merge v0.16.0

.circleci/.gitignore

-.idea

.circleci/build_docs/commit_docs.sh

-#!/usr/bin/env bash
-
-set -ex
-
-
-if [ "$2" == "" ]; then
-    echo call as "$0" "<src>" "<target branch>"
-    echo where src is the root of the built documentation git checkout and
-    echo branch should be "main" or "1.7" or so
-    exit 1
-fi
-
-src=$1
-target=$2
-
-echo "committing docs from ${src} to ${target}"
-
-pushd "${src}"
-git checkout gh-pages
-mkdir -p ./"${target}"
-rm -rf ./"${target}"/*
-cp -r "${src}/docs/build/html/"* ./"$target"
-if [ "${target}" == "main" ]; then
-    mkdir -p ./_static
-    rm -rf ./_static/*
-    cp -r "${src}/docs/build/html/_static/"* ./_static
-    git add --all ./_static || true
-fi
-git add --all ./"${target}" || true
-git config user.email "soumith+bot@pytorch.org"
-git config user.name "pytorchbot"
-# If there aren't changes, don't make a commit; push is no-op
-git commit -m "auto-generating sphinx docs" || true
-git remote add https https://github.com/pytorch/vision.git
-git push -u https gh-pages

.circleci/config.yml

-version: 2.1
-
-# How to test the Linux jobs:
-#   - Install CircleCI local CLI: https://circleci.com/docs/2.0/local-cli/
-#   - circleci config process .circleci/config.yml > gen.yml && circleci local execute -c gen.yml --job binary_linux_wheel_py3.7
-#     - Replace binary_linux_wheel_py3.7 with the name of the job you want to test.
-#       Job names are 'name:' key.
-
-executors:
-  windows-cpu:
-    machine:
-      resource_class: windows.xlarge
-      image: windows-server-2019-vs2019:stable
-      shell: bash.exe
-
-  windows-gpu:
-    machine:
-      resource_class: windows.gpu.nvidia.medium
-      image: windows-server-2019-nvidia:stable
-      shell: bash.exe
-
-commands:
-  checkout_merge:
-    description: "checkout merge branch"
-    steps:
-      - checkout
-#     - run:
-#         name: Checkout merge branch
-#         command: |
-#           set -ex
-#           BRANCH=$(git rev-parse --abbrev-ref HEAD)
-#           if [[ "$BRANCH" != "main" ]]; then
-#             git fetch --force origin ${CIRCLE_BRANCH}/merge:merged/${CIRCLE_BRANCH}
-#             git checkout "merged/$CIRCLE_BRANCH"
-#           fi
-  designate_upload_channel:
-    description: "inserts the correct upload channel into ${BASH_ENV}"
-    steps:
-      - run:
-          name: adding UPLOAD_CHANNEL to BASH_ENV
-          command: |
-            our_upload_channel=test
-            echo "export UPLOAD_CHANNEL=${our_upload_channel}" >> ${BASH_ENV}
-
-  brew_update:
-    description: "Update Homebrew and install base formulae"
-    steps:
-      - run:
-          name: Update Homebrew
-          no_output_timeout: "10m"
-          command: |
-            set -ex
-
-            # Update repositories manually.
-            # Running `brew update` produces a comparison between the
-            # current checkout and the updated checkout, which takes a
-            # very long time because the existing checkout is 2y old.
-            for path in $(find /usr/local/Homebrew -type d -name .git)
-            do
-            cd $path/..
-            git fetch --depth=1 origin
-            git reset --hard origin/master
-            done
-
-            export HOMEBREW_NO_AUTO_UPDATE=1
-
-            # Install expect and moreutils so that we can call `unbuffer` and `ts`.
-            # moreutils installs a `parallel` executable by default, which conflicts
-            # with the executable from the GNU `parallel`, so we must unlink GNU
-            # `parallel` first, and relink it afterwards.
-            brew install coreutils
-            brew unlink parallel
-            brew install moreutils
-            brew link parallel --overwrite
-            brew install expect
-
-  brew_install:
-    description: "Install Homebrew formulae"
-    parameters:
-      formulae:
-        type: string
-        default: ""
-    steps:
-      - run:
-          name: Install << parameters.formulae >>
-          no_output_timeout: "10m"
-          command: |
-            set -ex
-            export HOMEBREW_NO_AUTO_UPDATE=1
-            brew install << parameters.formulae >>
-
-  run_brew_for_ios_build:
-    steps:
-      - brew_update
-      - brew_install:
-          formulae: libtool
-
-  apt_install:
-    parameters:
-      args:
-        type: string
-      descr:
-        type: string
-        default: ""
-      update:
-        type: boolean
-        default: true
-    steps:
-      - run:
-          name: >
-            <<^ parameters.descr >> apt install << parameters.args >> <</ parameters.descr >>
-            <<# parameters.descr >> << parameters.descr >>            <</ parameters.descr >>
-          command: |
-            <<# parameters.update >> sudo apt update -qy  <</ parameters.update >>
-            sudo apt install << parameters.args >>
-
-  pip_install:
-    parameters:
-      args:
-        type: string
-      descr:
-        type: string
-        default: ""
-      user:
-        type: boolean
-        default: true
-    steps:
-      - run:
-          name: >
-            <<^ parameters.descr >> pip install << parameters.args >> <</ parameters.descr >>
-            <<# parameters.descr >> << parameters.descr >>            <</ parameters.descr >>
-          command: >
-            pip install
-            <<# parameters.user >> --user <</ parameters.user >>
-            --progress-bar=off
-            << parameters.args >>
-
-  install_torchvision:
-    parameters:
-      editable:
-        type: boolean
-        default: true
-    steps:
-      - pip_install:
-          args: --pre torch -f https://download.pytorch.org/whl/test/cpu/torch_test.html
-          descr: Install PyTorch from nightly releases
-      - pip_install:
-          args: --no-build-isolation <<# parameters.editable >> --editable <</ parameters.editable >> .
-          descr: Install torchvision <<# parameters.editable >> in editable mode <</ parameters.editable >>
-
-  # Most of the test suite is handled by the `unittest` jobs, with completely different workflow and setup.
-  # This command can be used if only a selection of tests need to be run, for ad-hoc files.
