8000 Update base for Update on "std/var: Return real results for complex i… · pytorch/pytorch@90a3322 · GitHub
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Update base for Update on "std/var: Return real results for complex input"
Fixes gh-56627 [ghstack-poisoned]
2 parents 6aa9037 + 74a4868 commit 90a3322

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610 files changed

+31323
-20545
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  • cuda
  • fake_quant_per_channel_affine.cpp
  • sparse
  • templates
  • test
  • TH/generic
  • benchmarks/static_runtime
  • c10
  • caffe2
  • cmake
  • docs
  • scripts
  • setup.py
  • test

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    610 files changed

    +31323
    -20545
    lines changed

    ‎.circleci/cimodel/data/binary_build_definitions.py

    Lines changed: 6 additions & 1 deletion
    Original file line numberDiff line numberDiff line change
    @@ -27,7 +27,12 @@ def gen_build_env_parms(self):
    2727

    2828
    def gen_docker_image(self):
    2929
    if self.gcc_config_variant == 'gcc5.4_cxx11-abi':
    30-
    return miniutils.quote("pytorch/pytorch-binary-docker-image-ubuntu16.04:latest")
    30+
    if self.gpu_version is None:
    31+
    return miniutils.quote("pytorch/libtorch-cxx11-builder:cpu")
    32+
    else:
    33+
    return miniutils.quote(
    34+
    f"pytorch/libtorch-cxx11-builder:{self.gpu_version}"
    35+
    )
    3136
    if self.pydistro == "conda":
    3237
    if self.gpu_version is None:
    3338
    return miniutils.quote("pytorch/conda-builder:cpu")

    ‎.circleci/cimodel/data/simple/docker_definitions.py

    Lines changed: 1 addition & 1 deletion
    Original file line numberDiff line numberDiff line change
    @@ -14,7 +14,7 @@
    1414
    "pytorch-linux-xenial-cuda10.1-cudnn7-py3-gcc7",
    1515
    "pytorch-linux-xenial-cuda10.2-cudnn7-py3-gcc7",
    1616
    "pytorch-linux-xenial-cuda11.1-cudnn8-py3-gcc7",
    17-
    "pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7",
    17+
    "pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7",
    1818
    "pytorch-linux-xenial-py3-clang5-android-ndk-r19c",
    1919
    "pytorch-linux-xenial-py3-clang5-asan",
    2020
    "pytorch-linux-xenial-py3-clang7-onnx",

    ‎.circleci/cimodel/data/windows_build_definitions.py

    Lines changed: 5 additions & 5 deletions
    Original file line numberDiff line numberDiff line change
    @@ -138,18 +138,18 @@ def render(self):
    138138

    139139
    WORKFLOW_DATA = [
    140140
    # VS2019 CUDA-10.1
    141-
    WindowsJob(None, _VC2019, CudaVersion(10, 1)),
    142-
    WindowsJob(1, _VC2019, CudaVersion(10, 1)),
    143-
    WindowsJob(2, _VC2019, CudaVersion(10, 1)),
    141+
    WindowsJob(None, _VC2019, CudaVersion(10, 1), master_only=True),
    142+
    WindowsJob(1, _VC2019, CudaVersion(10, 1), master_only=True),
    143+
    WindowsJob(2, _VC2019, CudaVersion(10, 1), master_only=True),
    144144
    WindowsJob('_azure_multi_gpu', _VC2019, CudaVersion(10, 1), multi_gpu=True, nightly_only=True),
    145145
    # VS2019 CUDA-11.1
    146146
    WindowsJob(None, _VC2019, CudaVersion(11, 1)),
    147147
    WindowsJob(1, _VC2019, CudaVersion(11, 1), master_only=True),
    148148
    WindowsJob(2, _VC2019, CudaVersion(11, 1), master_only=True),
    149149
    # VS2019 CPU-only
    150150
    WindowsJob(None, _VC2019, None),
    151-
    WindowsJob(1, _VC2019, None, master_only=True),
    152-
    WindowsJob(2, _VC2019, None, master_only=True),
    151+
    WindowsJob(1, _VC2019, None),
    152+
    WindowsJob(2, _VC2019, None),
    153153
    WindowsJob(1, _VC2019, CudaVersion(10, 1), force_on_cpu=True, master_only=True),
    154154
    ]
    155155

    ‎.circleci/config.yml

    Lines changed: 88 additions & 78 deletions
    Large diffs are not rendered by default.

