58:41.3151310Z + python test_custom_ops.py -v
2025-07-17T07:58:41.3151770Z ~/runner/_work/pytorch/pytorch/test/custom_operator ~/runner/_work/pytorch/pytorch
2025-07-17T07:58:42.8939600Z /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/pointwise.py:11: FutureWarning: `torch.library.impl_abstract` was renamed to `torch.library.register_fake`. Please use that instead; we will remove `torch.library.impl_abstract` in a future version of PyTorch.
2025-07-17T07:58:42.8940750Z   @torch.library.impl_abstract("custom::cos")
2025-07-17T07:58:42.9201550Z /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/pointwise.py:17: FutureWarning: `torch.library.impl_abstract` was renamed to `torch.library.register_fake`. Please use that instead; we will remove `torch.library.impl_abstract` in a future version of PyTorch.
2025-07-17T07:58:42.9202570Z   @torch.library.impl_abstract("custom::tan")
2025-07-17T07:58:42.9300850Z 
2025-07-17T07:58:42.9301000Z Running tests...
2025-07-17T07:58:42.9301270Z ----------------------------------------------------------------------
2025-07-17T07:58:42.9301680Z Test results will be stored in test-reports/python-unittest/test_custom_ops
2025-07-17T07:58:43.1752040Z   test_abstract_impl_pystub_faketensor (__main__.TestCustomOperators.test_abstract_impl_pystub_faketensor) ... /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/my_custom_ops.py:9: FutureWarning: `torch.library.impl_abstract` was renamed to `torch.library.register_fake`. Please use that instead; we will remove `torch.library.impl_abstract` in a future version of PyTorch.
2025-07-17T07:58:43.1753170Z   @torch.library.impl_abstract("custom::nonzero")
2025-07-17T07:58:43.1886280Z /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/my_custom_ops.py:13: FutureWarning: `create_unbacked_symint` is deprecated, please use `new_dynamic_size` instead
2025-07-17T07:58:43.1886830Z   nnz = ctx.create_unbacked_symint()
2025-07-17T07:58:43.1934280Z ok (0.263s)
2025-07-17T07:58:43.1951270Z   test_abstract_impl_pystub_meta (__main__.TestCustomOperators.test_abstract_impl_pystub_meta) ... /Users/ec2-user/runner/_work/pytorch/pytorch/test/custom_operator/my_custom_ops2.py:9: FutureWarning: `torch.library.impl_abstract` was renamed to `torch.library.register_fake`. Please use that instead; we will remove `torch.library.impl_abstract` in a future version of PyTorch.
2025-07-17T07:58:43.1952300Z   @torch.library.impl_abstract("custom::sin")
2025-07-17T07:58:43.1960860Z ok (0.003s)
2025-07-17T07:58:43.1968350Z   test_calling_custom_op (__main__.TestCustomOperators.test_calling_custom_op) ... ok (0.001s)
2025-07-17T07:58:43.2165200Z   test_calling_custom_op_inside_script_module (__main__.TestCustomOperators.test_calling_custom_op_inside_script_module) ... ok (0.020s)
2025-07-17T07:58:43.2168480Z   test_calling_custom_op_string (__main__.TestCustomOperators.test_calling_custom_op_string) ... ok (0.000s)
2025-07-17T07:58:43.2179980Z   test_calling_custom_op_with_autograd (__main__.TestCustomOperators.test_calling_custom_op_with_autograd) ... /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/torch/autograd/graph.py:829: UserWarning: Using backward() with create_graph=True will create a reference cycle between the parameter and its gradient which can cause a memory leak. We recommend using autograd.grad when creating the graph to avoid this. If you have to use this function, make sure to reset the .grad fields of your parameters to None after use to break the cycle and avoid the leak. (Triggered internally at /Users/ec2-user/runner/_work/pytorch/pytorch/torch/csrc/autograd/engine.cpp:1296.)
2025-07-17T07:58:43.2181900Z   return Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass
2025-07-17T07:58:43.2183360Z ok (0.001s)
2025-07-17T07:58:43.2186930Z   test_calling_custom_op_with_autograd_in_nograd_mode (__main__.TestCustomOperators.test_calling_custom_op_with_autograd_in_nograd_mode) ... ok (0.000s)
2025-07-17T07:58:43.2188350Z   test_custom_library_is_loaded (__main__.TestCustomOperators.test_custom_library_is_loaded) ... ok (0.000s)
2025-07-17T07:58:43.2445350Z   test_dynamo_pystub_suggestion (__main__.TestCustomOperators.test_dynamo_pystub_suggestion) ... ok (0.026s)
2025-07-17T07:58:43.2449130Z   test_op_with_incorrect_abstract_impl_pystub (__main__.TestCustomOperators.test_op_with_incorrect_abstract_impl_pystub) ... ok (0.000s)
2025-07-17T07:58:43.2452220Z   test_op_with_no_abstract_impl_pystub (__main__.TestCustomOperators.test_op_with_no_abstract_impl_pystub) ... ok (0.000s)
2025-07-17T07:58:43.2500530Z   test_saving_and_loading_script_module_with_custom_op (__main__.TestCustomOperators.test_saving_and_loading_script_module_with_custom_op) ... ok (0.005s)
2025-07-17T07:58:43.2500950Z 
2025-07-17T07:58:43.2501070Z ----------------------------------------------------------------------
2025-07-17T07:58:43.2501300Z Ran 12 tests in 0.320s
2025-07-17T07:58:43.2501400Z 
2025-07-17T07:58:43.2501450Z OK
2025-07-17T07:58:43.2501510Z 
2025-07-17T07:58:43.2501570Z Generating XML reports...
2025-07-17T07:58:43.2523050Z Generated XML report: test-reports/python-unittest/test_custom_ops/TEST-TestCustomOperators-20250717075842.xml
2025-07-17T07:58:43.5797920Z + python model.py --export-script-module=model.pt
2025-07-17T07:58:44.3562960Z + build/test_custom_ops ./model.pt
2025-07-17T07:58:44.5609980Z [W717 07:58:44.084899000 engine.cpp:1296] Warning: Using backward() with create_graph=True will create a reference cycle between the parameter and its gradient which can cause a memory leak. We recommend using autograd.grad when creating the graph to avoid this. If you have to use this function, make sure to reset the .grad fields of your parameters to None after use to break the cycle and avoid the leak. (function operator())
2025-07-17T07:58:44.6292640Z ok
2025-07-17T07:58:44.6307120Z + popd
2025-07-17T07:58:44.6307270Z ~/runner/_work/pytorch/pytorch
2025-07-17T07:58:44.6307540Z + assert_git_not_dirty
2025-07-17T07:58:44.6307740Z + [[ macos-py3-arm64 != *rocm* ]]
2025-07-17T07:58:44.6307960Z + [[ macos-py3-arm64 != *xla* ]]
2025-07-17T07:58:44.6313910Z ++ git status --porcelain
2025-07-17T07:58:44.6315220Z ++ grep -v '?? third_party'
2025-07-17T07:58:45.1480350Z ++ true
2025-07-17T07:58:45.1481640Z + git_status=
2025-07-17T07:58:45.1481810Z + [[ -n '' ]]
2025-07-17T07:58:45.1752770Z ##[group]Run cat test/**/*_toprint.log || true
2025-07-17T07:58:45.1753000Z cat test/**/*_toprint.log || true
2025-07-17T07:58:45.2808630Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T07:58:45.2808860Z env:
2025-07-17T07:58:45.2808980Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:45.2809150Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:45.2809330Z   TEST_CONFIG: default
2025-07-17T07:58:45.2809470Z   SHARD_NUMBER: 1
2025-07-17T07:58:45.2809610Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:45.2809740Z   PR_BODY: 
2025-07-17T07:58:45.2809930Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:45.2810170Z ##[endgroup]
2025-07-17T07:58:45.7377080Z cat: test/**/*_toprint.log: No such file or directory
2025-07-17T07:58:45.7415140Z ##[group]Run kill "$MONITOR_SCRIPT_PID"
2025-07-17T07:58:45.7415360Z kill "$MONITOR_SCRIPT_PID"
2025-07-17T07:58:45.7427070Z shell: /bin/bash -e -l {0}
2025-07-17T07:58:45.7427250Z env:
2025-07-17T07:58:45.7427380Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:45.7427570Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:45.7427760Z   TEST_CONFIG: default
2025-07-17T07:58:45.7427920Z   SHARD_NUMBER: 1
2025-07-17T07:58:45.7428060Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:45.7428340Z   PR_BODY: 
2025-07-17T07:58:45.7428540Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:45.7428800Z   MONITOR_SCRIPT_PID: 32807
2025-07-17T07:58:45.7428960Z ##[endgroup]
2025-07-17T07:58:45.7935780Z Prepare all required actions
2025-07-17T07:58:45.7936080Z Getting action download info
2025-07-17T07:58:45.9334080Z Download action repository 'seemethere/upload-artifact-s3@v5' (SHA:baba72d0712b404f646cebe0730933554ebce96a)
2025-07-17T07:58:46.1387570Z Download action repository 'actions/upload-artifact@v4' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02)
2025-07-17T07:58:46.3618580Z ##[group]Run ./.github/actions/upload-test-artifacts
2025-07-17T07:58:46.3618950Z with:
2025-07-17T07:58:46.3619060Z   use-gha: true
2025-07-17T07:58:46.3619250Z   file-suffix: test-default-1-3-macos-m1-stable_46154244367
2025-07-17T07:58:46.3619490Z   s3-bucket: gha-artifacts
2025-07-17T07:58:46.3619630Z env:
2025-07-17T07:58:46.3619750Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:46.3619940Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:46.3620120Z   TEST_CONFIG: default
2025-07-17T07:58:46.3620260Z   SHARD_NUMBER: 1
2025-07-17T07:58:46.3620390Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:46.3620540Z   PR_BODY: 
2025-07-17T07:58:46.3620740Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:46.3620970Z ##[endgroup]
2025-07-17T07:58:46.3669650Z ##[group]Run actions/upload-artifact@v4
2025-07-17T07:58:46.3669830Z with:
2025-07-17T07:58:46.3670070Z   name: test-jsons-runattempt1-test-default-1-3-macos-m1-stable_46154244367.zip
2025-07-17T07:58:46.3670360Z   retention-days: 14
2025-07-17T07:58:46.3670500Z   if-no-files-found: warn
2025-07-17T07:58:46.3670660Z   path: test/**/*.json
2025-07-17T07:58:46.3670800Z   compression-level: 6
2025-07-17T07:58:46.3670940Z   overwrite: false
2025-07-17T07:58:46.3671080Z   include-hidden-files: false
2025-07-17T07:58:46.3671240Z env:
2025-07-17T07:58:46.3671350Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:46.3671520Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:46.3671700Z   TEST_CONFIG: default
2025-07-17T07:58:46.3671830Z   SHARD_NUMBER: 1
2025-07-17T07:58:46.3671960Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:46.3672090Z   PR_BODY: 
2025-07-17T07:58:46.3672280Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:46.3672520Z ##[endgroup]
2025-07-17T07:58:46.9174940Z With the provided path, there will be 6 files uploaded
2025-07-17T07:58:46.9178630Z Artifact name is valid!
2025-07-17T07:58:46.9179460Z Root directory input is valid!
2025-07-17T07:58:46.9743000Z Beginning upload of artifact content to blob storage
2025-07-17T07:58:47.1124630Z Uploaded bytes 45915
2025-07-17T07:58:47.1352080Z Finished uploading artifact content to blob storage!
2025-07-17T07:58:47.1355370Z SHA256 digest of uploaded artifact zip is 45c8dc7e8748c423dc9614faaf912743693d192b6799617b25acc64b0b953dc8
2025-07-17T07:58:47.1357060Z Finalizing artifact upload
2025-07-17T07:58:47.2192640Z Artifact test-jsons-runattempt1-test-default-1-3-macos-m1-stable_46154244367.zip.zip successfully finalized. Artifact ID 3552385017
2025-07-17T07:58:47.2198150Z Artifact test-jsons-runattempt1-test-default-1-3-macos-m1-stable_46154244367.zip has been successfully uploaded! Final size is 45915 bytes. Artifact ID is 3552385017
2025-07-17T07:58:47.2225050Z Artifact download URL: https://github.com/pytorch/pytorch/actions/runs/16337959945/artifacts/3552385017
2025-07-17T07:58:47.2503720Z ##[group]Run actions/upload-artifact@v4
2025-07-17T07:58:47.2504340Z with:
2025-07-17T07:58:47.2505160Z   name: test-reports-runattempt1-test-default-1-3-macos-m1-stable_46154244367.zip
2025-07-17T07:58:47.2506090Z   retention-days: 14
2025-07-17T07:58:47.2506650Z   if-no-files-found: ignore
2025-07-17T07:58:47.2507220Z   path: test/**/*.xml
test/**/*.csv

2025-07-17T07:58:47.2507810Z   compression-level: 6
2025-07-17T07:58:47.2508280Z   overwrite: false
2025-07-17T07:58:47.2508800Z   include-hidden-files: false
2025-07-17T07:58:47.2509720Z env:
2025-07-17T07:58:47.2510140Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:47.2510720Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:47.2511300Z   TEST_CONFIG: default
2025-07-17T07:58:47.2511770Z   SHARD_NUMBER: 1
2025-07-17T07:58:47.2513080Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:47.2513640Z   PR_BODY: 
2025-07-17T07:58:47.2514300Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:47.2515240Z ##[endgroup]
2025-07-17T07:58:47.6728460Z With the provided path, there will be 196 files uploaded
2025-07-17T07:58:47.6731190Z Artifact name is valid!
2025-07-17T07:58:47.6731660Z Root directory input is valid!