-  run_tests_selective:
-    parameters:
-      file_or_dir:
-        type: string
-    steps:
-      - run:
-          name: Install test utilities
-          command: pip install --progress-bar=off pytest pytest-mock
-      - run:
-          name: Run tests
-          command: pytest --junitxml=test-results/junit.xml -v --durations 20 <<parameters.file_or_dir>>
-      - store_test_results:
-          path: test-results
-
-  download_model_weights:
-    parameters:
-      extract_roots:
-        type: string
-        default: "torchvision/models"
-      background:
-        type: boolean
-        default: true
-    steps:
-      - apt_install:
-          args: parallel wget
-          descr: Install download utilitites
-      - run:
-          name: Download model weights
-          background: << parameters.background >>
-          command: |
-            mkdir -p ~/.cache/torch/hub/checkpoints
-            python scripts/collect_model_urls.py << parameters.extract_roots >> \
-                | parallel -j0 'wget --no-verbose -O ~/.cache/torch/hub/checkpoints/`basename {}` {}\?source=ci'
-
-binary_common: &binary_common
-  parameters:
-    # Edit these defaults to do a release
-    build_version:
-      description: "version number of release binary; by default, build a nightly"
-      type: string
-      default: "0.14.1"
-    pytorch_version:
-      description: "PyTorch version to build against; by default, use a nightly"
-      type: string
-      default: "1.13.1"
-    # Don't edit these
-    python_version:
-      description: "Python version to build against (e.g., 3.7)"
-      type: string
-    cu_version:
-      description: "CUDA version to build against, in CU format (e.g., cpu or cu100)"
-      type: string
-      default: "cpu"
-    unicode_abi:
-      description: "Python 2.7 wheel only: whether or not we are cp27mu (default: no)"
-      type: string
-      default: ""
-    wheel_docker_image:
-      description: "Wheel only: what docker image to use"
-      type: string
-      default: ""
-    conda_docker_image:
-      description: "Conda only: what docker image to use"
-      type: string
-      default: "pytorch/conda-builder:cpu"
-  environment:
-    PYTHON_VERSION: << parameters.python_version >>
-    PYTORCH_VERSION: << parameters.pytorch_version >>
-    UNICODE_ABI: << parameters.unicode_abi >>
-    CU_VERSION: << parameters.cu_version >>
-    MACOSX_DEPLOYMENT_TARGET: 10.9
-
-torchvision_ios_params: &torchvision_ios_params
-  parameters:
-    build_environment:
-      type: string
-      default: ""
-    ios_arch:
-      type: string
-      default: ""
-    ios_platform:
-      type: string
-      default: ""
-  environment:
-    BUILD_ENVIRONMENT: << parameters.build_environment >>
-    IOS_ARCH: << parameters.ios_arch >>
-    IOS_PLATFORM: << parameters.ios_platform >>
-
-torchvision_android_params: &torchvision_android_params
-  parameters:
-    build_environment:
-      type: string
-      default: ""
-  environment:
-    BUILD_ENVIRONMENT: << parameters.build_environment >>
-
-smoke_test_common: &smoke_test_common
-  <<: *binary_common
-  docker:
-    - image: torchvision/smoke_test:latest
-
-jobs:
-  circleci_consistency:
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - checkout
-      - pip_install:
-          args: jinja2 pyyaml
-      - run:
-          name: Check CircleCI config consistency
-          command: |
-            python .circleci/regenerate.py
-            git diff --exit-code || (echo ".circleci/config.yml not in sync with config.yml.in! Run .circleci/regenerate.py to update config"; exit 1)
-
-  lint_python_and_config:
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - checkout
-      - pip_install:
-          args: pre-commit
-          descr: Install lint utilities
-      - run:
-          name: Install pre-commit hooks
-          command: pre-commit install-hooks
-      - run:
-          name: Lint Python code and config files
-          command: pre-commit run --all-files
-      - run:
-          name: Required lint modifications
-          when: on_fail
-          command: git --no-pager diff
-
-  lint_c:
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - apt_install:
-          args: libtinfo5
-          descr: Install additional system libraries
-      - checkout
-      - run:
-          name: Install lint utilities
-          command: |
-            curl https://oss-clang-format.s3.us-east-2.amazonaws.com/linux64/clang-format-linux64 -o clang-format
-            chmod +x clang-format
-            sudo mv clang-format /opt/clang-format
-      - run:
-          name: Lint C code
-          command: ./.circleci/unittest/linux/scripts/run-clang-format.py -r torchvision/csrc --clang-format-executable /opt/clang-format
-      - run:
-          name: Required lint modifications
-          when: on_fail
-          command: git --no-pager diff
-
-  type_check_python:
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - checkout
-      - install_torchvision:
-          editable: true
-      - pip_install:
-          args: mypy
-          descr: Install Python type check utilities
-      - run:
-          name: Check Python types statically
-          command: mypy --install-types --non-interactive --config-file mypy.ini
-
-  unittest_torchhub:
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - checkout
-      - install_torchvision
-      - run_tests_selective:
-          file_or_dir: test/test_hub.py
-
-  unittest_onnx:
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - checkout
-      - install_torchvision
-      - pip_install:
-          args: onnx onnxruntime
-          descr: Install ONNX
-      - run_tests_selective:
-          file_or_dir: test/test_onnx.py
-
-  unittest_extended:
-    docker:
-      - image: cimg/python:3.7
-    resource_class: xlarge
-    steps:
-      - checkout
-      - download_model_weights
-      - install_torchvision
-      - run:
-          name: Enable extended tests
-          command: echo 'export PYTORCH_TEST_WITH_EXTENDED=1' >> $BASH_ENV
-      - run_tests_selective:
-          file_or_dir: test/test_extended_*.py
-
-  binary_linux_wheel:
-    <<: *binary_common
-    docker:
-      - image: << parameters.wheel_docker_image >>
-    resource_class: 2xlarge+
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Build conda packages
-          no_output_timeout: 30m
-          command: |
-              set -ex
-              packaging/build_wheel.sh
-      - store_artifacts:
-          path: dist
-      - persist_to_workspace:
-          root: dist
-          paths:
-            - "*"
-
-  binary_linux_conda:
-    <<: *binary_common
-    docker:
-      - image: "<< parameters.conda_docker_image >>"
-    resource_class: 2xlarge+
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Build conda packages
-          no_output_timeout: 30m
-          command: |
-              set -ex
-              packaging/build_conda.sh
-      - store_artifacts:
-          path: /opt/conda/conda-bld/linux-64
-      - persist_to_workspace:
-          root: /opt/conda/conda-bld/linux-64
-          paths:
-            - "*"
-      - store_test_results:
-          path: build_results/
-
-  binary_win_conda:
-    <<: *binary_common
-    executor: windows-cpu
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Build conda packages
-          no_output_timeout: 30m
-          command: |
-            set -ex
-            source packaging/windows/internal/vc_install_helper.sh
-            packaging/windows/internal/cuda_install.bat
-            eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
-            conda activate base
-            conda install -yq conda-build "conda-package-handling!=1.5.0"
-            packaging/build_conda.sh
-            rm /C/tools/miniconda3/conda-bld/win-64/vs${VC_YEAR}*.tar.bz2
-      - store_artifacts:
-          path: C:/tools/miniconda3/conda-bld/win-64
-      - persist_to_workspace:
-          root: C:/tools/miniconda3/conda-bld/win-64
-          paths:
-            - "*"
-      - store_test_results:
-          path: build_results/
-
-  binary_win_wheel:
-    <<: *binary_common
-    executor: windows-cpu
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Build wheel packages
-          no_output_timeout: 30m
-          command: |
-            set -ex
-            source packaging/windows/internal/vc_install_helper.sh
-            packaging/windows/internal/cuda_install.bat
-            packaging/build_wheel.sh
-      - store_artifacts:
-          path: dist
-      - persist_to_workspace:
-          root: dist
-          paths:
-            - "*"
-      - store_test_results:
-          path: build_results/
-
-  binary_macos_wheel:
-    <<: *binary_common
-    macos:
-      xcode: "14.0"
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          # Cannot easily deduplicate this as source'ing activate
-          # will set environment variables which we need to propagate
-          # to build_wheel.sh
-          command: |
-            curl -o conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
-            sh conda.sh -b
-            source $HOME/miniconda3/bin/activate
-            packaging/build_wheel.sh
-      - store_artifacts:
-          path: dist
-      - persist_to_workspace:
-          root: dist
-          paths:
-            - "*"
-
-  binary_ios_build:
-    <<: *torchvision_ios_params
-    macos:
-      xcode: "14.0"
-    steps:
-    - attach_workspace:
-        at: ~/workspace
-    - checkout
-    - run_brew_for_ios_build
-    - run:
-        name: Build
-        no_output_timeout: "1h"
-        command: |
-          script="/Users/distiller/project/.circleci/unittest/ios/scripts/binary_ios_build.sh"
-          cat "$script"
-          source "$script"
-    - persist_to_workspace:
-        root: /Users/distiller/workspace/
-        paths: ios
-
-  binary_ios_upload:
-    <<: *torchvision_ios_params
-    macos:
-      xcode: "14.0"
-    steps:
-    - attach_workspace:
-        at: ~/workspace
-    - checkout
-    - run_brew_for_ios_build
-    - run:
-        name: Upload
-        no_output_timeout: "1h"
-        command: |
-          script="/Users/distiller/project/.circleci/unittest/ios/scripts/binary_ios_upload.sh"
-          cat "$script"
-          source "$script"
-
-  binary_android_build:
-    <<: *torchvision_android_params
-    docker:
-      - image: cimg/android:2021.08-ndk
-    resource_class: xlarge
-    steps:
-    - attach_workspace:
-        at: ~/workspace
-    - checkout
-    - run:
-        name: Build
-        no_output_timeout: "1h"
-        command: |
-          script="/home/circleci/project/.circleci/unittest/android/scripts/binary_android_build.sh"
-          cat "$script"
-          source "$script"
-    - store_artifacts:
-        path: ~/workspace/artifacts
-
-  binary_android_upload:
-    <<: *torchvision_android_params
-    docker:
-      - image: cimg/android:2021.08-ndk
-    resource_class: xlarge
-    steps:
-    - attach_workspace:
-        at: ~/workspace
-    - checkout
-    - run:
-        name: Upload
-        no_output_timeout: "1h"