    ‎.circleci/docker/build.sh

    Lines changed: 2 additions & 2 deletions
    Original file line numberDiff line numberDiff line change
    @@ -140,8 +140,8 @@ case "$image" in
    140140
    VISION=yes
    141141
    KATEX=yes
    142142
    ;;
    143-
    pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7)
    144-
    CUDA_VERSION=11.2.0 # Deviating from major.minor to conform to nvidia's Docker image names
    143+
    pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7)
    144+
    CUDA_VERSION=11.3.0 # Deviating from major.minor to conform to nvidia's Docker image names
    145145
    CUDNN_VERSION=8
    146146
    ANACONDA_PYTHON_VERSION=3.6
    147147
    GCC_VERSION=7

    ‎.circleci/docker/common/install_conda.sh

    Lines changed: 2 additions & 2 deletions
    Original file line numberDiff line numberDiff line change
    @@ -91,8 +91,8 @@ if [ -n "$ANACONDA_PYTHON_VERSION" ]; then
    9191
    conda_install magma-cuda110 -c pytorch
    9292
    elif [[ "$CUDA_VERSION" == 11.1* ]]; then
    9393
    conda_install magma-cuda111 -c pytorch
    94-
    elif [[ "$CUDA_VERSION" == 11.2* ]]; then
    95-
    conda_install magma-cuda112 -c pytorch
    94+
    elif [[ "$CUDA_VERSION" == 11.3* ]]; then
    95+
    conda_install magma-cuda113 -c pytorch
    9696
    fi
    9797

    9898
    # TODO: This isn't working atm

    ‎.circleci/scripts/binary_populate_env.sh

    Lines changed: 2 additions & 0 deletions
    Original file line numberDiff line numberDiff line change
    @@ -168,6 +168,8 @@ export CIRCLE_SHA1="$CIRCLE_SHA1"
    168168
    export CIRCLE_PR_NUMBER="${CIRCLE_PR_NUMBER:-}"
    169169
    export CIRCLE_BRANCH="$CIRCLE_BRANCH"
    170170
    export CIRCLE_WORKFLOW_ID="$CIRCLE_WORKFLOW_ID"
    171+
    172+
    export USE_GOLD_LINKER=1
    171173
    # =================== The above code will be executed inside Docker container ===================
    172174
    EOL
    173175

    ‎.circleci/verbatim-sources/job-specs/job-specs-custom.yml

    Lines changed: 4 additions & 0 deletions
    Original file line numberDiff line numberDiff line change
    @@ -209,6 +209,10 @@
    209209
    source /Users/distiller/workspace/miniconda3/bin/activate
    210210
    pip install boto3
    211211
    export PYTHONPATH="$PWD"
    212+
    213+
    # Using the same IAM user to write stats to our OSS bucket
    214+
    export AWS_ACCESS_KEY_ID=${CIRCLECI_AWS_ACCESS_KEY_FOR_SCCACHE_S3_BUCKET_V4}
    215+
    export AWS_SECRET_ACCESS_KEY=${CIRCLECI_AWS_SECRET_KEY_FOR_SCCACHE_S3_BUCKET_V4}
    212216
    python tools/print_test_stats.py --upload-to-s3 --compare-with-s3 test
    213217
    when: always
    214218
    - store_test_results:

    ‎.circleci/verbatim-sources/workflows/workflows-scheduled-ci.yml

    Lines changed: 28 additions & 28 deletions
    Original file line numberDiff line numberDiff line change
    @@ -9,28 +9,28 @@
    99
    - master
    1010
    jobs:
    1111
    - docker_build_job:
    12-
    name: "docker-pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    13-
    image_name: "pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    12+
    name: "docker-pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    13+
    image_name: "pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    1414
    - pytorch_linux_build:
    15-
    name: periodic_pytorch_xenial_cuda11_2_cudnn8_gcc7_build
    15+
    name: periodic_pytorch_xenial_cuda11_3_cudnn8_gcc7_build
    1616
    requires:
    17-
    - "docker-pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    18-
    build_environment: "pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7-build"
    19-
    docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    17+
    - "docker-pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    18+
    build_environment: "pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7-build"
    19+
    docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    2020
    - pytorch_linux_test:
    21-
    name: periodic_pytorch_xenial_cuda11_2_cudnn8_gcc7_test
    21+
    name: periodic_pytorch_xenial_cuda11_3_cudnn8_gcc7_test
    2222
    requires:
    23-
    - periodic_pytorch_xenial_cuda11_2_cudnn8_gcc7_build
    24-
    build_environment: "pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7-test"
    25-
    docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    23+
    - periodic_pytorch_xenial_cuda11_3_cudnn8_gcc7_build
    24+
    build_environment: "pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7-test"
    25+
    docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    2626
    use_cuda_docker_runtime: "1"
    2727
    resource_class: gpu.medium
    2828
    - pytorch_linux_build:
    29-
    name: periodic_libtorch_xenial_cuda11_2_cudnn8_gcc7_build
    29+
    name: periodic_libtorch_xenial_cuda11_3_cudnn8_gcc7_build
    3030
    requires:
    31-
    - "docker-pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    32-
    build_environment: "pytorch-libtorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7-build"
    33-
    docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    31+
    - "docker-pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    32+
    build_environment: "pytorch-libtorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7-build"
    33+
    docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    3434
    - pytorch_windows_build:
    3535
    build_environment: pytorch-win-vs2019-cuda11-cudnn8-py3
    3636
    cuda_version: "11.2"
    @@ -71,30 +71,30 @@
    7171
    debuggable-scheduled-ci:
    7272
    jobs:
    7373
    - docker_build_job:
    74-
    name: "docker-pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    75-
    image_name: "pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    74+
    name: "docker-pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    75+
    image_name: "pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    7676
    filters:
    7777
    branches:
    7878
    only:
    7979
    - /ci-all\/.*/
    8080
    - /release\/.*/
    8181
    - pytorch_linux_build:
    82-
    name: pytorch_linux_xenial_cuda11_2_cudnn8_py3_gcc7_build
    82+
    name: pytorch_linux_xenial_cuda11_3_cudnn8_py3_gcc7_build
    8383
    requires:
    84-
    - "docker-pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    85-
    build_environment: "pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7-build"
    86-
    docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    84+
    - "docker-pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    85+
    build_environment: "pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7-build"
    86+
    docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    8787
    filters:
    8888
    branches:
    8989
    only:
    9090
    - /ci-all\/.*/
    9191
    - /release\/.*/
    9292
    - pytorch_linux_test:
    93-
    name: pytorch_linux_xenial_cuda11_2_cudnn8_py3_gcc7_test
    93+
    name: pytorch_linux_xenial_cuda11_3_cudnn8_py3_gcc7_test
    9494
    requires:
    95-
    - pytorch_linux_xenial_cuda11_2_cudnn8_py3_gcc7_build
    96-
    build_environment: "pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7-test"
    97-
    docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    95+
    - pytorch_linux_xenial_cuda11_3_cudnn8_py3_gcc7_build
    96+
    build_environment: "pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7-test"
    97+
    docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    9898
    use_cuda_docker_runtime: "1"
    9999
    resource_class: gpu.medium
    100100
    filters:
    @@ -103,11 +103,11 @@
    103103
    - /ci-all\/.*/
    104104
    - /release\/.*/
    105105
    - pytorch_linux_build:
    106-
    name: pytorch_libtorch_linux_xenial_cuda11_2_cudnn8_py3_gcc7_build
    106+
    name: pytorch_libtorch_linux_xenial_cuda11_3_cudnn8_py3_gcc7_build
    107107
    requires:
    108-
    - "docker-pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    109-
    build_environment: "pytorch-libtorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7-build"
    110-
    docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.2-cudnn8-py3-gcc7"
    108+
    - "docker-pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    109+
    build_environment: "pytorch-libtorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7-build"
    110+
    docker_image: "308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/pytorch-linux-xenial-cuda11.3-cudnn8-py3-gcc7"
    111111
    filters:
    112112
    branches:
    113113
    only:

    ‎.github/scripts/run_torchbench.py

    Lines changed: 103 additions & 0 deletions
    Original file line numberDiff line numberDiff line change
    @@ -0,0 +1,103 @@
    1+
    """
    2+
    Generate a torchbench test report from a file containing the PR body.
    3+
    Currently, only supports running tests on specified model names
    4+
    5+
    Testing environment:
    6+
    - Intel Xeon 8259CL @ 2.50 GHz, 24 Cores with disabled Turbo and HT
    7+
    - Nvidia Tesla T4
    8+
    - Nvidia Driver 450.51.06
    9+
    - Python 3.7
    10+
    - CUDA 10.2
    11+
    """
    12+
    # Known issues:
    13+
    # 1. Does not reuse the build artifact in other CI workflows
    14+
    # 2. CI jobs are serialized because there is only one worker
    15+
    import os
    16+
    import pathlib
    17+
    import argparse
    18+
    import subprocess
    19+
    20+
    from typing import List
    21+
    22+
    CUDA_VERSION = "cu102"
    23+
    PYTHON_VERSION = "3.7"
    24+
    TORCHBENCH_CONFIG_NAME = "config.yaml"
    25+
    MAGIC_PREFIX = "RUN_TORCHBENCH:"
    26+
    ABTEST_CONFIG_TEMPLATE = """# This config is automatically generated by run_torchbench.py
    27+
    start: {control}
    28+
    end: {treatment}
    29+
    threshold: 100
    30+
    direction: decrease
    31+
    timeout: 720
    32+
    tests:"""
    33+
    34+
    def gen_abtest_config(control: str, treatment: str, models: List[str]):
    35+
    d = {}
    36+
    d["control"] = control
    37+
    d["treatment"] = treatment
    38+
    config = ABTEST_CONFIG_TEMPLATE.format(**d)
    39+
    if models == ["ALL"]:
    40+
    return config + "\n"
    41+
    for model in models:
    42+
    config = f"{config}\n - {model}"
    43+
    config = config + "\n"
    44+
    return config
    45+
    46+
    def deploy_torchbench_config(output_dir: str, config: str):
    47+
    # Create test dir if needed
    48+
    pathlib.Path(output_dir).mkdir(exist_ok=True)
    49+
    # TorchBench config file name
    50+
    config_path = os.path.join(output_dir, TORCHBENCH_CONFIG_NAME)
    51+
    with open(config_path, "w") as fp:
    52+
    fp.write(config)
    53+
    54+
    def extract_models_from_pr(torchbench_path: str, prbody_file: str) -> List[str]:
    55+
    model_list = []
    56+
    with open(prbody_file, "r") as pf:
    57+
    lines = map(lambda x: x.strip(), pf.read().splitlines())
    58+
    magic_lines = list(filter(lambda x: x.startswith(MAGIC_PREFIX), lines))
    59+
    if magic_lines:
    60+
    # Only the first magic line will be respected.
    61+
    model_list = list(map(lambda x: x.strip(), magic_lines[0][len(MAGIC_PREFIX):].split(",")))
    62+
    # Shortcut: if model_list is ["ALL"], run all the tests
    63+
    if model_list == ["ALL"]:
    64+
    return model_list