2025-07-17T07:58:47.7451170Z Beginning upload of artifact content to blob storage
2025-07-17T07:58:48.0742940Z Uploaded bytes 690698
2025-07-17T07:58:48.0928700Z Finished uploading artifact content to blob storage!
2025-07-17T07:58:48.0931350Z SHA256 digest of uploaded artifact zip is 9fd132a99f6f85f70287837dc814b528d899094cd8eba6fe00e9c6d1ab92b5de
2025-07-17T07:58:48.0932730Z Finalizing artifact upload
2025-07-17T07:58:48.1752900Z Artifact test-reports-runattempt1-test-default-1-3-macos-m1-stable_46154244367.zip.zip successfully finalized. Artifact ID 3552385118
2025-07-17T07:58:48.1756640Z Artifact test-reports-runattempt1-test-default-1-3-macos-m1-stable_46154244367.zip has been successfully uploaded! Final size is 690698 bytes. Artifact ID is 3552385118
2025-07-17T07:58:48.1783830Z Artifact download URL: https://github.com/pytorch/pytorch/actions/runs/16337959945/artifacts/3552385118
2025-07-17T07:58:48.2010270Z ##[group]Run actions/upload-artifact@v4
2025-07-17T07:58:48.2010800Z with:
2025-07-17T07:58:48.2011390Z   name: logs-runattempt1-test-default-1-3-macos-m1-stable_46154244367.zip
2025-07-17T07:58:48.2012130Z   retention-days: 14
2025-07-17T07:58:48.2012540Z   if-no-files-found: ignore
2025-07-17T07:58:48.2013060Z   path: usage_log.txt
test/**/*.log

2025-07-17T07:58:48.2013540Z   compression-level: 6
2025-07-17T07:58:48.2013970Z   overwrite: false
2025-07-17T07:58:48.2014400Z   include-hidden-files: false
2025-07-17T07:58:48.2014820Z env:
2025-07-17T07:58:48.2015190Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:48.2015640Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:48.2016160Z   TEST_CONFIG: default
2025-07-17T07:58:48.2016580Z   SHARD_NUMBER: 1
2025-07-17T07:58:48.2016940Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:48.2017360Z   PR_BODY: 
2025-07-17T07:58:48.2017870Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:48.2018510Z ##[endgroup]
2025-07-17T07:58:48.6265290Z Multiple search paths detected. Calculating the least common ancestor of all paths
2025-07-17T07:58:48.6266280Z The least common ancestor is /Users/ec2-user/runner/_work/pytorch/pytorch. This will be the root directory of the artifact
2025-07-17T07:58:48.6266810Z With the provided path, there will be 244 files uploaded
2025-07-17T07:58:48.6269240Z Artifact name is valid!
2025-07-17T07:58:48.6269440Z Root directory input is valid!
2025-07-17T07:58:48.6896990Z Beginning upload of artifact content to blob storage
2025-07-17T07:58:49.0481990Z Uploaded bytes 905423
2025-07-17T07:58:49.0679990Z Finished uploading artifact content to blob storage!
2025-07-17T07:58:49.0682360Z SHA256 digest of uploaded artifact zip is e0dba99c2c0538d3f19bd3cd10755abea5b57292a2e7014457711c40af4ae2f3
2025-07-17T07:58:49.0683750Z Finalizing artifact upload
2025-07-17T07:58:49.1530940Z Artifact logs-runattempt1-test-default-1-3-macos-m1-stable_46154244367.zip.zip successfully finalized. Artifact ID 3552385212
2025-07-17T07:58:49.1534440Z Artifact logs-runattempt1-test-default-1-3-macos-m1-stable_46154244367.zip has been successfully uploaded! Final size is 905423 bytes. Artifact ID is 3552385212
2025-07-17T07:58:49.1561410Z Artifact download URL: https://github.com/pytorch/pytorch/actions/runs/16337959945/artifacts/3552385212
2025-07-17T07:58:49.1878200Z ##[group]Run pytorch/test-infra/.github/actions/upload-benchmark-results@main
2025-07-17T07:58:49.1878820Z with:
2025-07-17T07:58:49.1879440Z   benchmark-results-dir: test/test-reports
2025-07-17T07:58:49.1879880Z   dry-run: false
2025-07-17T07:58:49.1892700Z   schema-version: v3
2025-07-17T07:58:49.1893690Z   github-token: ***
2025-07-17T07:58:49.1894000Z env:
2025-07-17T07:58:49.1894270Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:49.1894650Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:49.1895050Z   TEST_CONFIG: default
2025-07-17T07:58:49.1895370Z   SHARD_NUMBER: 1
2025-07-17T07:58:49.1895660Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:49.1895960Z   PR_BODY: 
2025-07-17T07:58:49.1896410Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:49.1896930Z ##[endgroup]
2025-07-17T07:58:49.1921710Z ##[group]Run set -eux
2025-07-17T07:58:49.1922220Z set -eux
2025-07-17T07:58:49.1922750Z python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0
2025-07-17T07:58:49.1923310Z 
2025-07-17T07:58:49.1923570Z DEVICE_NAME=""
2025-07-17T07:58:49.1923920Z DEVICE_TYPE=""
2025-07-17T07:58:49.1924240Z 
2025-07-17T07:58:49.1924530Z if command -v nvidia-smi; then
2025-07-17T07:58:49.1925160Z   # NB: I'm using PyTorch here to get the device name, however, it needs to
2025-07-17T07:58:49.1925940Z   # install the correct version of PyTorch manually for now. Any PyTorch
2025-07-17T07:58:49.1926670Z   # version is fine, I just use 2.7.1 to satify PYPIDEP linter
2025-07-17T07:58:49.1927260Z   python3 -mpip install torch==2.7.1
2025-07-17T07:58:49.1927730Z elif command -v rocminfo; then
2025-07-17T07:58:49.1928330Z   # NB: Installing torch on ROCm runner with pip here causes CI to fail
2025-07-17T07:58:49.1929090Z   # with a memoryview is too large error only on MI300 runners. Is pip
2025-07-17T07:58:49.1929870Z   # version on ROCm runner there too old? As a workaround, let's use the
2025-07-17T07:58:49.1930550Z   # GPU device name coming from rocminfo instead
2025-07-17T07:58:49.1931030Z   DEVICE_NAME=rocm
2025-07-17T07:58:49.1931700Z   DEVICE_TYPE=$(rocminfo | grep "Marketing Name" | tail -n1 | awk -F':' '{print $2}' | xargs)
2025-07-17T07:58:49.1932350Z fi
2025-07-17T07:58:49.1932620Z 
2025-07-17T07:58:49.1932990Z echo "DEVICE_NAME=$DEVICE_NAME" >> $GITHUB_ENV
2025-07-17T07:58:49.1933550Z echo "DEVICE_TYPE=$DEVICE_TYPE" >> $GITHUB_ENV
2025-07-17T07:58:49.1957490Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T07:58:49.1957900Z env:
2025-07-17T07:58:49.1958140Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:49.1958470Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:49.1958830Z   TEST_CONFIG: default
2025-07-17T07:58:49.1959100Z   SHARD_NUMBER: 1
2025-07-17T07:58:49.1959360Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:49.1959630Z   PR_BODY: 
2025-07-17T07:58:49.1960010Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:49.1960480Z ##[endgroup]
2025-07-17T07:58:49.2267200Z + python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0
2025-07-17T07:58:49.8498660Z Collecting boto3==1.35.33
2025-07-17T07:58:49.8528070Z   Using cached boto3-1.35.33-py3-none-any.whl.metadata (6.6 kB)
2025-07-17T07:58:49.8950010Z Collecting psutil==7.0.0
2025-07-17T07:58:49.9002930Z   Using cached psutil-7.0.0-cp36-abi3-macosx_11_0_arm64.whl.metadata (22 kB)
2025-07-17T07:58:49.9213160Z Collecting pynvml==12.0.0
2025-07-17T07:58:49.9232990Z   Using cached pynvml-12.0.0-py3-none-any.whl.metadata (5.4 kB)
2025-07-17T07:58:49.9272700Z Requirement already satisfied: botocore<1.36.0,>=1.35.33 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from boto3==1.35.33) (1.35.99)
2025-07-17T07:58:49.9276420Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from boto3==1.35.33) (1.0.1)
2025-07-17T07:58:49.9278230Z Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from boto3==1.35.33) (0.10.4)
2025-07-17T07:58:49.9376720Z Collecting nvidia-ml-py<13.0.0a0,>=12.0.0 (from pynvml==12.0.0)
2025-07-17T07:58:49.9391280Z   Using cached nvidia_ml_py-12.575.51-py3-none-any.whl.metadata (9.3 kB)
2025-07-17T07:58:49.9448050Z Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (2.9.0.post0)
2025-07-17T07:58:49.9453740Z Requirement already satisfied: urllib3!=2.2.0,<3,>=1.25.4 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.26.20)
2025-07-17T07:58:49.9477080Z Requirement already satisfied: six>=1.5 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from python-dateutil<3.0.0,>=2.1->botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.17.0)
2025-07-17T07:58:49.9556730Z Using cached boto3-1.35.33-py3-none-any.whl (139 kB)
2025-07-17T07:58:49.9605330Z Using cached psutil-7.0.0-cp36-abi3-macosx_11_0_arm64.whl (239 kB)
2025-07-17T07:58:49.9634060Z Using cached pynvml-12.0.0-py3-none-any.whl (26 kB)
2025-07-17T07:58:49.9662370Z Using cached nvidia_ml_py-12.575.51-py3-none-any.whl (47 kB)
2025-07-17T07:58:50.1051310Z Installing collected packages: nvidia-ml-py, pynvml, psutil, boto3
2025-07-17T07:58:50.1497470Z   Attempting uninstall: psutil
2025-07-17T07:58:50.1515930Z     Found existing installation: psutil 5.9.1
2025-07-17T07:58:50.1571580Z     Uninstalling psutil-5.9.1:
2025-07-17T07:58:50.1578550Z       Successfully uninstalled psutil-5.9.1
2025-07-17T07:58:50.2685290Z   Attempting uninstall: boto3
2025-07-17T07:58:50.2699650Z     Found existing installation: boto3 1.35.42
2025-07-17T07:58:50.2793800Z     Uninstalling boto3-1.35.42:
2025-07-17T07:58:50.2808100Z       Successfully uninstalled boto3-1.35.42
2025-07-17T07:58:50.3249130Z 
2025-07-17T07:58:50.3286770Z Successfully installed boto3-1.35.33 nvidia-ml-py-12.575.51 psutil-7.0.0 pynvml-12.0.0
2025-07-17T07:58:50.3816390Z + DEVICE_NAME=
2025-07-17T07:58:50.3816620Z + DEVICE_TYPE=
2025-07-17T07:58:50.3816790Z + command -v nvidia-smi
2025-07-17T07:58:50.3817030Z + command -v rocminfo
2025-07-17T07:58:50.3817240Z + echo DEVICE_NAME=
2025-07-17T07:58:50.3818450Z + echo DEVICE_TYPE=
2025-07-17T07:58:50.3852270Z ##[group]Run set -eux
2025-07-17T07:58:50.3852450Z set -eux
2025-07-17T07:58:50.3852620Z 
2025-07-17T07:58:50.3852780Z if [[ -z "${GITHUB_TOKEN}" ]]; then
2025-07-17T07:58:50.3853020Z   echo "Missing github-token input"
2025-07-17T07:58:50.3853270Z   exit 1
2025-07-17T07:58:50.3853410Z fi
2025-07-17T07:58:50.3865360Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T07:58:50.3865600Z env:
2025-07-17T07:58:50.3865760Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:50.3865970Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:50.3866170Z   TEST_CONFIG: default
2025-07-17T07:58:50.3866350Z   SHARD_NUMBER: 1
2025-07-17T07:58:50.3866510Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:50.3866680Z   PR_BODY: 
2025-07-17T07:58:50.3866910Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:50.3867190Z   DEVICE_NAME: 
2025-07-17T07:58:50.3867340Z   DEVICE_TYPE: 
2025-07-17T07:58:50.3867740Z   GITHUB_TOKEN: ***
2025-07-17T07:58:50.3867890Z ##[endgroup]
2025-07-17T07:58:50.4104980Z + [[ -z *** ]]
2025-07-17T07:58:50.4186710Z ##[group]Run pytorch/test-infra/.github/actions/get-workflow-job-id@main
2025-07-17T07:58:50.4187030Z with:
2025-07-17T07:58:50.4187280Z   github-token: ***
2025-07-17T07:58:50.4187470Z env:
2025-07-17T07:58:50.4187630Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:50.4188020Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:50.4188250Z   TEST_CONFIG: default
2025-07-17T07:58:50.4188440Z   SHARD_NUMBER: 1
2025-07-17T07:58:50.4188730Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:50.4188910Z   PR_BODY: 
2025-07-17T07:58:50.4189150Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:50.4189420Z   DEVICE_NAME: 
2025-07-17T07:58:50.4189580Z   DEVICE_TYPE: 
2025-07-17T07:58:50.4189730Z ##[endgroup]
2025-07-17T07:58:50.4200470Z ##[group]Run set -eux
2025-07-17T07:58:50.4200640Z set -eux
2025-07-17T07:58:50.4200780Z 
2025-07-17T07:58:50.4201110Z python3 "${GITHUB_ACTION_PATH}/../../scripts/get_workflow_job_id.py" "${GITHUB_RUN_ID}" "${RUNNER_NAME}"
2025-07-17T07:58:50.4213170Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T07:58:50.4213400Z env:
2025-07-17T07:58:50.4213650Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:50.4213840Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:50.4214050Z   TEST_CONFIG: default
2025-07-17T07:58:50.4214240Z   SHARD_NUMBER: 1
2025-07-17T07:58:50.4214410Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:50.4214560Z   PR_BODY: 
2025-07-17T07:58:50.4214800Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:50.4215080Z   DEVICE_NAME: 
2025-07-17T07:58:50.4215230Z   DEVICE_TYPE: 
2025-07-17T07:58:50.4215550Z   GITHUB_TOKEN: ***
2025-07-17T07:58:50.4215730Z ##[endgroup]
2025-07-17T07:58:50.4447590Z + python3 /Users/ec2-user/runner/_work/_actions/pytorch/test-infra/main/.github/actions/get-workflow-job-id/../../scripts/get_workflow_job_id.py 16337959945 i-06ffcdff1c2e10d08