-        command: |
-          script="/home/circleci/project/.circleci/unittest/android/scripts/binary_android_upload.sh"
-          cat "$script"
-          source "$script"
-
-  binary_macos_conda:
-    <<: *binary_common
-    macos:
-      xcode: "14.0"
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          command: |
-            curl -o conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
-            sh conda.sh -b
-            source $HOME/miniconda3/bin/activate
-            conda install -yq conda-build
-            packaging/build_conda.sh
-      - store_artifacts:
-          path: /Users/distiller/miniconda3/conda-bld/osx-64
-      - persist_to_workspace:
-          root: /Users/distiller/miniconda3/conda-bld/osx-64
-          paths:
-            - "*"
-      - store_test_results:
-          path: build_results/
-
-  # Requires org-member context
-  binary_conda_upload:
-    docker:
-      - image: continuumio/miniconda
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - designate_upload_channel
-      - run:
-          command: |
-            # Prevent credential from leaking
-            conda install -yq anaconda-client
-            set -x
-            anaconda  -t "${CONDA_PYTORCHBOT_TOKEN}" upload ~/workspace/*.tar.bz2 -u "pytorch-${UPLOAD_CHANNEL}" --label main --no-progress --force
-
-  # Requires org-member context
-  binary_wheel_upload:
-    parameters:
-      subfolder:
-        description: "What whl subfolder to upload to, e.g., blank or cu100/ (trailing slash is important)"
-        type: string
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - designate_upload_channel
-      - checkout
-      - pip_install:
-          args: awscli
-      - run:
-          command: |
-            export PATH="$HOME/.local/bin:$PATH"
-            # Prevent credential from leaking
-            set +x
-            export AWS_ACCESS_KEY_ID="${PYTORCH_BINARY_AWS_ACCESS_KEY_ID}"
-            export AWS_SECRET_ACCESS_KEY="${PYTORCH_BINARY_AWS_SECRET_ACCESS_KEY}"
-            set -x
-            for pkg in ~/workspace/*.whl; do
-              aws s3 cp "$pkg" "s3://pytorch/whl/${UPLOAD_CHANNEL}/<< parameters.subfolder >>" --acl public-read
-            done
-
-  smoke_test_linux_conda:
-    <<: *smoke_test_common
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - designate_upload_channel
-      - run:
-          name: install binaries
-          command: |
-            set -x
-            source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
-            conda install -v -y -c pytorch-nightly pytorch
-            conda install -v -y $(ls ~/workspace/torchvision*.tar.bz2)
-      - run:
-          name: smoke test
-          command: |
-            source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
-            python -c "import torchvision"
-
-  smoke_test_linux_pip:
-    <<: *smoke_test_common
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - designate_upload_channel
-      - run:
-          name: install binaries
-          command: |
-            set -x
-            source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
-      - pip_install:
-          args: $(ls ~/workspace/torchvision*.whl) --pre -f https://download.pytorch.org/whl/test/torch_test.html
-      - run:
-          name: smoke test
-          command: |
-            source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
-            python -c "import torchvision"
-
-  smoke_test_docker_image_build:
-    machine:
-      image: ubuntu-2004:202104-01
-    resource_class: large
-    environment:
-      image_name: torchvision/smoke_test
-    steps:
-      - checkout
-      - designate_upload_channel
-      - run:
-          name: Build and push Docker image
-          no_output_timeout: "1h"
-          command: |
-            set +x
-            echo "${DOCKER_HUB_TOKEN}" | docker login --username "${DOCKER_HUB_USERNAME}" --password-stdin
-            set -x
-            cd .circleci/smoke_test/docker && docker build . -t ${image_name}:${CIRCLE_WORKFLOW_ID}
-            docker tag ${image_name}:${CIRCLE_WORKFLOW_ID} ${image_name}:latest
-            docker push ${image_name}:${CIRCLE_WORKFLOW_ID}
-            docker push ${image_name}:latest
-
-  smoke_test_win_conda:
-    <<: *binary_common
-    executor:
-      name: windows-cpu
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - designate_upload_channel
-      - run:
-          name: install binaries
-          command: |
-            set -x
-            eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
-            conda env remove -n python${PYTHON_VERSION} || true
-            conda create -yn python${PYTHON_VERSION} python=${PYTHON_VERSION}
-            conda activate python${PYTHON_VERSION}
-            conda install -v -y -c pytorch-nightly pytorch
-            conda install -v -y $(ls ~/workspace/torchvision*.tar.bz2)
-      - run:
-          name: smoke test
-          command: |
-            eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
-            conda activate python${PYTHON_VERSION}
-            python -c "import torchvision"
-
-  smoke_test_win_pip:
-    <<: *binary_common
-    executor:
-      name: windows-cpu
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - designate_upload_channel
-      - run:
-          name: install binaries
-          command: |
-            set -x
-            eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
-            conda create -yn python${PYTHON_VERSION} python=${PYTHON_VERSION}
-            conda activate python${PYTHON_VERSION}
-      - pip_install:
-          args: $(ls ~/workspace/torchvision*.whl) --pre -f https://download.pytorch.org/whl/test/torch_test.html
-      - run:
-          name: smoke test
-          command: |
-            eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
-            conda activate python${PYTHON_VERSION}
-            python -c "import torchvision"
-
-  unittest_linux_cpu:
-    <<: *binary_common
-    docker:
-      - image: "pytorch/manylinux-cpu"
-    resource_class: 2xlarge+
-    steps:
-      - checkout
-      - designate_upload_channel
-      - run:
-          name: Generate cache key
-          # This will refresh cache on Sundays, nightly build should generate new cache.
-          command: echo "$(date +"%Y-%U")" > .circleci-weekly
-      - restore_cache:
-
-          keys:
-            - env-v2-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-
-      - run:
-          name: Setup
-          command: .circleci/unittest/linux/scripts/setup_env.sh
-      - save_cache:
-
-          key: env-v2-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-
-          paths:
-            - conda
-            - env
-      - run:
-          name: Install torchvision
-          command: .circleci/unittest/linux/scripts/install.sh
-      - run:
-          name: Run tests
-          command: .circleci/unittest/linux/scripts/run_test.sh
-      - run:
-          name: Post process
-          command: .circleci/unittest/linux/scripts/post_process.sh
-      - store_test_results:
-          path: test-results
-
-  unittest_linux_gpu:
-    <<: *binary_common
-    machine:
-      image: ubuntu-2004-cuda-11.4:202110-01
-    resource_class: gpu.nvidia.medium
-    environment:
-      image_name: "pytorch/manylinux-cuda116"
-      CU_VERSION: << parameters.cu_version >>
-      PYTHON_VERSION: << parameters.python_version >>
-    steps:
-      - checkout
-      - designate_upload_channel
-      - run:
-          name: Generate cache key
-          # This will refresh cache on Sundays, nightly build should generate new cache.
-          command: echo "$(date +"%Y-%U")" > .circleci-weekly
-      - restore_cache:
-
-          keys:
-            - env-v3-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-
-      - run:
-          name: Setup
-          command: docker run -e PYTHON_VERSION -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/setup_env.sh
-      - save_cache:
-
-          key: env-v3-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-
-          paths:
-            - conda
-            - env
-      - run:
-          # Here we create an envlist file that contains some env variables that we want the docker container to be aware of.
-          # Normally, the CIRCLECI variable is set and available on all CI workflows: https://circleci.com/docs/2.0/env-vars/#built-in-environment-variables.
-          # They're avaiable in all the other workflows (OSX and Windows).
-          # But here, we're running the unittest_linux_gpu workflows in a docker container, where those variables aren't accessible.
-          # So instead we dump the variables we need in env.list and we pass that file when invoking "docker run".
-          name: export CIRCLECI env var
-          command: echo "CIRCLECI=true" >> ./env.list
-      - run:
-          name: Install torchvision
-          command: docker run -t --gpus all -v $PWD:$PWD -w $PWD -e UPLOAD_CHANNEL -e CU_VERSION "${image_name}" .circleci/unittest/linux/scripts/install.sh
-      - run:
-          name: Run tests
-          command: docker run --env-file ./env.list -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/run_test.sh
-      - run:
-          name: Post Process
-          command: docker run -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/post_process.sh
-      - store_test_results:
-          path: test-results
-
-  unittest_windows_cpu:
-    <<: *binary_common
-    executor:
-      name: windows-cpu
-    steps:
-      - checkout
-      - designate_upload_channel
-      - run:
-          name: Generate cache key
-          # This will refresh cache on Sundays, nightly build should generate new cache.
-          command: echo "$(date +"%Y-%U")" > .circleci-weekly
-      - restore_cache:
-
-          keys:
-            - env-v2-windows-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/windows/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-
-      - run:
-          name: Setup
-          command: .circleci/unittest/windows/scripts/setup_env.sh
-      - save_cache:
-
-          key: env-v2-windows-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/windows/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-
-          paths:
-            - conda
-            - env
-      - run:
-          name: Install torchvision
-          command: .circleci/unittest/windows/scripts/install.sh
-      - run:
-          name: Run tests
-          command: .circleci/unittest/windows/scripts/run_test.sh
-      - run:
-          name: Post process
-          command: .circleci/unittest/windows/scripts/post_process.sh
-      - store_test_results:
-          path: test-results
-
-  unittest_windows_gpu:
-    <<: *binary_common
-    executor:
-      name: windows-gpu
-    environment:
-      CUDA_VERSION: "11.6"
-      PYTHON_VERSION: << parameters.python_version >>
-    steps:
-      - checkout
-      - designate_upload_channel
-      - run:
-          name: Generate cache key
-          # This will refresh cache on Sundays, nightly build should generate new cache.