    65+
    # Sanity check: make sure all the user specified models exist in torchbench repository
    66+
    benchmark_path = os.path.join(torchbench_path, "torchbenchmark", "models")
    67+
    full_model_list = [model for model in os.listdir(benchmark_path) if os.path.isdir(os.path.join(benchmark_path, model))]
    68+
    for m in model_list:
    69+
    if m not in full_model_list:
    70+
    print(f"The model {m} you specified does not exist in TorchBench suite. Please double check.")
    71+
    return []
    72+
    return model_list
    73+
    74+
    def run_torchbench(pytorch_path: str, torchbench_path: str, output_dir: str):
    75+
    # Copy system environment so that we will not override
    76+
    env = dict(os.environ)
    77+
    command = ["python", "bisection.py", "--work-dir", output_dir,
    78+
    "--pytorch-src", pytorch_path, "--torchbench-src", torchbench_path,
    79+
    "--config", os.path.join(output_dir, "config.yaml"),
    80+
    "--output", os.path.join(output_dir, "result.txt")]
    81+
    subprocess.check_call(command, cwd=torchbench_path, env=env)
    82+
    83+
    if __name__ == "__main__":
    84+
    parser = argparse.ArgumentParser(description='Run TorchBench tests based on PR')
    85+
    parser.add_argument('--pr-num', required=True, type=str, help="The Pull Request number")
    86+
    parser.add_argument('--pr-base-sha', required=True, type=str, help="The Pull Request base hash")
    87+
    parser.add_argument('--pr-head-sha', required=True, type=str, help="The Pull Request head hash")
    88+
    parser.add_argument('--pr-body', required=True, help="The file that contains body of a Pull Request")
    89+
    parser.add_argument('--pytorch-path', required=True, type=str, help="Path to pytorch repository")
    90+
    parser.add_argument('--torchbench-path', required=True, type=str, help="Path to TorchBench repository")
    91+
    args = parser.parse_args()
    92+
    93+
    output_dir: str = os.path.join(os.environ["HOME"], ".torchbench", "bisection", f"pr{args.pr_num}")
    94+
    # Identify the specified models and verify the input
    95+
    models = extract_models_from_pr(args.torchbench_path, args.pr_body)
    96+
    if not models:
    97+
    print("Can't parse the model filter from the pr body. Currently we only support allow-list.")
    98+
    exit(1)
    99+
    print(f"Ready to run TorchBench with benchmark. Result will be saved in the directory: {output_dir}.")
    100+
    # Run TorchBench with the generated config
    101+
    torchbench_config = gen_abtest_config(args.pr_base_sha, args.pr_head_sha, models)
    102+
    deploy_torchbench_config(output_dir, torchbench_config)
    103+
    run_torchbench(pytorch_path=args.pytorch_path, torchbench_path=args.torchbench_path, output_dir=output_dir)