2025-07-17T07:58:51.3014830Z setting job-id=46154244367
2025-07-17T07:58:51.3119300Z setting job-name=macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)
2025-07-17T07:58:51.3246370Z ##[group]Run set -eux
2025-07-17T07:58:51.3246790Z set -eux
2025-07-17T07:58:51.3247180Z 
2025-07-17T07:58:51.3247790Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_metadata.py" \
2025-07-17T07:58:51.3248570Z   --schema-version "${SCHEMA_VERSION}" \
2025-07-17T07:58:51.3249170Z   --repo "${REPO}" \
2025-07-17T07:58:51.3249700Z   --head-branch "${HEAD_BRANCH}" \
2025-07-17T07:58:51.3250240Z   --head-sha "${HEAD_SHA}" \
2025-07-17T07:58:51.3250830Z   --workflow-id "${WORKFLOW_RUN_ID}" \
2025-07-17T07:58:51.3251370Z   --run-attempt "${RUN_ATTEMPT}" \
2025-07-17T07:58:51.3251820Z   --job-id "${JOB_ID}" \
2025-07-17T07:58:51.3252280Z   --job-name "${JOB_NAME}"
2025-07-17T07:58:51.3276790Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T07:58:51.3277380Z env:
2025-07-17T07:58:51.3277760Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:51.3278250Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:51.3278750Z   TEST_CONFIG: default
2025-07-17T07:58:51.3279180Z   SHARD_NUMBER: 1
2025-07-17T07:58:51.3279580Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:51.3279950Z   PR_BODY: 
2025-07-17T07:58:51.3280520Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:51.3281190Z   DEVICE_NAME: 
2025-07-17T07:58:51.3281580Z   DEVICE_TYPE: 
2025-07-17T07:58:51.3281960Z   SCHEMA_VERSION: v3
2025-07-17T07:58:51.3282390Z   REPO: pytorch/pytorch
2025-07-17T07:58:51.3282820Z   HEAD_BRANCH: refs/heads/main
2025-07-17T07:58:51.3283400Z   HEAD_SHA: a38f433be2e94a64b095a44ba39879d02d0c2316
2025-07-17T07:58:51.3284000Z   WORKFLOW_RUN_ID: 16337959945
2025-07-17T07:58:51.3284430Z   RUN_ATTEMPT: 1
2025-07-17T07:58:51.3284810Z   JOB_ID: 46154244367
2025-07-17T07:58:51.3285430Z   JOB_NAME: macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)
2025-07-17T07:58:51.3286080Z ##[endgroup]
2025-07-17T07:58:51.3708050Z + python3 /Users/ec2-user/runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_metadata.py --schema-version v3 --repo pytorch/pytorch --head-branch refs/heads/main --head-sha a38f433be2e94a64b095a44ba39879d02d0c2316 --workflow-id 16337959945 --run-attempt 1 --job-id 46154244367 --job-name 'macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)'
2025-07-17T07:58:51.4020290Z ##[group]Run set -eux
2025-07-17T07:58:51.4020490Z set -eux
2025-07-17T07:58:51.4020650Z 
2025-07-17T07:58:51.4020930Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_runners_info.py"
2025-07-17T07:58:51.4032580Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T07:58:51.4032850Z env:
2025-07-17T07:58:51.4033000Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:51.4033200Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:51.4033390Z   TEST_CONFIG: default
2025-07-17T07:58:51.4033570Z   SHARD_NUMBER: 1
2025-07-17T07:58:51.4033720Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:51.4033880Z   PR_BODY: 
2025-07-17T07:58:51.4034110Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:51.4034470Z   DEVICE_NAME: 
2025-07-17T07:58:51.4034630Z   DEVICE_TYPE: 
2025-07-17T07:58:51.4034800Z ##[endgroup]
2025-07-17T07:58:51.4265720Z + python3 /Users/ec2-user/runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_runners_info.py
2025-07-17T07:58:52.3391920Z ##[group]Run set -eux
2025-07-17T07:58:52.3392120Z set -eux
2025-07-17T07:58:52.3392290Z 
2025-07-17T07:58:52.3392470Z # TODO (huydhn): Implement this part
2025-07-17T07:58:52.3392740Z echo "dependencies={}" >> "${GITHUB_OUTPUT}"
2025-07-17T07:58:52.3405370Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T07:58:52.3405630Z env:
2025-07-17T07:58:52.3405780Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:52.3405990Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:52.3406230Z   TEST_CONFIG: default
2025-07-17T07:58:52.3406410Z   SHARD_NUMBER: 1
2025-07-17T07:58:52.3406610Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:52.3406790Z   PR_BODY: 
2025-07-17T07:58:52.3407040Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:52.3407330Z   DEVICE_NAME: 
2025-07-17T07:58:52.3407480Z   DEVICE_TYPE: 
2025-07-17T07:58:52.3407650Z ##[endgroup]
2025-07-17T07:58:52.3643890Z + echo 'dependencies={}'
2025-07-17T07:58:52.3669270Z ##[group]Run set -eux
2025-07-17T07:58:52.3669480Z set -eux
2025-07-17T07:58:52.3669630Z 
2025-07-17T07:58:52.3669830Z if [[ ! -d "${BENCHMARK_RESULTS_DIR}" ]]; then
2025-07-17T07:58:52.3670160Z   echo "${BENCHMARK_RESULTS_DIR} does not exist, skipping"
2025-07-17T07:58:52.3670620Z   # We don't want the job to fail if the directory doesn't exist
2025-07-17T07:58:52.3670910Z   exit 0
2025-07-17T07:58:52.3671090Z fi
2025-07-17T07:58:52.3671240Z 
2025-07-17T07:58:52.3671430Z if [[ "${DRY_RUN}" == "true" ]]; then
2025-07-17T07:58:52.3671800Z   python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \
2025-07-17T07:58:52.3672200Z     --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \
2025-07-17T07:58:52.3672540Z     --metadata "${BENCHMARK_METADATA}" \
2025-07-17T07:58:52.3672870Z     --runners "${RUNNER_INFO}" \
2025-07-17T07:58:52.3673110Z     --dependencies "${DEPENDENCIES}" \
2025-07-17T07:58:52.3673380Z     --dry-run
2025-07-17T07:58:52.3673570Z else
2025-07-17T07:58:52.3673830Z   python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \
2025-07-17T07:58:52.3674210Z     --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \
2025-07-17T07:58:52.3674540Z     --metadata "${BENCHMARK_METADATA}" \
2025-07-17T07:58:52.3674780Z     --runners "${RUNNER_INFO}" \
2025-07-17T07:58:52.3675030Z     --dependencies "${DEPENDENCIES}"
2025-07-17T07:58:52.3675260Z fi
2025-07-17T07:58:52.3687640Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T07:58:52.3687910Z env:
2025-07-17T07:58:52.3688250Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:52.3688470Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:52.3688690Z   TEST_CONFIG: default
2025-07-17T07:58:52.3688990Z   SHARD_NUMBER: 1
2025-07-17T07:58:52.3689160Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:52.3689320Z   PR_BODY: 
2025-07-17T07:58:52.3689560Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:52.3689850Z   DEVICE_NAME: 
2025-07-17T07:58:52.3690000Z   DEVICE_TYPE: 
2025-07-17T07:58:52.3690190Z   BENCHMARK_RESULTS_DIR: test/test-reports
2025-07-17T07:58:52.3690410Z   DRY_RUN: false
2025-07-17T07:58:52.3691160Z   BENCHMARK_METADATA: {"timestamp": 1752739131, "schema_version": "v3", "name": "macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "a38f433be2e94a64b095a44ba39879d02d0c2316", "workflow_id": 16337959945, "run_attempt": 1, "job_id": 46154244367}
2025-07-17T07:58:52.3692240Z   RUNNER_INFO: [{"cpu_info": "arm", "cpu_count": 8, "avail_mem_in_gb": 16, "extra_info": {"hostname": "ip-10-0-1-119.ec2.internal"}, "name": "", "type": ""}]
2025-07-17T07:58:52.3692650Z   DEPENDENCIES: {}
2025-07-17T07:58:52.3692800Z ##[endgroup]
2025-07-17T07:58:52.3925130Z + [[ ! -d test/test-reports ]]
2025-07-17T07:58:52.3925440Z + [[ false == \t\r\u\e ]]
2025-07-17T07:58:52.3927790Z + python3 /Users/ec2-user/runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py --benchmark-results-dir test/test-reports --metadata '{"timestamp": 1752739131, "schema_version": "v3", "name": "macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "a38f433be2e94a64b095a44ba39879d02d0c2316", "workflow_id": 16337959945, "run_attempt": 1, "job_id": 46154244367}' --runners '[{"cpu_info": "arm", "cpu_count": 8, "avail_mem_in_gb": 16, "extra_info": {"hostname": "ip-10-0-1-119.ec2.internal"}, "name": "", "type": ""}]' --dependencies '{}'
2025-07-17T07:58:52.4897280Z /Users/ec2-user/runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'test_ci_sanity_check_fail'}, {'test_file': 'test_openreg'}, {'test_file': 'higher_order_ops/test_invoke_subgraph'}, {'test_file': 'test_dataloader'}, {'test_file': 'export/test_torchbind'}, {'test_file': 'test_fake_tensor'}, {'test_file': 'test_quantization'}, {'test_file': 'export/test_export_with_inline_and_install'}, {'test_file': 'dynamo/test_inline_and_install'}, {'test_file': 'dynamo/test_install_free_tensors'}, {'test_file': 'functorch/test_eager_transforms'}, {'test_file': 'test_linalg'}, {'test_file': 'inductor/test_torchinductor_codegen_dynamic_shapes'}, {'test_file': 'functorch/test_ops'}, {'test_file': 'test_namedtuple_return_api'}, {'test_file': 'functorch/test_vmap'}, {'test_file': 'test_nestedtensor'}, {'test_file': 'inductor/test_torchinductor_dynamic_shapes'}, {'test_file': 'test_nn'}, {'test_file': 'inductor/test_aot_inductor_arrayref'}, {'test_file': 'test_transformers'}, {'test_file': 'test_binary_ufuncs'}, {'test_file': 'functorch/test_aotdispatch'}, {'test_file': 'test_foreach'}, {'test_file': 'test_package'}, {'test_file': 'inductor/test_provenance_tracing'}, {'test_file': 'test_decomp'}, {'test_file': 'test_autoload'}, {'test_file': 'export/test_retraceability'}, {'test_file': 'test_utils_config_module'}, {'test_file': 'test_mkl_verbose'}, {'test_file': 'export/test_export_strict'}, {'test_file': 'test_spectral_ops'}, {'test_file': 'distributions/test_distributions'}, {'test_file': 'inductor/test_triton_extension_backend'}, {'test_file': 'export/test_unflatten_training_ir'}, {'test_file': 'dynamo/test_deque_reconstruct'}, {'test_file': 'inductor/test_inductor_utils'}, {'test_file': 'test_license'}, {'test_file': 'inductor/test_cpp_wrapper_hipify'}, {'test_file': 'test_jit_fuser_te'}, {'test_file': 'export/test_export_training_ir_to_run_decomp'}, {'test_file': 'inductor/test_external_callables'}, {'test_file': 'inductor/test_triton_syntax'}, {'test_file': 'test_mkldnn_verbose'}, {'test_file': 'export/test_serdes'}, {'test_file': 'inductor/test_extension_backend'}, {'test_file': 'dynamo/test_recompiles'}, {'test_file': 'inductor/test_smoke'}, {'test_file': 'test_comparison_utils'}, {'test_file': 'test_ops'}, {'test_file': 'dynamo/test_base_output'}, {'test_file': 'inductor/test_ck_backend'}, {'test_file': 'inductor/test_kernel_benchmark'}, {'test_file': 'inductor/test_inductor_annotations'}, {'test_file': 'inductor/test_triton_cpu_backend'}, {'test_file': 'export/test_functionalized_assertions'}, {'test_file': 'inductor/test_analysis'}, {'test_file': 'inductor/test_b2b_gemm'}, {'test_file': 'inductor/test_cpu_cpp_wrapper'}, {'test_file': 'inductor/test_debug_trace'}, {'test_file': 'inductor/test_compiled_autograd'}, {'test_file': 'inductor/test_memory_planning'}, {'test_file': 'typing/test_python_operators'}, {'test_file': 'torch_np/test_nep50_examples'}, {'test_file': 'test_extension_utils'}, {'test_file': 'test_cpp_api_parity'}, {'test_file': 'inductor/test_best_config'}, {'test_file': 'inductor/test_torchinductor_strided_blocks'}, {'test_file': 'inductor/test_compile_worker'}, {'test_file': 'test_ops_jit'}, {'test_file': 'dynamo/test_skip_guard_eval_unsafe'}, {'test_file': 'functorch/test_ac_logging'}, {'test_file': 'test_custom_ops'}, {'test_file': 'inductor/test_triton_wrapper'}, {'test_file': 'test_ao_sparsity'}, {'test_file': 'inductor/test_aot_inductor_custom_ops'}, {'test_file': 'torch_np/test_binary_ufuncs'}, {'test_file': 'inductor/test_cutlass_backend'}, {'test_file': 'inductor/test_aot_inductor_package'}, {'test_file': 'test_hop_infra'}, {'test_file': 'inductor/test_flex_decoding'}, {'test_file': 'torch_np/test_unary_ufuncs'}, {'test_file': 'dynamo/test_nops'}, {'test_file': 'inductor/test_move_constructors_to_cuda'}, {'test_file': 'backends/xeon/test_launch'}, {'test_file': 'inductor/test_triton_kernels'}, {'test_file': 'inductor/test_async_compile'}, {'test_file': 'torch_np/numpy_tests/linalg/test_linalg'}, {'test_file': 'test_cpp_extensions_open_device_registration'}, {'test_file': 'inductor/test_pad_mm'}, {'test_file': 'dynamo/test_skip_non_tensor'}, {'test_file': 'dynamo/test_interop'}, {'test_file': 'inductor/test_torchinductor'}, {'test_file': 'test_file_check'}, {'test_file': 