-          command: echo "$(date +"%Y-%U")" > .circleci-weekly
-      - restore_cache:
-
-          keys:
-            - env-v1-windows-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/windows/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-
-      - run:
-          name: Setup
-          command: .circleci/unittest/windows/scripts/setup_env.sh
-      - save_cache:
-
-          key: env-v1-windows-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/windows/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-
-          paths:
-            - conda
-            - env
-      - run:
-          name: Install CUDA
-          command: packaging/windows/internal/cuda_install.bat
-      - run:
-          name: Update CUDA driver
-          command: packaging/windows/internal/driver_update.bat
-      - run:
-          name: Install torchvision
-          command: .circleci/unittest/windows/scripts/install.sh
-      - run:
-          name: Run tests
-          command: .circleci/unittest/windows/scripts/run_test.sh
-      - run:
-          name: Post process
-          command: .circleci/unittest/windows/scripts/post_process.sh
-      - store_test_results:
-          path: test-results
-
-  unittest_macos_cpu:
-    <<: *binary_common
-    macos:
-      xcode: "14.0"
-    resource_class: large
-    steps:
-      - checkout
-      - designate_upload_channel
-      - run:
-          name: Install wget
-          command: HOMEBREW_NO_AUTO_UPDATE=1 brew install wget
-          # Disable brew auto update which is very slow
-      - run:
-          name: Generate cache key
-          # This will refresh cache on Sundays, nightly build should generate new cache.
-          command: echo "$(date +"%Y-%U")" > .circleci-weekly
-      - restore_cache:
-
-          keys:
-            - env-v3-macos-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-
-      - run:
-          name: Setup
-          command: .circleci/unittest/linux/scripts/setup_env.sh
-      - save_cache:
-
-          key: env-v3-macos-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-
-          paths:
-            - conda
-            - env
-      - run:
-          name: Install torchvision
-          command: .circleci/unittest/linux/scripts/install.sh
-      - run:
-          name: Run tests
-          command: .circleci/unittest/linux/scripts/run_test.sh
-      - run:
-          name: Post process
-          command: .circleci/unittest/linux/scripts/post_process.sh
-      - store_test_results:
-          path: test-results
-
-  cmake_linux_cpu:
-    <<: *binary_common
-    docker:
-      - image: "pytorch/manylinux-cpu"
-    resource_class: 2xlarge+
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Setup conda
-          command: .circleci/unittest/linux/scripts/setup_env.sh
-      - run: packaging/build_cmake.sh
-
-  cmake_linux_gpu:
-    <<: *binary_common
-    machine:
-      image: ubuntu-2004-cuda-11.4:202110-01
-    resource_class: gpu.nvidia.small
-    environment:
-      PYTHON_VERSION: << parameters.python_version >>
-      PYTORCH_VERSION: << parameters.pytorch_version >>
-      UNICODE_ABI: << parameters.unicode_abi >>
-      CU_VERSION: << parameters.cu_version >>
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Setup conda
-          command: docker run -e CU_VERSION -e PYTHON_VERSION -e UNICODE_ABI -e PYTORCH_VERSION -t --gpus all -v $PWD:$PWD -w $PWD << parameters.wheel_docker_image >> .circleci/unittest/linux/scripts/setup_env.sh
-      - run:
-          name: Build torchvision C++ distribution and test
-          no_output_timeout: 30m
-          command: docker run -e CU_VERSION -e PYTHON_VERSION -e UNICODE_ABI -e PYTORCH_VERSION -e UPLOAD_CHANNEL -t --gpus all -v $PWD:$PWD -w $PWD << parameters.wheel_docker_image >> packaging/build_cmake.sh
-
-  cmake_macos_cpu:
-    <<: *binary_common
-    macos:
-      xcode: "14.0"
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          command: |
-            curl -o conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
-            sh conda.sh -b
-            source $HOME/miniconda3/bin/activate
-            conda install -yq conda-build cmake
-            packaging/build_cmake.sh
-
-  cmake_windows_cpu:
-    <<: *binary_common
-    executor:
-      name: windows-cpu
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          command: |
-            set -ex
-            source packaging/windows/internal/vc_install_helper.sh
-            packaging/build_cmake.sh
-
-  cmake_windows_gpu:
-    <<: *binary_common
-    executor:
-      name: windows-gpu
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Update CUDA driver
-          command: packaging/windows/internal/driver_update.bat
-      - run:
-          command: |
-            set -ex
-            source packaging/windows/internal/vc_install_helper.sh
-            packaging/windows/internal/cuda_install.bat
-            packaging/build_cmake.sh
-
-  build_docs:
-    <<: *binary_common
-    docker:
-      - image: cimg/python:3.7
-    resource_class: 2xlarge+
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - checkout
-      - download_model_weights
-      - run:
-          name: Setup
-          command: .circleci/unittest/linux/scripts/setup_env.sh
-      - designate_upload_channel
-      - run:
-          name: Install torchvision
-          command: .circleci/unittest/linux/scripts/install.sh
-      - run:
-          name: Build docs
-          command: |
-            set -ex
-            # turn v1.12.0rc3 into 1.12.0
-            tag=$(echo $CIRCLE_TAG | sed -e 's/v*\([0-9.]*\).*/\1/')
-            VERSION=${tag:-main}
-            eval "$(./conda/bin/conda shell.bash hook)"
-            conda activate ./env
-            pushd docs
-            pip install --progress-bar=off -r requirements.txt
-            make html
-            popd
-      - persist_to_workspace:
-          root: ./
-          paths:
-            - "*"
-      - store_artifacts:
-          path: ./docs/build/html
-          destination: docs
-
-  upload_docs:
-    <<: *binary_common
-    docker:
-      - image: "pytorch/manylinux-cuda100"
-    resource_class: 2xlarge+
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - run:
-          name: Generate netrc
-          command: |
-            # set credentials for https pushing
-            # requires the org-member context
-            cat > ~/.netrc \<<DONE
-              machine github.com
-              login pytorchbot
-              password ${GITHUB_PYTORCHBOT_TOKEN}
-            DONE
-      - run:
-          name: Upload docs
-          command: |
-            # Don't use "checkout" step since it uses ssh, which cannot git push
-            # https://circleci.com/docs/2.0/configuration-reference/#checkout
-            set -ex
-            # Change v1.12.1rc1 into 1.12 (only major.minor)
-            tag=$(echo $CIRCLE_TAG | sed -e 's/v*\([0-9]*\.[0-9]*\).*/\1/')
-            target=${tag:-main}
-            ~/workspace/.circleci/build_docs/commit_docs.sh ~/workspace $target
-
-
-workflows:
-  lint:
-    jobs:
-      - circleci_consistency
-      - lint_python_and_config
-      - lint_c
-      - type_check_python
-
-  build:
-    jobs:
-      - binary_linux_wheel:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          filters:
-            branches:
-              only: /.*/
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: binary_linux_wheel_py3.7_cpu
-          python_version: '3.7'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_linux_wheel:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          cu_version: cu116
-          name: binary_linux_wheel_py3.7_cu116
-          python_version: '3.7'
-          wheel_docker_image: pytorch/manylinux-cuda116
-      - binary_linux_wheel:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          cu_version: cu117
-          name: binary_linux_wheel_py3.7_cu117
-          python_version: '3.7'
-          wheel_docker_image: pytorch/manylinux-cuda117
-      - binary_linux_wheel:
-          cu_version: rocm5.1.1
-          name: binary_linux_wheel_py3.7_rocm5.1.1
-          python_version: '3.7'
-          wheel_docker_image: pytorch/manylinux-rocm:5.1.1
-      - binary_linux_wheel:
-          cu_version: rocm5.2
-          name: binary_linux_wheel_py3.7_rocm5.2
-          python_version: '3.7'
-          wheel_docker_image: pytorch/manylinux-rocm:5.2
-      - binary_linux_wheel:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          name: binary_linux_wheel_py3.8_cpu
-          python_version: '3.8'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_linux_wheel:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          cu_version: cu116
-          name: binary_linux_wheel_py3.8_cu116
-          python_version: '3.8'
-          wheel_docker_image: pytorch/manylinux-cuda116
-      - binary_linux_wheel:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          cu_version: cu117
-          name: binary_linux_wheel_py3.8_cu117
-          python_version: '3.8'
-          wheel_docker_image: pytorch/manylinux-cuda117
-      - binary_linux_wheel:
-          cu_version: rocm5.1.1
-          name: binary_linux_wheel_py3.8_rocm5.1.1
-          python_version: '3.8'