    ‎.github/workflows/cancel_redundant_workflows.yml

    Lines changed: 1 addition & 0 deletions
    Original file line numberDiff line numberDiff line change
    @@ -8,6 +8,7 @@ on:
    88
    - Lint
    99
    - Linux CI (pytorch-linux-xenial-py3.6-gcc5.4)
    1010
    - Test tools
    11+
    - TorchBench CI (pytorch-linux-py3.7-cu102)
    1112
    - clang-format
    1213
    jobs:
    1314
    cancel:

    ‎.github/workflows/lint.yml

    Lines changed: 1 addition & 0 deletions
    Original file line numberDiff line numberDiff line change
    @@ -261,6 +261,7 @@ jobs:
    261261
    git submodule update --init --recursive
    262262
    263263
    export USE_NCCL=0
    264+
    export USE_DEPLOY=1
    264265
    # We really only need compile_commands.json, so no need to build!
    265266
    time python setup.py --cmake-only build
    266267

    ‎.github/workflows/run_torchbench.yml

    Lines changed: 66 additions & 0 deletions
    Original file line numberDiff line numberDiff line change
    @@ -0,0 +1,66 @@
    1+
    name: TorchBench CI (pytorch-linux-py3.7-cu102)
    2+
    on:
    3+
    pull_request:
    4+
    5+
    env:
    6+
    PR_NUM: ${{ github.event.number }}
    7+
    PR_BODY: ${{ github.event.pull_request.body }}
    8+
    PR_BASE_SHA: ${{ github.event.pull_request.base.sha }}
    9+
    PR_HEAD_SHA: ${{ github.event.pull_request.head.sha }}
    10+
    11+
    jobs:
    12+
    run-torchbench:
    13+
    # We don't accept running on non-pytorch repos because of security concerns
    14+
    # Only run the job when the body contains magic word "RUN_TORCHBENCH:"
    15+
    if: ${{ github.repository_owner == 'pytorch' && contains(github.event.pull_request.body, 'RUN_TORCHBENCH:') }}
    16+
    runs-on: [self-hosted, bm-runner]
    17+
    # Set to 12 hours
    18+
    timeout-minutes: 720
    19+
    steps:
    20+
    - name: Checkout PyTorch
    21+
    uses: actions/checkout@v2
    22+
    with:
    23+
    path: pytorch
    24+
    - name: Checkout TorchBench
    25+
    uses: actions/checkout@v2
    26+
    with:
    27+
    repository: pytorch/benchmark
    28+
    path: benchmark
    29+
    - name: Create conda environment
    30+
    run: |
    31+
    conda create -y -n pr-ci python=3.7
    32+
    # shellcheck disable=SC1091
    33+
    . "${HOME}"/anaconda3/etc/profile.d/conda.sh
    34+
    conda activate pr-ci
    35+
    conda install -y numpy=1.17 requests=2.22 ninja pyyaml mkl mkl-include setuptools cmake cffi typing_extensions future six dataclasses pillow pytest tabulate
    36+
    - name: Update self-hosted PyTorch
    37+
    run: |
    38+
    pushd "${HOME}"/pytorch
    39+
    git fetch
    40+
    popd
    41+
    - name: Run TorchBench
    42+
    run: |
    43+
    pushd "${HOME}"/pytorch
    44+
    PR_MERGE_BASE=$(git merge-base "$PR_BASE_SHA" "$PR_HEAD_SHA")
    45+
    popd
    46+
    PR_BODY_FILE=/tmp/pr-body.txt
    47+
    echo "$PR_BODY" > ${PR_BODY_FILE}
    48+
    # shellcheck disable=SC1091
    49+
    . "${HOME}"/anaconda3/etc/profile.d/conda.sh
    50+
    conda activate pr-ci
    51+
    python3 pytorch/.github/scripts/run_torchbench.py \
    52+
    --pytorch-path "${HOME}"/pytorch \
    53+
    --torchbench-path "${PWD}"/benchmark \
    54+
    --pr-num "$PR_NUM" \
    55+
    --pr-base-sha "$PR_MERGE_BASE" \
    56+
    --pr-head-sha "$PR_HEAD_SHA" \
    57+
    --pr-body "$PR_BODY_FILE"
    58+
    - name: Remove conda environment and cleanup
    59+
    run: |
    60+
    conda env remove --name pr-ci
    61+
    rm /tmp/pr-body.txt
    62+
    - name: Upload artifact
    63+
    uses: actions/upload-artifact@v2
    64+
    with:
    65+
    name: TorchBench result
    66+
    path: ~/.torchbench/bisection/pr${{ github.event.number }}

    ‎.jenkins/pytorch/build.sh

    Lines changed: 2 additions & 2 deletions
    Original file line numberDiff line numberDiff line change
    @@ -184,8 +184,8 @@ fi
    184184
    # Target only our CI GPU machine's CUDA arch to speed up the build
    185185
    export TORCH_CUDA_ARCH_LIST="5.2"
    186186

    187-
    # Add sm_75 support for the Linux CUDA 10.2 cuDNN 7 build
    188-
    if [[ "$BUILD_ENVIRONMENT" == *cuda10.2-cudnn7*build ]]; then
    187+
    # Add sm_75 support for the Linux CUDA 11.1 cuDNN 8 CircleCI build
    188+
    if [[ "$BUILD_ENVIRONMENT" == *xenial-cuda11.1-cudnn8*build ]]; then
    189189
    export TORCH_CUDA_ARCH_LIST=$TORCH_CUDA_ARCH_LIST";7.5"
    190190
    fi
    191191

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