'export/test_tree_utils'}, {'test_file': 'inductor/test_indexing'}, {'test_file': 'dynamo/test_buffers_override'}, {'test_file': 'test_appending_byte_serializer'}, {'test_file': 'dynamo/test_resume'}, {'test_file': 'inductor/test_xpu_basic'}, {'test_file': 'inductor/test_coordinate_descent_tuner'}, {'test_file': 'inductor/test_aot_inductor'}, {'test_file': 'inductor/test_combo_kernels'}, {'test_file': 'torch_np/test_dtype'}, {'test_file': 'inductor/test_metrics'}, {'test_file': 'test_proxy_tensor'}, {'test_file': 'test_transformers_privateuse1'}, {'test_file': 'inductor/test_minifier_utils'}, {'test_file': 'dynamo/test_modules'}, {'test_file': 'inductor/test_flex_attention'}, {'test_file': 'export/test_cpp_serdes'}, {'test_file': 'inductor/test_cudagraph_trees'}, {'test_file': 'inductor/test_kernel_optimization'}, {'test_file': 'xpu/test_fusion'}, {'test_file': 'dynamo/test_sdpa'}, {'test_file': 'dynamo/test_fx_passes_pre_grad'}, {'test_file': 'inductor/test_foreach'}, {'test_file': 'dynamo/test_global'}, {'test_file': 'dynamo/test_utils'}, {'test_file': 'inductor/test_fp8'}, {'test_file': 'dynamo/test_frame_init'}, {'test_file': 'dynamo/test_graph_region_tracker'}, {'test_file': 'profiler/test_kineto'}, {'test_file': 'test_fx_experimental'}, {'test_file': 'test_flop_counter'}, {'test_file': 'test_typing'}, {'test_file': 'inductor/test_fx_fusion'}, {'test_file': 'test_meta'}, {'test_file': 'test_functionalization'}, {'test_file': 'inductor/test_op_completeness'}, {'test_file': 'test_utils_filelock'}, {'test_file': 'dynamo/test_pre_dispatch'}, {'test_file': 'inductor/test_gpu_cpp_wrapper'}, {'test_file': 'export/test_export'}, {'test_file': 'export/test_tools'}, {'test_file': 'dynamo/test_metrics_context'}, {'test_file': 'test_fx'}, {'test_file': 'inductor/test_torchinductor_opinfo'}, {'test_file': 'inductor/test_autoheuristic'}, {'test_file': 'inductor/test_static_cuda_launcher'}, {'test_file': 'inductor/test_utils'}, {'test_file': 'dynamo/test_subgraphs'}, {'test_file': 'cpp_extensions/python_agnostic_extension/test/test_python_agnostic'}, {'test_file': 'dynamo/test_reconstruct'}, {'test_file': 'inductor/test_subgraph_choice'}, {'test_file': 'test_show_pickle'}, {'test_file': 'inductor/test_mkldnn_pattern_matcher'}, {'test_file': 'dynamo/test_dicts'}, {'test_file': 'inductor/test_cuda_repro'}, {'test_file': 'dynamo/test_dynamic_shapes'}, {'test_file': 'test_pytree'}, {'test_file': 'inductor/test_compile_subprocess'}, {'test_file': 'dynamo/test_list'}, {'test_file': 'higher_order_ops/test_with_effects'}, {'test_file': 'inductor/test_benchmark_fusion'}, {'test_file': 'dynamo/test_fx_graph_runnable'}, {'test_file': 'inductor/test_graph_transform_observer'}, {'test_file': 'test_openmp'}, {'test_file': 'inductor/test_compiled_optimizers'}, {'test_file': 'dynamo/test_functions'}, {'test_file': 'inductor/test_minifier'}, {'test_file': 'torch_np/test_ufuncs_basic'}, {'test_file': 'inductor/test_ordered_set'}, {'test_file': 'test_compile_benchmark_util'}, {'test_file': 'export/test_passes'}, {'test_file': 'inductor/test_helion_kernels'}, {'test_file': 'inductor/test_aot_inductor_utils'}, {'test_file': 'torch_np/test_random'}, {'test_file': 'inductor/test_alignment'}, {'test_file': 'test_namedtensor'}, {'test_file': 'export/test_package'}, {'test_file': 'dynamo/test_config'}, {'test_file': 'inductor/test_cudacodecache'}, {'test_file': 'inductor/test_codecache'}, {'test_file': 'torch_np/numpy_tests/core/test_scalarinherit'}, {'test_file': 'export/test_upgrader'}, {'test_file': 'dynamo/test_compile'}, {'test_file': 'inductor/test_quantization'}, {'test_file': 'dynamo/test_after_aot'}, {'test_file': 'inductor/test_max_autotune'}, {'test_file': 'test_hub'}, {'test_file': 'dynamo/test_autograd_function'}, {'test_file': 'export/test_db'}, {'test_file': 'inductor/test_inplace_padding'}, {'test_file': 'test_optim'}, {'test_file': 'inductor/test_profiler'}, {'test_file': 'inductor/test_cudagraph_trees_expandable_segments'}, {'test_file': 'test_utils'}, {'test_file': 'inductor/test_cooperative_reductions'}, {'test_file': 'inductor/test_cpu_select_algorithm'}, {'test_file': 'inductor/test_fuzzer'}, {'test_file': 'test_per_overload_api'}, {'test_file': 'export/test_schema'}, {'test_file': 'test_expanded_weights'}, {'test_file': 'lazy/test_bindings'}, {'test_file': 'inductor/test_codegen_triton'}, {'test_file': 'inductor/test_triton_heuristics'}, {'test_file': 'inductor/test_pattern_matcher'}, {'test_file': 'dynamo/test_repros'}, {'test_file': 'dynamo/test_cudagraphs_expandable_segments'}, {'test_file': 'dynamo/test_view'}, {'test_file': 'test_native_functions'}, {'test_file': 'inductor/test_inductor_scheduler'}, {'test_file': 'test_type_hints'}, {'test_file': 'inductor/test_custom_post_grad_passes'}, {'test_file': 'dynamo/test_pgo'}, {'test_file': 'dynamo/test_export'}, {'test_file': 'inductor/test_group_batch_fusion'}, {'test_file': 'test_import_stats'}, {'test_file': 'inductor/test_split_cat_fx_passes'}, {'test_file': 'dynamo/test_guard_serialization'}, {'test_file': 'test_module_tracker'}, {'test_file': 'inductor/test_halide'}, {'test_file': 'test_cuda_expandable_segments'}, {'test_file': 'test_fx_passes'}, {'test_file': 'inductor/test_minifier_isolate'}, {'test_file': 'inductor/test_online_softmax'}, {'test_file': 'dynamo/test_unittest'}, {'test_file': 'inductor/test_op_dtype_prop'}, {'test_file': 'test_logging'}, {'test_file': 'test_multiprocessing'}, {'test_file': 'inductor/test_multi_kernel'}, {'test_file': 'torch_np/test_basic'}, {'test_file': 'inductor/test_inplacing_pass'}, {'test_file': 'test_tensorexpr_pybind'}, {'test_file': 'test_tensorexpr'}, {'test_file': 'dynamo/test_model_output'}, {'test_file': 'inductor/test_decompose_mem_bound_mm'}, {'test_file': 'test_complex'}, {'test_file': 'test_jit_disabled'}, {'test_file': 'test_jiterator'}, {'test_file': 'functorch/test_minifier'}, {'test_file': 'inductor/test_custom_lowering'}, {'test_file': 'test_ops_fwd_gradients'}, {'test_file': 'inductor/test_select_algorithm'}, {'test_file': 'inductor/test_block_analysis'}, {'test_file': 'inductor/test_benchmarking'}, {'test_file': 'inductor/test_fxir_backend'}, {'test_file': 'dynamo/test_misc'}, {'test_file': 'export/test_swap'}, {'test_file': 'torch_np/numpy_tests/core/test_einsum'}, {'test_file': 'higher_order_ops/test_invoke_quant'}, {'test_file': 'cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic'}, {'test_file': 'inductor/test_cutlass_evt'}, {'test_file': 'inductor/test_snode_runtime'}, {'test_file': 'test_stateless'}, {'test_file': 'profiler/test_profiler'}, {'test_file': 'test_cpp_extensions_mtia_backend'}, {'test_file': 'inductor/test_control_flow'}, {'test_file': 'inductor/test_perf'}, {'test_file': 'test_numpy_interop'}, {'test_file': 'dynamo/test_export_mutations'}, {'test_file': 'test_legacy_vmap'}, {'test_file': 'nn/test_multihead_attention'}, {'test_file': 'inductor/test_layout_optim'}, {'test_file': 'inductor/test_binary_folding'}, {'test_file': 'inductor/test_scatter_optimization'}, {'test_file': 'test_numba_integration'}, {'test_file': 'inductor/test_torchinductor_codegen_config_overrides'}, {'test_file': 'xpu/test_gemm'}, {'test_file': 'torch_np/numpy_tests/core/test_numeric'}, {'test_file': 'xpu/test_conv'}, {'test_file': 'dynamo/test_backward_higher_order_ops'}, {'test_file': 'dynamo/test_optimizers'}, {'test_file': 'test_weak'}, {'test_file': 'dynamo/test_graph_deduplication'}, {'test_file': 'dynamo/test_sets'}, {'test_file': 'distributions/test_constraints'}, {'test_file': 'test_cpp_extensions_stream_and_event'}, {'test_file': 'test_tensorboard'}, {'test_file': 'inductor/test_split_cat_fx_aten_passes'}, {'test_file': 'dynamo/test_structured_trace'}, {'test_file': 'profiler/test_cpp_thread'}, {'test_file': 'dynamo/test_decorators'}, {'test_file': 'dynamo/test_debug_utils'}, {'test_file': 'functorch/test_ac_knapsack'}, {'test_file': 'functorch/test_ac'}, {'test_file': 'dynamo/test_base_hop'}, {'test_file': 'dynamo/test_modes'}, {'test_file': 'inductor/test_memory'}, {'test_file': 'inductor/test_inductor_freezing'}, {'test_file': 'dynamo/test_profiler'}, {'test_file': 'dynamo/test_sources'}, {'test_file': 'dynamo/test_cudagraphs'}, {'test_file': 'inductor/test_mps_basic'}, {'test_file': 'inductor/test_config'}, {'test_file': 'test_datapipe'}, {'test_file': 'functorch/test_logging'}, {'test_file': 'dynamo/test_flat_apply'}, {'test_file': 'torch_np/test_indexing'}, {'test_file': 'dynamo/test_deviceguard'}, {'test_file': 'inductor/test_dependencies'}, {'test_file': 'test_content_store'}, {'test_file': 'export/test_unflatten'}, {'test_file': 'lazy/test_step_closures'}, {'test_file': 'test_dispatch'}, {'test_file': 'inductor/test_fused_attention'}, {'test_file': 'test_ops_gradients'}, {'test_file': 'dynamo/test_python_dispatcher'}, {'test_file': 'test_pruning_op'}, {'test_file': 'test_set_default_mobile_cpu_allocator'}, {'test_file': 'test_monitor'}, {'test_file': 'dynamo/test_verify_correctness'}, {'test_file': 'dynamo/test_logging'}, {'test_file': 'dynamo/test_package'}, {'test_file': 'dynamo/test_backends'}, {'test_file': 'inductor/test_torchbind'}, {'test_file': 'export/test_serialize'}, {'test_file': 'test_segment_reductions'}, {'test_file': 'inductor/test_padding'}, {'test_file': 'inductor/test_auto_functionalize'}, {'test_file': 'test_out_dtype_op'}, {'test_file': 'export/test_hop'}, {'test_file': 'dynamo/test_higher_order_ops'}, {'test_file': 'inductor/test_efficient_conv_bn_eval'}, {'test_file': 'test_cuda_sanitizer'}, {'test_file': 'test_model_exports_to_core_aten'}, {'test_file': 'test_mkldnn'}, {'test_file': 'torch_np/numpy_tests/lib/test_function_base'}, {'test_file': 'lazy/test_functionalization'}, {'test_file': 'test_jit'}, {'test_file': 'dynamo/test_aot_autograd_cache'}, {'test_file': 'dynamo/test_einops'}, {'test_file': 'dynamo/test_compiler_bisector'}, {'test_file': 'test_python_dispatch'}, {'test_file': 'test_modules'}, {'test_file': 'nn/test_lazy_modules'}, {'test_file': 'optim/test_lrscheduler'}, {'test_file': 'dynamo/test_trace_rules'}, {'test_file': 'torch_np/numpy_tests/lib/test_type_check'}, {'test_file': 'test_itt'}, {'test_file': 'inductor/test_cpu_repro'}, {'test_file': 'dynamo/test_aot_autograd'}, {'test_file': 'dynamo/test_activation_checkpointing'}, {'test_file': 'test_autograd_fallback'}, {'test_file': 'test_bundled_inputs'}, {'test_file': 'inductor/test_unbacked_symints'}, {'test_file': 'dynamo/test_error_messages'}, {'test_file': 'test_cuda'}, {'test_file': 'inductor/test_mmdecomp'}, {'test_file': 'inductor/test_loop_ordering'}, {'test_file': 'nn/test_pruning'}, {'test_file': 'test_fx_reinplace_pass'}, {'test_file': 'test_cuda_nvml_based_avail'}, {'test_file': 'torch_np/test_function_base'}, {'test_file': 'test_tensor_creation_ops'}, {'test_file': 'test_accelerator'}, {'test_file': 'export/test_experimental'}, {'test_file': 'dynamo/test_callback'}, {'test_file': 'test_functionalization_of_rng_ops'}, {'test_file': 'test_public_bindings'}, {'test_file': 'export/test_converter'}, {'test_file': 'torch_np/numpy_tests/core/test_indexing'}, {'test_file': 'dynamo/test_unspec'}, {'test_file': 'test_schema_check'}, {'test_file': 'dynamo/test_exceptions'}, {'test_file': 'test_cuda_trace'}, {'test_file': 'dynamo/test_reorder_logs'}, {'test_file': 'torch_np/numpy_tests/lib/test_histograms'}, {'test_file': 'benchmark_utils/test_benchmark_utils'}, {'test_file': 'test_masked'}, {'test_file': 'test_type_info'}, {'test_file': 'dynamo/test_torchrec'}, {'test_file': 'dynamo/test_exc'}, {'test_file': 'test_jit_llga_fuser'}, {'test_file': 'test_subclass'}, {'test_file': 'dynamo/test_hooks'}, {'test_file': 'export/test_pass_infra'}, {'test_file': 'dynamo/test_input_attr_tracking'}, {'test_file': 'nn/test_parametrization'}, {'test_file': 'test_matmul_cuda'}, {'test_file': 'dynamo/test_minifier'}, {'test_file': 'export/test_lift_unlift'}, {'test_file': 'test_autograd'}, {'test_file': 'dynamo/test_precompile_context'}, {'test_file': 'dynamo/test_bytecode_utils'}, {'test_file': 'test_dlpack'}, {'test_file': 