-          wheel_docker_image: pytorch/manylinux-rocm:5.1.1
-      - binary_linux_wheel:
-          cu_version: rocm5.2
-          name: binary_linux_wheel_py3.8_rocm5.2
-          python_version: '3.8'
-          wheel_docker_image: pytorch/manylinux-rocm:5.2
-      - binary_linux_wheel:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          name: binary_linux_wheel_py3.9_cpu
-          python_version: '3.9'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_linux_wheel:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          cu_version: cu116
-          name: binary_linux_wheel_py3.9_cu116
-          python_version: '3.9'
-          wheel_docker_image: pytorch/manylinux-cuda116
-      - binary_linux_wheel:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          cu_version: cu117
-          name: binary_linux_wheel_py3.9_cu117
-          python_version: '3.9'
-          wheel_docker_image: pytorch/manylinux-cuda117
-      - binary_linux_wheel:
-          cu_version: rocm5.1.1
-          name: binary_linux_wheel_py3.9_rocm5.1.1
-          python_version: '3.9'
-          wheel_docker_image: pytorch/manylinux-rocm:5.1.1
-      - binary_linux_wheel:
-          cu_version: rocm5.2
-          name: binary_linux_wheel_py3.9_rocm5.2
-          python_version: '3.9'
-          wheel_docker_image: pytorch/manylinux-rocm:5.2
-      - binary_linux_wheel:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          name: binary_linux_wheel_py3.10_cpu
-          python_version: '3.10'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_linux_wheel:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          cu_version: cu116
-          name: binary_linux_wheel_py3.10_cu116
-          python_version: '3.10'
-          wheel_docker_image: pytorch/manylinux-cuda116
-      - binary_linux_wheel:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          cu_version: cu117
-          name: binary_linux_wheel_py3.10_cu117
-          python_version: '3.10'
-          wheel_docker_image: pytorch/manylinux-cuda117
-      - binary_linux_wheel:
-          cu_version: rocm5.1.1
-          name: binary_linux_wheel_py3.10_rocm5.1.1
-          python_version: '3.10'
-          wheel_docker_image: pytorch/manylinux-rocm:5.1.1
-      - binary_linux_wheel:
-          cu_version: rocm5.2
-          name: binary_linux_wheel_py3.10_rocm5.2
-          python_version: '3.10'
-          wheel_docker_image: pytorch/manylinux-rocm:5.2
-      - binary_macos_wheel:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          name: binary_macos_wheel_py3.7_cpu
-          python_version: '3.7'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_macos_wheel:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          name: binary_macos_wheel_py3.8_cpu
-          python_version: '3.8'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_macos_wheel:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          name: binary_macos_wheel_py3.9_cpu
-          python_version: '3.9'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_macos_wheel:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          name: binary_macos_wheel_py3.10_cpu
-          python_version: '3.10'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_win_wheel:
-          cu_version: cpu
-          filters:
-            branches:
-              only: main
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: binary_win_wheel_py3.7_cpu
-          python_version: '3.7'
-      - binary_win_wheel:
-          cu_version: cu116
-          filters:
-            branches:
-              only: main
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: binary_win_wheel_py3.7_cu116
-          python_version: '3.7'
-      - binary_win_wheel:
-          cu_version: cu117
-          filters:
-            branches:
-              only: main
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: binary_win_wheel_py3.7_cu117
-          python_version: '3.7'
-      - binary_win_wheel:
-          cu_version: cpu
-          filters:
-            branches:
-              only: main
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: binary_win_wheel_py3.8_cpu
-          python_version: '3.8'
-      - binary_win_wheel:
-          cu_version: cu116
-          filters:
-            branches:
-              only: main
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: binary_win_wheel_py3.8_cu116
-          python_version: '3.8'
-      - binary_win_wheel:
-          cu_version: cu117
-          filters:
-            branches:
-              only: main
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: binary_win_wheel_py3.8_cu117
-          python_version: '3.8'
-      - binary_win_wheel:
-          cu_version: cpu
-          filters:
-            branches:
-              only: main
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: binary_win_wheel_py3.9_cpu
-          python_version: '3.9'
-      - binary_win_wheel:
-          cu_version: cu116
-          filters:
-            branches:
-              only: main
-            tags:
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-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.8_cpu
-          python_version: '3.8'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.8_cpu_upload
-          requires:
-          - nightly_binary_linux_conda_py3.8_cpu
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          cu_version: cu116
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.8_cu116
-          python_version: '3.8'
-          wheel_docker_image: pytorch/manylinux-cuda116
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.8_cu116_upload
-          requires:
-          - nightly_binary_linux_conda_py3.8_cu116
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          cu_version: cu117
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.8_cu117
-          python_version: '3.8'
-          wheel_docker_image: pytorch/manylinux-cuda117
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.8_cu117_upload
-          requires:
-          - nightly_binary_linux_conda_py3.8_cu117
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.9_cpu
-          python_version: '3.9'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.9_cpu_upload
-          requires:
-          - nightly_binary_linux_conda_py3.9_cpu
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          cu_version: cu116
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.9_cu116
-          python_version: '3.9'
-          wheel_docker_image: pytorch/manylinux-cuda116
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.9_cu116_upload
-          requires:
-          - nightly_binary_linux_conda_py3.9_cu116
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          cu_version: cu117
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.9_cu117
-          python_version: '3.9'
-          wheel_docker_image: pytorch/manylinux-cuda117
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.9_cu117_upload
-          requires:
-          - nightly_binary_linux_conda_py3.9_cu117
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.10_cpu
-          python_version: '3.10'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.10_cpu_upload
-          requires:
-          - nightly_binary_linux_conda_py3.10_cpu
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda116
-          cu_version: cu116
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.10_cu116
-          python_version: '3.10'
-          wheel_docker_image: pytorch/manylinux-cuda116
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.10_cu116_upload
-          requires:
-          - nightly_binary_linux_conda_py3.10_cu116
-      - binary_linux_conda:
-          conda_docker_image: pytorch/conda-builder:cuda117
-          cu_version: cu117
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.10_cu117
-          python_version: '3.10'
-          wheel_docker_image: pytorch/manylinux-cuda117
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_linux_conda_py3.10_cu117_upload
-          requires:
-          - nightly_binary_linux_conda_py3.10_cu117
-      - binary_macos_conda:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_macos_conda_py3.7_cpu
-          python_version: '3.7'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_macos_conda_py3.7_cpu_upload
-          requires:
-          - nightly_binary_macos_conda_py3.7_cpu
-      - binary_macos_conda:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_macos_conda_py3.8_cpu
-          python_version: '3.8'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_macos_conda_py3.8_cpu_upload
-          requires:
-          - nightly_binary_macos_conda_py3.8_cpu
-      - binary_macos_conda:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_macos_conda_py3.9_cpu
-          python_version: '3.9'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_macos_conda_py3.9_cpu_upload
-          requires:
-          - nightly_binary_macos_conda_py3.9_cpu
-      - binary_macos_conda:
-          conda_docker_image: pytorch/conda-builder:cpu
-          cu_version: cpu
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_macos_conda_py3.10_cpu
-          python_version: '3.10'