'optim/test_swa_utils'}, {'test_file': 'test_sympy_utils'}, {'test_file': 'test_sparse_semi_structured'}, {'test_file': 'functorch/test_control_flow'}, {'test_file': 'lazy/test_ts_opinfo'}, {'test_file': 'test_maskedtensor'}, {'test_file': 'torch_np/numpy_tests/core/test_scalarmath'}, {'test_file': 'torch_np/numpy_tests/core/test_getlimits'}, {'test_file': 'dynamo/test_recompile_ux'}, {'test_file': 'dynamo/test_ctx_manager'}, {'test_file': 'test_autocast'}, {'test_file': 'torch_np/numpy_tests/core/test_dtype'}, {'test_file': 'inductor/test_compile'}, {'test_file': 'inductor/test_distributed_patterns'}, {'test_file': 'functorch/test_vmap_registrations'}, {'test_file': 'dynamo/test_fake_distributed'}, {'test_file': 'dynamo/test_comptime'}, {'test_file': 'torch_np/numpy_tests/core/test_shape_base'}, {'test_file': 'test_testing'}, {'test_file': 'nn/test_packed_sequence'}, {'test_file': 'test_futures'}, {'test_file': 'test_cpp_extensions_jit'}, {'test_file': 'export/test_sparse'}, {'test_file': 'optim/test_optim'}, {'test_file': 'export/test_verifier'}, {'test_file': 'torch_np/numpy_tests/fft/test_pocketfft'}, {'test_file': 'test_serialization'}, {'test_file': 'dynamo/test_generator'}, {'test_file': 'test_functional_optim'}, {'test_file': 'test_cuda_primary_ctx'}, {'test_file': 'nn/test_embedding'}, {'test_file': 'nn/test_dropout'}, {'test_file': 'test_dynamic_shapes'}, {'test_file': 'torch_np/numpy_tests/fft/test_helper'}, {'test_file': 'torch_np/test_ndarray_methods'}, {'test_file': 'test_torch'}, {'test_file': 'torch_np/numpy_tests/lib/test_twodim_base'}, {'test_file': 'test_vulkan'}, {'test_file': 'torch_np/numpy_tests/lib/test_shape_base_'}, {'test_file': 'test_mkldnn_fusion'}, {'test_file': 'dynamo/test_guard_manager'}, {'test_file': 'test_shape_ops'}, {'test_file': 'torch_np/test_scalars_0D_arrays'}, {'test_file': 'export/test_draft_export'}, {'test_file': 'dynamo/test_subclasses'}, {'test_file': 'nn/test_load_state_dict'}, {'test_file': 'test_indexing'}, {'test_file': 'torch_np/numpy_tests/lib/test_index_tricks'}, {'test_file': 'torch_np/numpy_tests/core/test_dlpack'}, {'test_file': 'torch_np/numpy_tests/lib/test_arraypad'}, {'test_file': 'lazy/test_debug_util'}, {'test_file': 'test_native_mha'}, {'test_file': 'test_sort_and_select'}, {'test_file': 'test_xnnpack_integration'}, {'test_file': 'test_sparse_csr'}, {'test_file': 'lazy/test_generator'}, {'test_file': 'test_functional_autograd_benchmark'}, {'test_file': 'torch_np/numpy_tests/core/test_scalar_methods'}, {'test_file': 'test_multiprocessing_spawn'}, {'test_file': 'nn/test_module_hooks'}, {'test_file': 'torch_np/numpy_tests/lib/test_arraysetops'}, {'test_file': 'torch_np/numpy_tests/core/test_numerictypes'}, {'test_file': 'test_view_ops'}, {'test_file': 'test_scatter_gather_ops'}, {'test_file': 'nn/test_pooling'}, {'test_file': 'profiler/test_memory_profiler'}, {'test_file': 'test_overrides'}, {'test_file': 'test_unary_ufuncs'}, {'test_file': 'nn/test_init'}, {'test_file': 'test_function_schema'}, {'test_file': 'test_cuda_multigpu'}, {'test_file': 'test_mobile_optimizer'}, {'test_file': 'torch_np/numpy_tests/core/test_scalar_ctors'}, {'test_file': 'test_sparse'}, {'test_file': 'torch_np/test_reductions'}, {'test_file': 'profiler/test_profiler_tree'}, {'test_file': 'nn/test_convolution'}, {'test_file': 'test_type_promotion'}, {'test_file': 'dynamo/test_python_autograd'}, {'test_file': 'test_jit_autocast'}, {'test_file': 'profiler/test_record_function'}, {'test_file': 'test_prims'}, {'test_file': 'lazy/test_reuse_ir'}, {'test_file': 'test_reductions'}, {'test_file': 'profiler/test_execution_trace'}, {'test_file': 'profiler/test_torch_tidy'}, {'test_file': 'doctests'}, {'test_file': 'test_autoload_disable'}, {'test_file': 'test_autoload_enable'}, {'test_file': 'test_cpp_extensions_aot_ninja'}, {'test_file': 'test_cpp_extensions_aot_no_ninja'}, {'test_file': 'test_rename_privateuse1_to_existing_device'}], 'excluded': []} from test/test-reports/td_exclusions-b30565d148a4c0c095a1.json is not a benchmark record, skipping
2025-07-17T07:58:52.4949590Z   warn(f"{result} from {filepath} is not a benchmark record, skipping")
2025-07-17T07:58:52.5025350Z Prepare all required actions
2025-07-17T07:58:52.5025630Z Getting action download info
2025-07-17T07:58:52.6055880Z ##[group]Run ./.github/actions/upload-utilization-stats
2025-07-17T07:58:52.6056270Z with:
2025-07-17T07:58:52.6056470Z   job_id: 46154244367
2025-07-17T07:58:52.6056860Z   job_name: macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)
2025-07-17T07:58:52.6057310Z   workflow_name: trunk
2025-07-17T07:58:52.6057620Z   workflow_run_id: 16337959945
2025-07-17T07:58:52.6057920Z   workflow_attempt: 1
2025-07-17T07:58:52.6058210Z   local_path: usage_log.txt
2025-07-17T07:58:52.6058480Z env:
2025-07-17T07:58:52.6058710Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:52.6059030Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:52.6059370Z   TEST_CONFIG: default
2025-07-17T07:58:52.6059610Z   SHARD_NUMBER: 1
2025-07-17T07:58:52.6059830Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:52.6060100Z   PR_BODY: 
2025-07-17T07:58:52.6060480Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:52.6060920Z   DEVICE_NAME: 
2025-07-17T07:58:52.6061160Z   DEVICE_TYPE: 
2025-07-17T07:58:52.6061400Z ##[endgroup]
2025-07-17T07:58:52.6079630Z ##[group]Run echo "workflow_id: 16337959945"
2025-07-17T07:58:52.6080010Z echo "workflow_id: 16337959945"
2025-07-17T07:58:52.6080370Z echo "workflow_attempt: 1"
2025-07-17T07:58:52.6080700Z echo "workflow_Name: trunk"
2025-07-17T07:58:52.6081010Z echo "job_id: 46154244367"
2025-07-17T07:58:52.6081490Z echo "job_name:  macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)"
2025-07-17T07:58:52.6082030Z echo "artifact_prefix: "
2025-07-17T07:58:52.6082360Z python3 --version
2025-07-17T07:58:52.6101410Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T07:58:52.6101750Z env:
2025-07-17T07:58:52.6101930Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:52.6102190Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:52.6102480Z   TEST_CONFIG: default
2025-07-17T07:58:52.6102900Z   SHARD_NUMBER: 1
2025-07-17T07:58:52.6103100Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:52.6103310Z   PR_BODY: 
2025-07-17T07:58:52.6103610Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:52.6103970Z   DEVICE_NAME: 
2025-07-17T07:58:52.6104170Z   DEVICE_TYPE: 
2025-07-17T07:58:52.6104360Z ##[endgroup]
2025-07-17T07:58:52.6386830Z workflow_id: 16337959945
2025-07-17T07:58:52.6387170Z workflow_attempt: 1
2025-07-17T07:58:52.6387370Z workflow_Name: trunk
2025-07-17T07:58:52.6387580Z job_id: 46154244367
2025-07-17T07:58:52.6387860Z job_name:  macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)
2025-07-17T07:58:52.6388160Z artifact_prefix: 
2025-07-17T07:58:52.6444750Z Python 3.12.11
2025-07-17T07:58:52.6475690Z ##[group]Run nick-fields/retry@v3.0.0
2025-07-17T07:58:52.6475920Z with:
2025-07-17T07:58:52.6476100Z   shell: bash
2025-07-17T07:58:52.6476270Z   timeout_minutes: 5
2025-07-17T07:58:52.6476480Z   max_attempts: 5
2025-07-17T07:58:52.6476690Z   retry_wait_seconds: 30
2025-07-17T07:58:52.6477070Z   command: set -eu
python3 -m pip install python-dateutil==2.8.2 boto3==1.35.42 pandas==2.1.3 dataclasses_json==0.6.7

2025-07-17T07:58:52.6477470Z   polling_interval_seconds: 1
2025-07-17T07:58:52.6477680Z   warning_on_retry: true
2025-07-17T07:58:52.6477870Z   continue_on_error: false
2025-07-17T07:58:52.6478050Z env:
2025-07-17T07:58:52.6478200Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:52.6478410Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:52.6478640Z   TEST_CONFIG: default
2025-07-17T07:58:52.6478850Z   SHARD_NUMBER: 1
2025-07-17T07:58:52.6479010Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:52.6479210Z   PR_BODY: 
2025-07-17T07:58:52.6479460Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:52.6479760Z   DEVICE_NAME: 
2025-07-17T07:58:52.6479920Z   DEVICE_TYPE: 
2025-07-17T07:58:52.6480090Z ##[endgroup]
2025-07-17T07:58:52.9141680Z Collecting python-dateutil==2.8.2
2025-07-17T07:58:52.9161390Z   Using cached python_dateutil-2.8.2-py2.py3-none-any.whl.metadata (8.2 kB)
2025-07-17T07:58:53.0449080Z Collecting boto3==1.35.42
2025-07-17T07:58:53.0471270Z   Using cached boto3-1.35.42-py3-none-any.whl.metadata (6.7 kB)
2025-07-17T07:58:53.1086510Z Collecting pandas==2.1.3
2025-07-17T07:58:53.1102530Z   Using cached pandas-2.1.3-cp312-cp312-macosx_11_0_arm64.whl.metadata (18 kB)
2025-07-17T07:58:53.1226270Z Requirement already satisfied: dataclasses_json==0.6.7 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (0.6.7)
2025-07-17T07:58:53.1231230Z Requirement already satisfied: six>=1.5 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from python-dateutil==2.8.2) (1.17.0)
2025-07-17T07:58:53.1236360Z Requirement already satisfied: botocore<1.36.0,>=1.35.42 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from boto3==1.35.42) (1.35.99)
2025-07-17T07:58:53.1238600Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from boto3==1.35.42) (1.0.1)
2025-07-17T07:58:53.1241430Z Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from boto3==1.35.42) (0.10.4)
2025-07-17T07:58:53.1247220Z Requirement already satisfied: numpy<2,>=1.26.0 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from pandas==2.1.3) (1.26.4)
2025-07-17T07:58:53.1504450Z Collecting pytz>=2020.1 (from pandas==2.1.3)
2025-07-17T07:58:53.1519970Z   Using cached pytz-2025.2-py2.py3-none-any.whl.metadata (22 kB)
2025-07-17T07:58:53.1707460Z Collecting tzdata>=2022.1 (from pandas==2.1.3)
2025-07-17T07:58:53.1722230Z   Using cached tzdata-2025.2-py2.py3-none-any.whl.metadata (1.4 kB)
2025-07-17T07:58:53.1763900Z Requirement already satisfied: marshmallow<4.0.0,>=3.18.0 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from dataclasses_json==0.6.7) (3.26.1)
2025-07-17T07:58:53.1767040Z Requirement already satisfied: typing-inspect<1,>=0.4.0 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from dataclasses_json==0.6.7) (0.9.0)
2025-07-17T07:58:53.1787820Z Requirement already satisfied: urllib3!=2.2.0,<3,>=1.25.4 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from botocore<1.36.0,>=1.35.42->boto3==1.35.42) (1.26.20)
2025-07-17T07:58:53.1796620Z Requirement already satisfied: packaging>=17.0 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses_json==0.6.7) (23.1)
2025-07-17T07:58:53.1830550Z Requirement already satisfied: mypy-extensions>=0.3.0 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (1.1.0)
2025-07-17T07:58:53.1833090Z Requirement already satisfied: typing-extensions>=3.7.4 in /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (4.12.2)
2025-07-17T07:58:53.1886740Z Using cached python_dateutil-2.8.2-py2.py3-none-any.whl (247 kB)
2025-07-17T07:58:53.1921640Z Using cached boto3-1.35.42-py3-none-any.whl (139 kB)
2025-07-17T07:58:53.1945880Z Using cached pandas-2.1.3-cp312-cp312-macosx_11_0_arm64.whl (10.6 MB)
2025-07-17T07:58:53.2235910Z Using cached pytz-2025.2-py2.py3-none-any.whl (509 kB)
2025-07-17T07:58:53.2278960Z Using cached tzdata-2025.2-py2.py3-none-any.whl (347 kB)
2025-07-17T07:58:53.3211960Z Installing collected packages: pytz, tzdata, python-dateutil, pandas, boto3
2025-07-17T07:58:53.4615010Z   Attempting uninstall: python-dateutil
2025-07-17T07:58:53.4635750Z     Found existing installation: python-dateutil 2.9.0.post0
2025-07-17T07:58:53.4667450Z     Uninstalling python-dateutil-2.9.0.post0:
2025-07-17T07:58:53.4675330Z       Successfully uninstalled python-dateutil-2.9.0.post0
2025-07-17T07:58:56.0453610Z   Attempting uninstall: boto3
2025-07-17T07:58:56.0469170Z     Found existing installation: boto3 1.35.33
2025-07-17T07:58:56.0499550Z     Uninstalling boto3-1.35.33:
2025-07-17T07:58:56.0515000Z       Successfully uninstalled boto3-1.35.33
2025-07-17T07:58:56.0942370Z 
2025-07-17T07:58:56.0981310Z Successfully installed boto3-1.35.42 pandas-2.1.3 python-dateutil-2.8.2 pytz-2025.2 tzdata-2025.2
2025-07-17T07:58:56.7313430Z Command completed after 1 attempt(s).