-          wheel_docker_image: pytorch/manylinux-cpu
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_macos_conda_py3.10_cpu_upload
-          requires:
-          - nightly_binary_macos_conda_py3.10_cpu
-      - binary_win_conda:
-          cu_version: cpu
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.7_cpu
-          python_version: '3.7'
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.7_cpu_upload
-          requires:
-          - nightly_binary_win_conda_py3.7_cpu
-      - binary_win_conda:
-          cu_version: cu116
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.7_cu116
-          python_version: '3.7'
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.7_cu116_upload
-          requires:
-          - nightly_binary_win_conda_py3.7_cu116
-      - binary_win_conda:
-          cu_version: cu117
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.7_cu117
-          python_version: '3.7'
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.7_cu117_upload
-          requires:
-          - nightly_binary_win_conda_py3.7_cu117
-      - binary_win_conda:
-          cu_version: cpu
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.8_cpu
-          python_version: '3.8'
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.8_cpu_upload
-          requires:
-          - nightly_binary_win_conda_py3.8_cpu
-      - binary_win_conda:
-          cu_version: cu116
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.8_cu116
-          python_version: '3.8'
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.8_cu116_upload
-          requires:
-          - nightly_binary_win_conda_py3.8_cu116
-      - binary_win_conda:
-          cu_version: cu117
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.8_cu117
-          python_version: '3.8'
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.8_cu117_upload
-          requires:
-          - nightly_binary_win_conda_py3.8_cu117
-      - binary_win_conda:
-          cu_version: cpu
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.9_cpu
-          python_version: '3.9'
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.9_cpu_upload
-          requires:
-          - nightly_binary_win_conda_py3.9_cpu
-      - binary_win_conda:
-          cu_version: cu116
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.9_cu116
-          python_version: '3.9'
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.9_cu116_upload
-          requires:
-          - nightly_binary_win_conda_py3.9_cu116
-      - binary_win_conda:
-          cu_version: cu117
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.9_cu117
-          python_version: '3.9'
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.9_cu117_upload
-          requires:
-          - nightly_binary_win_conda_py3.9_cu117
-      - binary_win_conda:
-          cu_version: cpu
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.10_cpu
-          python_version: '3.10'
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.10_cpu_upload
-          requires:
-          - nightly_binary_win_conda_py3.10_cpu
-      - binary_win_conda:
-          cu_version: cu116
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.10_cu116
-          python_version: '3.10'
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.10_cu116_upload
-          requires:
-          - nightly_binary_win_conda_py3.10_cu116
-      - binary_win_conda:
-          cu_version: cu117
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.10_cu117
-          python_version: '3.10'
-      - binary_conda_upload:
-          context: org-member
-          filters:
-            branches:
-              only: nightly
-            tags:
-              only: /v[0-9]+(\.[0-9]+)*-rc[0-9]+/
-          name: nightly_binary_win_conda_py3.10_cu117_upload
-          requires:
-          - nightly_binary_win_conda_py3.10_cu117
-  docker_build:
-    triggers:
-      - schedule:
-          cron: "0 10 * * 0"
-          filters:
-            branches:
-              only:
-                - main
-    jobs:
-      - smoke_test_docker_image_build:
-          context: org-member

.circleci/config.yml.in

-version: 2.1
-
-# How to test the Linux jobs:
-#   - Install CircleCI local CLI: https://circleci.com/docs/2.0/local-cli/
-#   - circleci config process .circleci/config.yml > gen.yml && circleci local execute -c gen.yml --job binary_linux_wheel_py3.7
-#     - Replace binary_linux_wheel_py3.7 with the name of the job you want to test.
-#       Job names are 'name:' key.
-
-executors:
-  windows-cpu:
-    machine:
-      resource_class: windows.xlarge
-      image: windows-server-2019-vs2019:stable
-      shell: bash.exe
-
-  windows-gpu:
-    machine:
-      resource_class: windows.gpu.nvidia.medium
-      image: windows-server-2019-nvidia:stable
-      shell: bash.exe
-
-commands:
-  checkout_merge:
-    description: "checkout merge branch"
-    steps:
-      - checkout
-#     - run:
-#         name: Checkout merge branch
-#         command: |
-#           set -ex
-#           BRANCH=$(git rev-parse --abbrev-ref HEAD)
-#           if [[ "$BRANCH" != "main" ]]; then
-#             git fetch --force origin ${CIRCLE_BRANCH}/merge:merged/${CIRCLE_BRANCH}
-#             git checkout "merged/$CIRCLE_BRANCH"
-#           fi
-  designate_upload_channel:
-    description: "inserts the correct upload channel into ${BASH_ENV}"
-    steps:
-      - run:
-          name: adding UPLOAD_CHANNEL to BASH_ENV
-          command: |
-            our_upload_channel=test
-            echo "export UPLOAD_CHANNEL=${our_upload_channel}" >> ${BASH_ENV}
-
-  brew_update:
-    description: "Update Homebrew and install base formulae"
-    steps:
-      - run:
-          name: Update Homebrew
-          no_output_timeout: "10m"
-          command: |
-            set -ex
-
-            # Update repositories manually.
-            # Running `brew update` produces a comparison between the
-            # current checkout and the updated checkout, which takes a
-            # very long time because the existing checkout is 2y old.
-            for path in $(find /usr/local/Homebrew -type d -name .git)
-            do
-            cd $path/..
-            git fetch --depth=1 origin
-            git reset --hard origin/master
-            done
-
-            export HOMEBREW_NO_AUTO_UPDATE=1
-
-            # Install expect and moreutils so that we can call `unbuffer` and `ts`.
-            # moreutils installs a `parallel` executable by default, which conflicts
-            # with the executable from the GNU `parallel`, so we must unlink GNU
-            # `parallel` first, and relink it afterwards.
-            brew install coreutils
-            brew unlink parallel
-            brew install moreutils
-            brew link parallel --overwrite
-            brew install expect
-
-  brew_install:
-    description: "Install Homebrew formulae"
-    parameters:
-      formulae:
-        type: string
-        default: ""
-    steps:
-      - run:
-          name: Install << parameters.formulae >>
-          no_output_timeout: "10m"
-          command: |
-            set -ex
-            export HOMEBREW_NO_AUTO_UPDATE=1
-            brew install << parameters.formulae >>
-
-  run_brew_for_ios_build:
-    steps:
-      - brew_update
-      - brew_install:
-          formulae: libtool
-
-  apt_install:
-    parameters:
-      args:
-        type: string
-      descr:
-        type: string
-        default: ""
-      update:
-        type: boolean
-        default: true
-    steps:
-      - run:
-          name: >
-            <<^ parameters.descr >> apt install << parameters.args >> <</ parameters.descr >>
-            <<# parameters.descr >> << parameters.descr >>            <</ parameters.descr >>
-          command: |
-            <<# parameters.update >> sudo apt update -qy  <</ parameters.update >>
-            sudo apt install << parameters.args >>
-
-  pip_install:
-    parameters:
-      args:
-        type: string
-      descr:
-        type: string
-        default: ""
-      user:
-        type: boolean
-        default: true
-    steps:
-      - run:
-          name: >
-            <<^ parameters.descr >> pip install << parameters.args >> <</ parameters.descr >>
-            <<# parameters.descr >> << parameters.descr >>            <</ parameters.descr >>
-          command: >
-            pip install
-            <<# parameters.user >> --user <</ parameters.user >>
-            --progress-bar=off
-            << parameters.args >>
-
-  install_torchvision:
-    parameters:
-      editable:
-        type: boolean
-        default: true
-    steps:
-      - pip_install:
-          args: --pre torch -f https://download.pytorch.org/whl/test/cpu/torch_test.html
-          descr: Install PyTorch from nightly releases
-      - pip_install:
-          args: --no-build-isolation <<# parameters.editable >> --editable <</ parameters.editable >> .
-          descr: Install torchvision <<# parameters.editable >> in editable mode <</ parameters.editable >>
-
-  # Most of the test suite is handled by the `unittest` jobs, with completely different workflow and setup.
-  # This command can be used if only a selection of tests need to be run, for ad-hoc files.