2025-07-17T07:58:56.7425320Z ##[group]Run python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \
2025-07-17T07:58:56.7427110Z python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \
2025-07-17T07:58:56.7428360Z   --workflow-run-id "16337959945" \
2025-07-17T07:58:56.7429000Z   --workflow-name "trunk" \
2025-07-17T07:58:56.7429670Z   --workflow-run-attempt "1" \
2025-07-17T07:58:56.7430430Z   --job-id "46154244367" \
2025-07-17T07:58:56.7431240Z   --job-name "macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)" \
2025-07-17T07:58:56.7432150Z   --local-path "usage_log.txt" \
2025-07-17T07:58:56.7432780Z   --artifact-prefix ""
2025-07-17T07:58:56.7471220Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T07:58:56.7471960Z env:
2025-07-17T07:58:56.7495750Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:56.7496770Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:56.7497380Z   TEST_CONFIG: default
2025-07-17T07:58:56.7497850Z   SHARD_NUMBER: 1
2025-07-17T07:58:56.7498380Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:56.7498880Z   PR_BODY: 
2025-07-17T07:58:56.7499520Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:56.7500320Z   DEVICE_NAME: 
2025-07-17T07:58:56.7500770Z   DEVICE_TYPE: 
2025-07-17T07:58:56.7501190Z ##[endgroup]
2025-07-17T07:58:59.2297640Z Traceback (most recent call last):
2025-07-17T07:58:59.2298360Z   File "<frozen runpy>", line 198, in _run_module_as_main
2025-07-17T07:58:59.2298660Z   File "<frozen runpy>", line 88, in _run_code
2025-07-17T07:58:59.2299210Z   File "/Users/ec2-user/runner/_work/pytorch/pytorch/tools/stats/upload_utilization_stats/upload_utilization_stats.py", line 527, in <module>
2025-07-17T07:58:59.2299720Z     ud.start()
2025-07-17T07:58:59.2300160Z   File "/Users/ec2-user/runner/_work/pytorch/pytorch/tools/stats/upload_utilization_stats/upload_utilization_stats.py", line 222, in start
2025-07-17T07:58:59.2300720Z     segments = self.segment_generator.generate(valid_records)
2025-07-17T07:58:59.2301040Z                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
2025-07-17T07:58:59.2301680Z   File "/Users/ec2-user/runner/_work/pytorch/pytorch/tools/stats/upload_utilization_stats/upload_utilization_stats.py", line 60, in generate
2025-07-17T07:58:59.2302250Z     df[time_col_name] = pd.to_datetime(df[time_col_name], unit="s", utc=True)
2025-07-17T07:58:59.2302570Z                                        ~~^^^^^^^^^^^^^^^
2025-07-17T07:58:59.2303050Z   File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/pandas/core/frame.py", line 3893, in __getitem__
2025-07-17T07:58:59.2303700Z     indexer = self.columns.get_loc(key)
2025-07-17T07:58:59.2303940Z               ^^^^^^^^^^^^^^^^^^^^^^^^^
2025-07-17T07:58:59.2304430Z   File "/Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779/lib/python3.12/site-packages/pandas/core/indexes/range.py", line 418, in get_loc
2025-07-17T07:58:59.2304920Z     raise KeyError(key)
2025-07-17T07:58:59.2305130Z KeyError: 'time'
2025-07-17T07:58:59.2305310Z repo: pytorch/pytorch
2025-07-17T07:58:59.2305540Z Converted Log Model: UtilizationMetadata:
2025-07-17T07:58:59.2306670Z  UtilizationMetadata(level='metadata', workflow_id='16337959945', job_id='46154244367', workflow_name='trunk', job_name='macos-py3-arm64 / test (default, 1, 3, macos-m1-stable)', usage_collect_interval=1.0, data_model_version=1.0, start_at=1752734807, gpu_count=0, cpu_count=8, gpu_type=None, error=None)
2025-07-17T07:58:59.2739030Z ##[error]Process completed with exit code 1.
2025-07-17T07:58:59.2765470Z ##[group]Run if [[ -n "$REINSTALL_BREW_MINICONDA" ]]; then
2025-07-17T07:58:59.2765800Z if [[ -n "$REINSTALL_BREW_MINICONDA" ]]; then
2025-07-17T07:58:59.2766050Z     brew install --cask miniconda
2025-07-17T07:58:59.2766270Z fi
2025-07-17T07:58:59.2778830Z shell: /bin/bash -e -l {0}
2025-07-17T07:58:59.2779000Z env:
2025-07-17T07:58:59.2779160Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:59.2779360Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:59.2779590Z   TEST_CONFIG: default
2025-07-17T07:58:59.2779770Z   SHARD_NUMBER: 1
2025-07-17T07:58:59.2779930Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:59.2780110Z   PR_BODY: 
2025-07-17T07:58:59.2780350Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:59.2780610Z   DEVICE_NAME: 
2025-07-17T07:58:59.2780760Z   DEVICE_TYPE: 
2025-07-17T07:58:59.2780920Z ##[endgroup]
2025-07-17T07:58:59.3097150Z ##[group]Run pytorch/test-infra/.github/actions/check-disk-space@main
2025-07-17T07:58:59.3097460Z with:
2025-07-17T07:58:59.3097630Z   minimum-available-space-in-gb: 6
2025-07-17T07:58:59.3097830Z env:
2025-07-17T07:58:59.3097990Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:59.3098190Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:59.3098410Z   TEST_CONFIG: default
2025-07-17T07:58:59.3098590Z   SHARD_NUMBER: 1
2025-07-17T07:58:59.3098760Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:59.3098920Z   PR_BODY: 
2025-07-17T07:58:59.3099150Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:59.3099430Z   DEVICE_NAME: 
2025-07-17T07:58:59.3099610Z   DEVICE_TYPE: 
2025-07-17T07:58:59.3099770Z ##[endgroup]
2025-07-17T07:58:59.3110580Z ##[group]Run echo "Print the available disk space for manual inspection"
2025-07-17T07:58:59.3111000Z echo "Print the available disk space for manual inspection"
2025-07-17T07:58:59.3111350Z df -h
2025-07-17T07:58:59.3111530Z 
2025-07-17T07:58:59.3111700Z function check_disk_space() {
2025-07-17T07:58:59.3111900Z   set +e
2025-07-17T07:58:59.3112060Z 
2025-07-17T07:58:59.3112260Z   # Set the minimum requirement space to 6GB
2025-07-17T07:58:59.3112600Z   MINIMUM_AVAILABLE_SPACE_IN_KB=$(($MINIMUM_AVAILABLE_SPACE_IN_GB * 1024 * 1024))
2025-07-17T07:58:59.3121840Z 
2025-07-17T07:58:59.3122030Z   # Use KB to avoid floating point warning like 3.1GB
2025-07-17T07:58:59.3122370Z   df -k | tr -s ' ' | cut -d' ' -f 4,9 | while read -r LINE;
2025-07-17T07:58:59.3122630Z   do
2025-07-17T07:58:59.3122930Z     AVAIL=$(echo $LINE | cut -f1 -d' ')
2025-07-17T07:58:59.3123220Z     MOUNT=$(echo $LINE | cut -f2 -d' ')
2025-07-17T07:58:59.3123440Z 
2025-07-17T07:58:59.3123620Z     if [ "${MOUNT}" = "/" ]; then
2025-07-17T07:58:59.3123930Z       if [ "${AVAIL}" -lt "${MINIMUM_AVAILABLE_SPACE_IN_KB}" ]; then
2025-07-17T07:58:59.3124480Z         echo "Failure: There is only ${AVAIL}KB free space left in ${MOUNT}, which is less than the minimum requirement of ${MINIMUM_AVAILABLE_SPACE_IN_KB}KB for ${RUNNER_OS}"
2025-07-17T07:58:59.3124960Z       else
2025-07-17T07:58:59.3125260Z         echo "Success: There is ${AVAIL}KB free space left in ${MOUNT} for ${RUNNER_OS}, continue"
2025-07-17T07:58:59.3125560Z       fi
2025-07-17T07:58:59.3125730Z     fi
2025-07-17T07:58:59.3125880Z   done
2025-07-17T07:58:59.3126020Z 
2025-07-17T07:58:59.3126160Z   set -e
2025-07-17T07:58:59.3126330Z }
2025-07-17T07:58:59.3126460Z 
2025-07-17T07:58:59.3126620Z RESULT=$(check_disk_space)
2025-07-17T07:58:59.3126820Z echo "${RESULT}"
2025-07-17T07:58:59.3126990Z 
2025-07-17T07:58:59.3127200Z if [[ "${RESULT}" == *Failure* && "${RUNNER_OS}" == "macOS" ]]; then
2025-07-17T07:58:59.3127730Z   # We can clean up /System/Library/Caches/com.apple.coresymbolicationd on MacOS to free up the space and this should free up enough space
2025-07-17T07:58:59.3128210Z   # https://github.com/pytorch/pytorch/issues/85440
2025-07-17T07:58:59.3128560Z   sudo rm "/System/Library/Caches/com.apple.coresymbolicationd/data" || true
2025-07-17T07:58:59.3129060Z   # Stop the daemon and launchctl will automatically start it again, thus accomplish a restart and free up the above file
2025-07-17T07:58:59.3129530Z   sudo launchctl stop com.apple.coresymbolicationd || true
2025-07-17T07:58:59.3129810Z 
2025-07-17T07:58:59.3130000Z   # Clean up crash reports on the runner
2025-07-17T07:58:59.3130320Z   sudo rm -rf "/System/Volumes/Data/Library/Logs/CrashReporter" || true
2025-07-17T07:58:59.3130620Z 
2025-07-17T07:58:59.3131060Z   # Also try to clean up torch.hub caching directory
2025-07-17T07:58:59.3131360Z   rm -rf "${HOME}/.cache/torch/hub" || true
2025-07-17T07:58:59.3131590Z 
2025-07-17T07:58:59.3131750Z   # Purge conda
2025-07-17T07:58:59.3131950Z   conda clean -p -t -y || true
2025-07-17T07:58:59.3132170Z   # and pip cache
2025-07-17T07:58:59.3132380Z   pip cache purge || true
2025-07-17T07:58:59.3132570Z 
2025-07-17T07:58:59.3132810Z   echo "Re-run disk space check for ${RUNNER_OS} after cleaning up"
2025-07-17T07:58:59.3133110Z   # Re-run the check
2025-07-17T07:58:59.3133300Z   RESULT=$(check_disk_space)
2025-07-17T07:58:59.3133530Z   echo "${RESULT}"
2025-07-17T07:58:59.3133730Z fi
2025-07-17T07:58:59.3133870Z 
2025-07-17T07:58:59.3134040Z if [[ "${RESULT}" == *Failure* ]]; then
2025-07-17T07:58:59.3134250Z   df -h
2025-07-17T07:58:59.3134400Z 
2025-07-17T07:58:59.3134880Z   echo "Please help create an issue to PyTorch Release Engineering via https://github.com/pytorch/test-infra/issues and provide the link to the workflow run."
2025-07-17T07:58:59.3135350Z   exit 1
2025-07-17T07:58:59.3135480Z fi
2025-07-17T07:58:59.3147420Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T07:58:59.3147660Z env:
2025-07-17T07:58:59.3147800Z   GIT_DEFAULT_BRANCH: main
2025-07-17T07:58:59.3148010Z   BUILD_ENVIRONMENT: macos-py3-arm64
2025-07-17T07:58:59.3148210Z   TEST_CONFIG: default
2025-07-17T07:58:59.3148380Z   SHARD_NUMBER: 1
2025-07-17T07:58:59.3148520Z   NUM_TEST_SHARDS: 3
2025-07-17T07:58:59.3148680Z   PR_BODY: 
2025-07-17T07:58:59.3148980Z   VENV_PATH: /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:58:59.3149240Z   DEVICE_NAME: 
2025-07-17T07:58:59.3149390Z   DEVICE_TYPE: 
2025-07-17T07:58:59.3149560Z   MINIMUM_AVAILABLE_SPACE_IN_GB: 6
2025-07-17T07:58:59.3149780Z ##[endgroup]
2025-07-17T07:58:59.3391490Z Print the available disk space for manual inspection
2025-07-17T07:58:59.3436960Z Filesystem        Size    Used   Avail Capacity iused ifree %iused  Mounted on
2025-07-17T07:58:59.3437400Z /dev/disk5s2s1   256Gi   9.5Gi   100Gi     9%    404k  1.1G    0%   /
2025-07-17T07:58:59.3437740Z devfs            217Ki   217Ki     0Bi   100%     752     0  100%   /dev
2025-07-17T07:58:59.3438120Z /dev/disk5s5     256Gi   2.0Gi   100Gi     2%       2  1.1G    0%   /System/Volumes/VM
2025-07-17T07:58:59.3438540Z /dev/disk5s3     256Gi   5.7Gi   100Gi     6%    1.0k  1.1G    0%   /System/Volumes/Preboot
2025-07-17T07:58:59.3438950Z /dev/disk1s2     500Mi   6.0Mi   387Mi     2%       1  4.0M    0%   /System/Volumes/xarts
2025-07-17T07:58:59.3439390Z /dev/disk1s1     500Mi    53Mi   387Mi    13%      61  4.0M    0%   /System/Volumes/iSCPreboot
2025-07-17T07:58:59.3439820Z /dev/disk1s3     500Mi   940Ki   387Mi     1%      51  4.0M    0%   /System/Volumes/Hardware
2025-07-17T07:58:59.3440230Z /dev/disk5s1     256Gi   137Gi   100Gi    58%    7.3M  1.1G    1%   /System/Volumes/Data
2025-07-17T07:58:59.3440650Z map auto_home      0Bi     0Bi     0Bi   100%       0     0     -   /System/Volumes/Data/home
2025-07-17T07:58:59.3441060Z /dev/disk3s4     228Gi   120Ki   210Gi     1%      18  2.2G    0%   /private/tmp/tmp-mount-g9r1EB
2025-07-17T07:58:59.3851950Z Success: There is 105033292KB free space left in / for macOS, continue
2025-07-17T07:58:59.3901430Z Post job cleanup.
2025-07-17T07:58:59.4329620Z Removing virtual environment at /Users/ec2-user/runner/_work/_temp/venv-3.12-1752734779
2025-07-17T07:59:03.4604000Z Post job cleanup.
2025-07-17T07:59:03.4648100Z Post job cleanup.
2025-07-17T07:59:03.5504410Z [command]/usr/bin/git version
2025-07-17T07:59:03.5577310Z git version 2.39.3 (Apple Git-146)
2025-07-17T07:59:03.5599010Z Copying '/Users/ec2-user/.gitconfig' to '/Users/ec2-user/runner/_work/_temp/a0bbfd60-c618-4785-beec-e17cb6469a30/.gitconfig'
2025-07-17T07:59:03.5605100Z Temporarily overriding HOME='/Users/ec2-user/runner/_work/_temp/a0bbfd60-c618-4785-beec-e17cb6469a30' before making global git config changes
2025-07-17T07:59:03.5605780Z Adding repository directory to the temporary git global config as a safe directory
2025-07-17T07:59:03.5611570Z [command]/usr/bin/git config --global --add safe.directory /Users/ec2-user/runner/_work/pytorch/pytorch
2025-07-17T07:59:03.5683940Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand
2025-07-17T07:59:03.5751370Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'core\.sshCommand' && git config --local --unset-all 'core.sshCommand' || :"
2025-07-17T07:59:03.6770740Z Entering 'android/libs/fbjni'
2025-07-17T07:59:03.6886370Z Entering 'third_party/FP16'
2025-07-17T07:59:03.6996590Z Entering 'third_party/FXdiv'
2025-07-17T07:59:03.7107070Z Entering 'third_party/NNPACK'
2025-07-17T07:59:03.7222940Z Entering 'third_party/NVTX'
2025-07-17T07:59:03.7326190Z Entering 'third_party/VulkanMemoryAllocator'
2025-07-17T07:59:03.7428070Z Entering 'third_party/XNNPACK'
2025-07-17T07:59:03.7684820Z Entering 'third_party/aiter'
2025-07-17T07:59:03.7788860Z Entering 'third_party/aiter/3rdparty/composable_kernel'
2025-07-17T07:59:03.7893960Z Entering 'third_party/benchmark'
2025-07-17T07:59:03.8008870Z Entering 'third_party/composable_kernel'
2025-07-17T07:59:03.8112590Z Entering 'third_party/cpp-httplib'
2025-07-17T07:59:03.8215880Z Entering 'third_party/cpuinfo'
2025-07-17T07:59:03.8347390Z Entering 'third_party/cudnn_frontend'
2025-07-17T07:59:03.8450340Z Entering 'third_party/cutlass'
2025-07-17T07:59:03.8557300Z Entering 'third_party/fbgemm'
2025-07-17T07:59:03.8806350Z Entering 'third_party/fbgemm/external/asmjit'
2025-07-17T07:59:03.8990170Z Entering 'third_party/fbgemm/external/composable_kernel'
2025-07-17T07:59:03.9233770Z Entering 'third_party/fbgemm/external/cpuinfo'
2025-07-17T07:59:03.9430690Z Entering 'third_party/fbgemm/external/cutlass'
2025-07-17T07:59:03.9694850Z Entering 'third_party/fbgemm/external/googletest'
2025-07-17T07:59:03.9846530Z Entering 'third_party/fbgemm/external/hipify_torch'
2025-07-17T07:59:04.0002910Z Entering 'third_party/fbgemm/external/json'
2025-07-17T07:59:04.0160580Z Entering 'third_party/flash-attention'
2025-07-17T07:59:04.0262390Z Entering 'third_party/flash-attention/csrc/composable_kernel'
2025-07-17T07:59:04.0366290Z Entering 'third_party/flash-attention/csrc/cutlass'
2025-07-17T07:59:04.0472040Z Entering 'third_party/flatbuffers'
2025-07-17T07:59:04.0576090Z Entering 'third_party/fmt'
2025-07-17T07:59:04.0692780Z Entering 'third_party/gemmlowp/gemmlowp'
2025-07-17T07:59:04.0803560Z Entering 'third_party/gloo'
2025-07-17T07:59:04.0918940Z Entering 'third_party/googletest'
2025-07-17T07:59:04.1035910Z Entering 'third_party/ideep'
2025-07-17T07:59:04.1162990Z Entering 'third_party/ideep/mkl-dnn'
2025-07-17T07:59:04.1365330Z Entering 'third_party/ittapi'
2025-07-17T07:59:04.1468740Z Entering 'third_party/kineto'
2025-07-17T07:59:04.1569000Z Entering 'third_party/kineto/libkineto/third_party/dynolog'
2025-07-17T07:59:04.1668010Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'
2025-07-17T07:59:04.1768950Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'
2025-07-17T07:59:04.1871870Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'
2025-07-17T07:59:04.1973200Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'
2025-07-17T07:59:04.2072710Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
2025-07-17T07:59:04.2176940Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-07-17T07:59:04.2279040Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-07-17T07:59:04.2379930Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-07-17T07:59:04.2481340Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-07-17T07:59:04.2582860Z Entering 'third_party/kineto/libkineto/third_party/fmt'
2025-07-17T07:59:04.2682770Z Entering 'third_party/kineto/libkineto/third_party/googletest'
2025-07-17T07:59:04.2784330Z Entering 'third_party/kleidiai'
2025-07-17T07:59:04.2885780Z Entering 'third_party/mimalloc'
2025-07-17T07:59:04.2986250Z Entering 'third_party/nlohmann'
2025-07-17T07:59:04.3087420Z Entering 'third_party/onnx'
2025-07-17T07:59:04.3389380Z Entering 'third_party/onnx/third_party/pybind11'
2025-07-17T07:59:04.3521640Z Entering 'third_party/opentelemetry-cpp'
2025-07-17T07:59:04.3625150Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-07-17T07:59:04.3732820Z Entering 'third_party/opentelemetry-cpp/third_party/googletest'
2025-07-17T07:59:04.3840170Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-07-17T07:59:04.3949020Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-07-17T07:59:04.4052870Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-07-17T07:59:04.4154830Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-07-17T07:59:04.4257950Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-07-17T07:59:04.4357510Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-07-17T07:59:04.4461050Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-07-17T07:59:04.4565640Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-07-17T07:59:04.4675380Z Entering 'third_party/pocketfft'
2025-07-17T07:59:04.4778790Z Entering 'third_party/protobuf'
2025-07-17T07:59:04.5009060Z Entering 'third_party/protobuf/third_party/benchmark'
2025-07-17T07:59:04.5145100Z Entering 'third_party/protobuf/third_party/googletest'
2025-07-17T07:59:04.5274950Z Entering 'third_party/psimd'
2025-07-17T07:59:04.5385360Z Entering 'third_party/pthreadpool'
2025-07-17T07:59:04.5494370Z Entering 'third_party/pybind11'
2025-07-17T07:59:04.5615460Z Entering 'third_party/python-peachpy'
2025-07-17T07:59:04.5724830Z Entering 'third_party/sleef'
2025-07-17T07:59:04.5839880Z Entering 'third_party/tensorpipe'
2025-07-17T07:59:04.6024040Z Entering 'third_party/tensorpipe/third_party/googletest'
2025-07-17T07:59:04.6171990Z Entering 'third_party/tensorpipe/third_party/libnop'
2025-07-17T07:59:04.6327900Z Entering 'third_party/tensorpipe/third_party/libuv'
2025-07-17T07:59:04.6499940Z Entering 'third_party/tensorpipe/third_party/pybind11'
2025-07-17T07:59:04.6659430Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-07-17T07:59:04.6789530Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader
2025-07-17T07:59:04.6846510Z http.https://github.com/.extraheader
2025-07-17T07:59:04.6854100Z [command]/usr/bin/git config --local --unset-all http.https://github.com/.extraheader
2025-07-17T07:59:04.6916400Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'http\.https\:\/\/github\.com\/\.extraheader' && git config --local --unset-all 'http.https://github.com/.extraheader' || :"
2025-07-17T07:59:04.7415240Z Entering 'android/libs/fbjni'
2025-07-17T07:59:04.7486760Z http.https://github.com/.extraheader
2025-07-17T07:59:04.7559040Z Entering 'third_party/FP16'
2025-07-17T07:59:04.7626090Z http.https://github.com/.extraheader
2025-07-17T07:59:04.7692840Z Entering 'third_party/FXdiv'
2025-07-17T07:59:04.7760140Z http.https://github.com/.extraheader
2025-07-17T07:59:04.7827900Z Entering 'third_party/NNPACK'
2025-07-17T07:59:04.7894720Z http.https://github.com/.extraheader
2025-07-17T07:59:04.7960940Z Entering 'third_party/NVTX'
2025-07-17T07:59:04.8027960Z http.https://github.com/.extraheader
2025-07-17T07:59:04.8095400Z Entering 'third_party/VulkanMemoryAllocator'
2025-07-17T07:59:04.8163080Z http.https://github.com/.extraheader
2025-07-17T07:59:04.8230440Z Entering 'third_party/XNNPACK'
2025-07-17T07:59:04.8299060Z http.https://github.com/.extraheader
2025-07-17T07:59:04.8370320Z Entering 'third_party/aiter'
2025-07-17T07:59:04.8439450Z http.https://github.com/.extraheader
2025-07-17T07:59:04.8505160Z Entering 'third_party/aiter/3rdparty/composable_kernel'
2025-07-17T07:59:04.8570800Z http.https://github.com/.extraheader
2025-07-17T07:59:04.8640710Z Entering 'third_party/benchmark'
2025-07-17T07:59:04.8708970Z http.https://github.com/.extraheader
2025-07-17T07:59:04.8777160Z Entering 'third_party/composable_kernel'
2025-07-17T07:59:04.8844190Z http.https://github.com/.extraheader
2025-07-17T07:59:04.8913190Z Entering 'third_party/cpp-httplib'
2025-07-17T07:59:04.8981060Z http.https://github.com/.extraheader
2025-07-17T07:59:04.9047520Z Entering 'third_party/cpuinfo'
2025-07-17T07:59:04.9115020Z http.https://github.com/.extraheader
2025-07-17T07:59:04.9181920Z Entering 'third_party/cudnn_frontend'