-  run_tests_selective:
-    parameters:
-      file_or_dir:
-        type: string
-    steps:
-      - run:
-          name: Install test utilities
-          command: pip install --progress-bar=off pytest pytest-mock
-      - run:
-          name: Run tests
-          command: pytest --junitxml=test-results/junit.xml -v --durations 20 <<parameters.file_or_dir>>
-      - store_test_results:
-          path: test-results
-
-  download_model_weights:
-    parameters:
-      extract_roots:
-        type: string
-        default: "torchvision/models"
-      background:
-        type: boolean
-        default: true
-    steps:
-      - apt_install:
-          args: parallel wget
-          descr: Install download utilitites
-      - run:
-          name: Download model weights
-          background: << parameters.background >>
-          command: |
-            mkdir -p ~/.cache/torch/hub/checkpoints
-            python scripts/collect_model_urls.py << parameters.extract_roots >> \
-                | parallel -j0 'wget --no-verbose -O ~/.cache/torch/hub/checkpoints/`basename {}` {}\?source=ci'
-
-binary_common: &binary_common
-  parameters:
-    # Edit these defaults to do a release
-    build_version:
-      description: "version number of release binary; by default, build a nightly"
-      type: string
-      default: "0.14.1"
-    pytorch_version:
-      description: "PyTorch version to build against; by default, use a nightly"
-      type: string
-      default: "1.13.1"
-    # Don't edit these
-    python_version:
-      description: "Python version to build against (e.g., 3.7)"
-      type: string
-    cu_version:
-      description: "CUDA version to build against, in CU format (e.g., cpu or cu100)"
-      type: string
-      default: "cpu"
-    unicode_abi:
-      description: "Python 2.7 wheel only: whether or not we are cp27mu (default: no)"
-      type: string
-      default: ""
-    wheel_docker_image:
-      description: "Wheel only: what docker image to use"
-      type: string
-      default: ""
-    conda_docker_image:
-      description: "Conda only: what docker image to use"
-      type: string
-      default: "pytorch/conda-builder:cpu"
-  environment:
-    PYTHON_VERSION: << parameters.python_version >>
-    PYTORCH_VERSION: << parameters.pytorch_version >>
-    UNICODE_ABI: << parameters.unicode_abi >>
-    CU_VERSION: << parameters.cu_version >>
-    MACOSX_DEPLOYMENT_TARGET: 10.9
-
-torchvision_ios_params: &torchvision_ios_params
-  parameters:
-    build_environment:
-      type: string
-      default: ""
-    ios_arch:
-      type: string
-      default: ""
-    ios_platform:
-      type: string
-      default: ""
-  environment:
-    BUILD_ENVIRONMENT: << parameters.build_environment >>
-    IOS_ARCH: << parameters.ios_arch >>
-    IOS_PLATFORM: << parameters.ios_platform >>
-
-torchvision_android_params: &torchvision_android_params
-  parameters:
-    build_environment:
-      type: string
-      default: ""
-  environment:
-    BUILD_ENVIRONMENT: << parameters.build_environment >>
-
-smoke_test_common: &smoke_test_common
-  <<: *binary_common
-  docker:
-    - image: torchvision/smoke_test:latest
-
-jobs:
-  circleci_consistency:
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - checkout
-      - pip_install:
-          args: jinja2 pyyaml
-      - run:
-          name: Check CircleCI config consistency
-          command: |
-            python .circleci/regenerate.py
-            git diff --exit-code || (echo ".circleci/config.yml not in sync with config.yml.in! Run .circleci/regenerate.py to update config"; exit 1)
-
-  lint_python_and_config:
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - checkout
-      - pip_install:
-          args: pre-commit
-          descr: Install lint utilities
-      - run:
-          name: Install pre-commit hooks
-          command: pre-commit install-hooks
-      - run:
-          name: Lint Python code and config files
-          command: pre-commit run --all-files
-      - run:
-          name: Required lint modifications
-          when: on_fail
-          command: git --no-pager diff
-
-  lint_c:
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - apt_install:
-          args: libtinfo5
-          descr: Install additional system libraries
-      - checkout
-      - run:
-          name: Install lint utilities
-          command: |
-            curl https://oss-clang-format.s3.us-east-2.amazonaws.com/linux64/clang-format-linux64 -o clang-format
-            chmod +x clang-format
-            sudo mv clang-format /opt/clang-format
-      - run:
-          name: Lint C code
-          command: ./.circleci/unittest/linux/scripts/run-clang-format.py -r torchvision/csrc --clang-format-executable /opt/clang-format
-      - run:
-          name: Required lint modifications
-          when: on_fail
-          command: git --no-pager diff
-
-  type_check_python:
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - checkout
-      - install_torchvision:
-          editable: true
-      - pip_install:
-          args: mypy
-          descr: Install Python type check utilities
-      - run:
-          name: Check Python types statically
-          command: mypy --install-types --non-interactive --config-file mypy.ini
-
-  unittest_torchhub:
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - checkout
-      - install_torchvision
-      - run_tests_selective:
-          file_or_dir: test/test_hub.py
-
-  unittest_onnx:
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - checkout
-      - install_torchvision
-      - pip_install:
-          args: onnx onnxruntime
-          descr: Install ONNX
-      - run_tests_selective:
-          file_or_dir: test/test_onnx.py
-
-  unittest_extended:
-    docker:
-      - image: cimg/python:3.7
-    resource_class: xlarge
-    steps:
-      - checkout
-      - download_model_weights
-      - install_torchvision
-      - run:
-          name: Enable extended tests
-          command: echo 'export PYTORCH_TEST_WITH_EXTENDED=1' >> $BASH_ENV
-      - run_tests_selective:
-          file_or_dir: test/test_extended_*.py
-
-  binary_linux_wheel:
-    <<: *binary_common
-    docker:
-      - image: << parameters.wheel_docker_image >>
-    resource_class: 2xlarge+
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Build conda packages
-          no_output_timeout: 30m
-          command: |
-              set -ex
-              packaging/build_wheel.sh
-      - store_artifacts:
-          path: dist
-      - persist_to_workspace:
-          root: dist
-          paths:
-            - "*"
-
-  binary_linux_conda:
-    <<: *binary_common
-    docker:
-      - image: "<< parameters.conda_docker_image >>"
-    resource_class: 2xlarge+
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Build conda packages
-          no_output_timeout: 30m
-          command: |
-              set -ex
-              packaging/build_conda.sh
-      - store_artifacts:
-          path: /opt/conda/conda-bld/linux-64
-      - persist_to_workspace:
-          root: /opt/conda/conda-bld/linux-64
-          paths:
-            - "*"
-      - store_test_results:
-          path: build_results/
-
-  binary_win_conda:
-    <<: *binary_common
-    executor: windows-cpu
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Build conda packages
-          no_output_timeout: 30m
-          command: |
-            set -ex
-            source packaging/windows/internal/vc_install_helper.sh
-            packaging/windows/internal/cuda_install.bat
-            eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
-            conda activate base
-            conda install -yq conda-build "conda-package-handling!=1.5.0"
-            packaging/build_conda.sh
-            rm /C/tools/miniconda3/conda-bld/win-64/vs${VC_YEAR}*.tar.bz2
-      - store_artifacts:
-          path: C:/tools/miniconda3/conda-bld/win-64
-      - persist_to_workspace:
-          root: C:/tools/miniconda3/conda-bld/win-64
-          paths:
-            - "*"
-      - store_test_results:
-          path: build_results/
-
-  binary_win_wheel:
-    <<: *binary_common
-    executor: windows-cpu
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Build wheel packages
-          no_output_timeout: 30m
-          command: |
-            set -ex
-            source packaging/windows/internal/vc_install_helper.sh
-            packaging/windows/internal/cuda_install.bat
-            packaging/build_wheel.sh
-      - store_artifacts:
-          path: dist
-      - persist_to_workspace:
-          root: dist
-          paths:
-            - "*"
-      - store_test_results:
-          path: build_results/
-
-  binary_macos_wheel:
-    <<: *binary_common
-    macos:
-      xcode: "14.0"
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          # Cannot easily deduplicate this as source'ing activate
-          # will set environment variables which we need to propagate
-          # to build_wheel.sh
-          command: |
-            curl -o conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
-            sh conda.sh -b
-            source $HOME/miniconda3/bin/activate
-            packaging/build_wheel.sh
-      - store_artifacts:
-          path: dist
-      - persist_to_workspace:
-          root: dist
-          paths:
-            - "*"
-
-  binary_ios_build:
-    <<: *torchvision_ios_params
-    macos:
-      xcode: "14.0"
-    steps:
-    - attach_workspace:
-        at: ~/workspace
-    - checkout
-    - run_brew_for_ios_build
-    - run:
-        name: Build
-        no_output_timeout: "1h"
-        command: |
-          script="/Users/distiller/project/.circleci/unittest/ios/scripts/binary_ios_build.sh"
-          cat "$script"
-          source "$script"
-    - persist_to_workspace:
-        root: /Users/distiller/workspace/
-        paths: ios
-
-  binary_ios_upload:
-    <<: *torchvision_ios_params
-    macos:
-      xcode: "14.0"
-    steps:
-    - attach_workspace:
-        at: ~/workspace
-    - checkout
-    - run_brew_for_ios_build
-    - run:
-        name: Upload