2025-07-17T07:59:04.9249360Z http.https://github.com/.extraheader
2025-07-17T07:59:04.9316290Z Entering 'third_party/cutlass'
2025-07-17T07:59:04.9384230Z http.https://github.com/.extraheader
2025-07-17T07:59:04.9454980Z Entering 'third_party/fbgemm'
2025-07-17T07:59:04.9523080Z http.https://github.com/.extraheader
2025-07-17T07:59:04.9588900Z Entering 'third_party/fbgemm/external/asmjit'
2025-07-17T07:59:04.9655000Z http.https://github.com/.extraheader
2025-07-17T07:59:04.9722140Z Entering 'third_party/fbgemm/external/composable_kernel'
2025-07-17T07:59:04.9789340Z http.https://github.com/.extraheader
2025-07-17T07:59:04.9865120Z Entering 'third_party/fbgemm/external/cpuinfo'
2025-07-17T07:59:04.9933130Z http.https://github.com/.extraheader
2025-07-17T07:59:04.9999750Z Entering 'third_party/fbgemm/external/cutlass'
2025-07-17T07:59:05.0067150Z http.https://github.com/.extraheader
2025-07-17T07:59:05.0136800Z Entering 'third_party/fbgemm/external/googletest'
2025-07-17T07:59:05.0204520Z http.https://github.com/.extraheader
2025-07-17T07:59:05.0271310Z Entering 'third_party/fbgemm/external/hipify_torch'
2025-07-17T07:59:05.0337330Z http.https://github.com/.extraheader
2025-07-17T07:59:05.0404200Z Entering 'third_party/fbgemm/external/json'
2025-07-17T07:59:05.0470700Z http.https://github.com/.extraheader
2025-07-17T07:59:05.0539480Z Entering 'third_party/flash-attention'
2025-07-17T07:59:05.0607670Z http.https://github.com/.extraheader
2025-07-17T07:59:05.0673310Z Entering 'third_party/flash-attention/csrc/composable_kernel'
2025-07-17T07:59:05.0740470Z http.https://github.com/.extraheader
2025-07-17T07:59:05.0809200Z Entering 'third_party/flash-attention/csrc/cutlass'
2025-07-17T07:59:05.0877650Z http.https://github.com/.extraheader
2025-07-17T07:59:05.0947970Z Entering 'third_party/flatbuffers'
2025-07-17T07:59:05.1016920Z http.https://github.com/.extraheader
2025-07-17T07:59:05.1084950Z Entering 'third_party/fmt'
2025-07-17T07:59:05.1152790Z http.https://github.com/.extraheader
2025-07-17T07:59:05.1219840Z Entering 'third_party/gemmlowp/gemmlowp'
2025-07-17T07:59:05.1287050Z http.https://github.com/.extraheader
2025-07-17T07:59:05.1353980Z Entering 'third_party/gloo'
2025-07-17T07:59:05.1422400Z http.https://github.com/.extraheader
2025-07-17T07:59:05.1489430Z Entering 'third_party/googletest'
2025-07-17T07:59:05.1556380Z http.https://github.com/.extraheader
2025-07-17T07:59:05.1622470Z Entering 'third_party/ideep'
2025-07-17T07:59:05.1689220Z http.https://github.com/.extraheader
2025-07-17T07:59:05.1754150Z Entering 'third_party/ideep/mkl-dnn'
2025-07-17T07:59:05.1820510Z http.https://github.com/.extraheader
2025-07-17T07:59:05.1890740Z Entering 'third_party/ittapi'
2025-07-17T07:59:05.1959220Z http.https://github.com/.extraheader
2025-07-17T07:59:05.2025920Z Entering 'third_party/kineto'
2025-07-17T07:59:05.2093250Z http.https://github.com/.extraheader
2025-07-17T07:59:05.2159820Z Entering 'third_party/kineto/libkineto/third_party/dynolog'
2025-07-17T07:59:05.2226010Z http.https://github.com/.extraheader
2025-07-17T07:59:05.2291000Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'
2025-07-17T07:59:05.2357540Z http.https://github.com/.extraheader
2025-07-17T07:59:05.2426490Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'
2025-07-17T07:59:05.2493290Z http.https://github.com/.extraheader
2025-07-17T07:59:05.2560360Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'
2025-07-17T07:59:05.2625870Z http.https://github.com/.extraheader
2025-07-17T07:59:05.2691960Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'
2025-07-17T07:59:05.2759430Z http.https://github.com/.extraheader
2025-07-17T07:59:05.2825260Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'
2025-07-17T07:59:05.2891930Z http.https://github.com/.extraheader
2025-07-17T07:59:05.2961090Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog'
2025-07-17T07:59:05.3027680Z http.https://github.com/.extraheader
2025-07-17T07:59:05.3096810Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'
2025-07-17T07:59:05.3163930Z http.https://github.com/.extraheader
2025-07-17T07:59:05.3231520Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json'
2025-07-17T07:59:05.3299790Z http.https://github.com/.extraheader
2025-07-17T07:59:05.3367170Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'
2025-07-17T07:59:05.3435040Z http.https://github.com/.extraheader
2025-07-17T07:59:05.3504750Z Entering 'third_party/kineto/libkineto/third_party/fmt'
2025-07-17T07:59:05.3571960Z http.https://github.com/.extraheader
2025-07-17T07:59:05.3637990Z Entering 'third_party/kineto/libkineto/third_party/googletest'
2025-07-17T07:59:05.3704040Z http.https://github.com/.extraheader
2025-07-17T07:59:05.3773380Z Entering 'third_party/kleidiai'
2025-07-17T07:59:05.3841210Z http.https://github.com/.extraheader
2025-07-17T07:59:05.3907820Z Entering 'third_party/mimalloc'
2025-07-17T07:59:05.3974690Z http.https://github.com/.extraheader
2025-07-17T07:59:05.4041710Z Entering 'third_party/nlohmann'
2025-07-17T07:59:05.4109330Z http.https://github.com/.extraheader
2025-07-17T07:59:05.4177030Z Entering 'third_party/onnx'
2025-07-17T07:59:05.4244170Z http.https://github.com/.extraheader
2025-07-17T07:59:05.4315670Z Entering 'third_party/onnx/third_party/pybind11'
2025-07-17T07:59:05.4384900Z http.https://github.com/.extraheader
2025-07-17T07:59:05.4454250Z Entering 'third_party/opentelemetry-cpp'
2025-07-17T07:59:05.4522860Z http.https://github.com/.extraheader
2025-07-17T07:59:05.4589420Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark'
2025-07-17T07:59:05.4656020Z http.https://github.com/.extraheader
2025-07-17T07:59:05.4723430Z Entering 'third_party/opentelemetry-cpp/third_party/googletest'
2025-07-17T07:59:05.4791840Z http.https://github.com/.extraheader
2025-07-17T07:59:05.4859260Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl'
2025-07-17T07:59:05.4926710Z http.https://github.com/.extraheader
2025-07-17T07:59:05.4993140Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json'
2025-07-17T07:59:05.5059960Z http.https://github.com/.extraheader
2025-07-17T07:59:05.5127430Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto'
2025-07-17T07:59:05.5194540Z http.https://github.com/.extraheader
2025-07-17T07:59:05.5262080Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp'
2025-07-17T07:59:05.5329070Z http.https://github.com/.extraheader
2025-07-17T07:59:05.5393800Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp'
2025-07-17T07:59:05.5460960Z http.https://github.com/.extraheader
2025-07-17T07:59:05.5526450Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb'
2025-07-17T07:59:05.5593720Z http.https://github.com/.extraheader
2025-07-17T07:59:05.5662070Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest'
2025-07-17T07:59:05.5729210Z http.https://github.com/.extraheader
2025-07-17T07:59:05.5798410Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg'
2025-07-17T07:59:05.5865410Z http.https://github.com/.extraheader
2025-07-17T07:59:05.5941580Z Entering 'third_party/pocketfft'
2025-07-17T07:59:05.6011120Z http.https://github.com/.extraheader
2025-07-17T07:59:05.6078460Z Entering 'third_party/protobuf'
2025-07-17T07:59:05.6144490Z http.https://github.com/.extraheader
2025-07-17T07:59:05.6210880Z Entering 'third_party/protobuf/third_party/benchmark'
2025-07-17T07:59:05.6279030Z http.https://github.com/.extraheader
2025-07-17T07:59:05.6345520Z Entering 'third_party/protobuf/third_party/googletest'
2025-07-17T07:59:05.6412160Z http.https://github.com/.extraheader
2025-07-17T07:59:05.6480880Z Entering 'third_party/psimd'
2025-07-17T07:59:05.6549530Z http.https://github.com/.extraheader
2025-07-17T07:59:05.6615940Z Entering 'third_party/pthreadpool'
2025-07-17T07:59:05.6683250Z http.https://github.com/.extraheader
2025-07-17T07:59:05.6750020Z Entering 'third_party/pybind11'
2025-07-17T07:59:05.6816980Z http.https://github.com/.extraheader
2025-07-17T07:59:05.6884270Z Entering 'third_party/python-peachpy'
2025-07-17T07:59:05.6951550Z http.https://github.com/.extraheader
2025-07-17T07:59:05.7018720Z Entering 'third_party/sleef'
2025-07-17T07:59:05.7085540Z http.https://github.com/.extraheader
2025-07-17T07:59:05.7154670Z Entering 'third_party/tensorpipe'
2025-07-17T07:59:05.7222070Z http.https://github.com/.extraheader
2025-07-17T07:59:05.7288040Z Entering 'third_party/tensorpipe/third_party/googletest'
2025-07-17T07:59:05.7353910Z http.https://github.com/.extraheader
2025-07-17T07:59:05.7420050Z Entering 'third_party/tensorpipe/third_party/libnop'
2025-07-17T07:59:05.7486740Z http.https://github.com/.extraheader
2025-07-17T07:59:05.7553510Z Entering 'third_party/tensorpipe/third_party/libuv'
2025-07-17T07:59:05.7620120Z http.https://github.com/.extraheader
2025-07-17T07:59:05.7686560Z Entering 'third_party/tensorpipe/third_party/pybind11'
2025-07-17T07:59:05.7752370Z http.https://github.com/.extraheader
2025-07-17T07:59:05.7818440Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang'
2025-07-17T07:59:05.7884890Z http.https://github.com/.extraheader
2025-07-17T07:59:05.8014160Z A job completed hook has been configured by the self-hosted runner administrator
2025-07-17T07:59:05.8079200Z ##[group]Run '/opt/runner_scripts/post-job.sh'
2025-07-17T07:59:05.8096290Z shell: /bin/bash --noprofile --norc -e -o pipefail {0}
2025-07-17T07:59:05.8096520Z ##[endgroup]
2025-07-17T07:59:05.8400280Z + df -h
2025-07-17T07:59:05.8420900Z + ls -t /var/log/post_job
2025-07-17T07:59:05.8421160Z + awk 'NR>100'
2025-07-17T07:59:05.8421570Z + xargs rm -fv
2025-07-17T07:59:05.8429650Z + Checking if runner needs to be terminated...ok
2025-07-17T07:59:05.8429910Z + Outputting disk space
2025-07-17T07:59:05.8430240Z Filesystem        Size    Used   Avail Capacity iused ifree %iused  Mounted on
2025-07-17T07:59:05.8430700Z /dev/disk5s2s1   256Gi   9.5Gi   101Gi     9%    404k  1.1G    0%   /
2025-07-17T07:59:05.8431040Z devfs            217Ki   217Ki     0Bi   100%     752     0  100%   /dev
2025-07-17T07:59:05.8431480Z /dev/disk5s5     256Gi   2.0Gi   101Gi     2%       2  1.1G    0%   /System/Volumes/VM
2025-07-17T07:59:05.8431920Z /dev/disk5s3     256Gi   5.7Gi   101Gi     6%    1.0k  1.1G    0%   /System/Volumes/Preboot
2025-07-17T07:59:05.8432320Z /dev/disk1s2     500Mi   6.0Mi   387Mi     2%       1  4.0M    0%   /System/Volumes/xarts
2025-07-17T07:59:05.8432730Z /dev/disk1s1     500Mi    53Mi   387Mi    13%      61  4.0M    0%   /System/Volumes/iSCPreboot
2025-07-17T07:59:05.8433160Z /dev/disk1s3     500Mi   940Ki   387Mi     1%      51  4.0M    0%   /System/Volumes/Hardware
2025-07-17T07:59:05.8433560Z /dev/disk5s1     256Gi   136Gi   101Gi    58%    7.3M  1.1G    1%   /System/Volumes/Data
2025-07-17T07:59:05.8433950Z map auto_home      0Bi     0Bi     0Bi   100%       0     0     -   /System/Volumes/Data/home
2025-07-17T07:59:05.8434530Z /dev/disk3s4     228Gi   120Ki   210Gi     1%      18  2.2G    0%   /private/tmp/tmp-mount-g9r1EB
2025-07-17T07:59:05.8434900Z + Cleaning up old logs (Keep the latest 100)
2025-07-17T07:59:06.6620770Z + Restoring SSH key to be the skeleton key
2025-07-17T07:59:06.6742860Z Cleaning up orphan processes