-        no_output_timeout: "1h"
-        command: |
-          script="/Users/distiller/project/.circleci/unittest/ios/scripts/binary_ios_upload.sh"
-          cat "$script"
-          source "$script"
-
-  binary_android_build:
-    <<: *torchvision_android_params
-    docker:
-      - image: cimg/android:2021.08-ndk
-    resource_class: xlarge
-    steps:
-    - attach_workspace:
-        at: ~/workspace
-    - checkout
-    - run:
-        name: Build
-        no_output_timeout: "1h"
-        command: |
-          script="/home/circleci/project/.circleci/unittest/android/scripts/binary_android_build.sh"
-          cat "$script"
-          source "$script"
-    - store_artifacts:
-        path: ~/workspace/artifacts
-
-  binary_android_upload:
-    <<: *torchvision_android_params
-    docker:
-      - image: cimg/android:2021.08-ndk
-    resource_class: xlarge
-    steps:
-    - attach_workspace:
-        at: ~/workspace
-    - checkout
-    - run:
-        name: Upload
-        no_output_timeout: "1h"
-        command: |
-          script="/home/circleci/project/.circleci/unittest/android/scripts/binary_android_upload.sh"
-          cat "$script"
-          source "$script"
-
-  binary_macos_conda:
-    <<: *binary_common
-    macos:
-      xcode: "14.0"
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          command: |
-            curl -o conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
-            sh conda.sh -b
-            source $HOME/miniconda3/bin/activate
-            conda install -yq conda-build
-            packaging/build_conda.sh
-      - store_artifacts:
-          path: /Users/distiller/miniconda3/conda-bld/osx-64
-      - persist_to_workspace:
-          root: /Users/distiller/miniconda3/conda-bld/osx-64
-          paths:
-            - "*"
-      - store_test_results:
-          path: build_results/
-
-  # Requires org-member context
-  binary_conda_upload:
-    docker:
-      - image: continuumio/miniconda
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - designate_upload_channel
-      - run:
-          command: |
-            # Prevent credential from leaking
-            conda install -yq anaconda-client
-            set -x
-            anaconda  -t "${CONDA_PYTORCHBOT_TOKEN}" upload ~/workspace/*.tar.bz2 -u "pytorch-${UPLOAD_CHANNEL}" --label main --no-progress --force
-
-  # Requires org-member context
-  binary_wheel_upload:
-    parameters:
-      subfolder:
-        description: "What whl subfolder to upload to, e.g., blank or cu100/ (trailing slash is important)"
-        type: string
-    docker:
-      - image: cimg/python:3.7
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - designate_upload_channel
-      - checkout
-      - pip_install:
-          args: awscli
-      - run:
-          command: |
-            export PATH="$HOME/.local/bin:$PATH"
-            # Prevent credential from leaking
-            set +x
-            export AWS_ACCESS_KEY_ID="${PYTORCH_BINARY_AWS_ACCESS_KEY_ID}"
-            export AWS_SECRET_ACCESS_KEY="${PYTORCH_BINARY_AWS_SECRET_ACCESS_KEY}"
-            set -x
-            for pkg in ~/workspace/*.whl; do
-              aws s3 cp "$pkg" "s3://pytorch/whl/${UPLOAD_CHANNEL}/<< parameters.subfolder >>" --acl public-read
-            done
-
-  smoke_test_linux_conda:
-    <<: *smoke_test_common
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - designate_upload_channel
-      - run:
-          name: install binaries
-          command: |
-            set -x
-            source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
-            conda install -v -y -c pytorch-nightly pytorch
-            conda install -v -y $(ls ~/workspace/torchvision*.tar.bz2)
-      - run:
-          name: smoke test
-          command: |
-            source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
-            python -c "import torchvision"
-
-  smoke_test_linux_pip:
-    <<: *smoke_test_common
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - designate_upload_channel
-      - run:
-          name: install binaries
-          command: |
-            set -x
-            source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
-      - pip_install:
-          args: $(ls ~/workspace/torchvision*.whl) --pre -f https://download.pytorch.org/whl/test/torch_test.html
-      - run:
-          name: smoke test
-          command: |
-            source /usr/local/etc/profile.d/conda.sh && conda activate python${PYTHON_VERSION}
-            python -c "import torchvision"
-
-  smoke_test_docker_image_build:
-    machine:
-      image: ubuntu-2004:202104-01
-    resource_class: large
-    environment:
-      image_name: torchvision/smoke_test
-    steps:
-      - checkout
-      - designate_upload_channel
-      - run:
-          name: Build and push Docker image
-          no_output_timeout: "1h"
-          command: |
-            set +x
-            echo "${DOCKER_HUB_TOKEN}" | docker login --username "${DOCKER_HUB_USERNAME}" --password-stdin
-            set -x
-            cd .circleci/smoke_test/docker && docker build . -t ${image_name}:${CIRCLE_WORKFLOW_ID}
-            docker tag ${image_name}:${CIRCLE_WORKFLOW_ID} ${image_name}:latest
-            docker push ${image_name}:${CIRCLE_WORKFLOW_ID}
-            docker push ${image_name}:latest
-
-  smoke_test_win_conda:
-    <<: *binary_common
-    executor:
-      name: windows-cpu
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - designate_upload_channel
-      - run:
-          name: install binaries
-          command: |
-            set -x
-            eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
-            conda env remove -n python${PYTHON_VERSION} || true
-            conda create -yn python${PYTHON_VERSION} python=${PYTHON_VERSION}
-            conda activate python${PYTHON_VERSION}
-            conda install -v -y -c pytorch-nightly pytorch
-            conda install -v -y $(ls ~/workspace/torchvision*.tar.bz2)
-      - run:
-          name: smoke test
-          command: |
-            eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
-            conda activate python${PYTHON_VERSION}
-            python -c "import torchvision"
-
-  smoke_test_win_pip:
-    <<: *binary_common
-    executor:
-      name: windows-cpu
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - designate_upload_channel
-      - run:
-          name: install binaries
-          command: |
-            set -x
-            eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
-            conda create -yn python${PYTHON_VERSION} python=${PYTHON_VERSION}
-            conda activate python${PYTHON_VERSION}
-      - pip_install:
-          args: $(ls ~/workspace/torchvision*.whl) --pre -f https://download.pytorch.org/whl/test/torch_test.html
-      - run:
-          name: smoke test
-          command: |
-            eval "$('/C/tools/miniconda3/Scripts/conda.exe' 'shell.bash' 'hook')"
-            conda activate python${PYTHON_VERSION}
-            python -c "import torchvision"
-
-  unittest_linux_cpu:
-    <<: *binary_common
-    docker:
-      - image: "pytorch/manylinux-cpu"
-    resource_class: 2xlarge+
-    steps:
-      - checkout
-      - designate_upload_channel
-      - run:
-          name: Generate cache key
-          # This will refresh cache on Sundays, nightly build should generate new cache.
-          command: echo "$(date +"%Y-%U")" > .circleci-weekly
-      - restore_cache:
-          {% raw %}
-          keys:
-            - env-v2-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-          {% endraw %}
-      - run:
-          name: Setup
-          command: .circleci/unittest/linux/scripts/setup_env.sh
-      - save_cache:
-          {% raw %}
-          key: env-v2-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-          {% endraw %}
-          paths:
-            - conda
-            - env
-      - run:
-          name: Install torchvision
-          command: .circleci/unittest/linux/scripts/install.sh
-      - run:
-          name: Run tests
-          command: .circleci/unittest/linux/scripts/run_test.sh
-      - run:
-          name: Post process
-          command: .circleci/unittest/linux/scripts/post_process.sh
-      - store_test_results:
-          path: test-results
-
-  unittest_linux_gpu:
-    <<: *binary_common
-    machine:
-      image: ubuntu-2004-cuda-11.4:202110-01
-    resource_class: gpu.nvidia.medium
-    environment:
-      image_name: "pytorch/manylinux-cuda116"
-      CU_VERSION: << parameters.cu_version >>
-      PYTHON_VERSION: << parameters.python_version >>
-    steps:
-      - checkout
-      - designate_upload_channel
-      - run:
-          name: Generate cache key
-          # This will refresh cache on Sundays, nightly build should generate new cache.
-          command: echo "$(date +"%Y-%U")" > .circleci-weekly
-      - restore_cache:
-          {% raw %}
-          keys:
-            - env-v3-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-          {% endraw %}
-      - run:
-          name: Setup
-          command: docker run -e PYTHON_VERSION -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/setup_env.sh
-      - save_cache:
-          {% raw %}
-          key: env-v3-linux-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-          {% endraw %}
-          paths:
-            - conda
-            - env
-      - run:
-          # Here we create an envlist file that contains some env variables that we want the docker container to be aware of.
-          # Normally, the CIRCLECI variable is set and available on all CI workflows: https://circleci.com/docs/2.0/env-vars/#built-in-environment-variables.
-          # They're avaiable in all the other workflows (OSX and Windows).
-          # But here, we're running the unittest_linux_gpu workflows in a docker container, where those variables aren't accessible.
-          # So instead we dump the variables we need in env.list and we pass that file when invoking "docker run".
-          name: export CIRCLECI env var
-          command: echo "CIRCLECI=true" >> ./env.list
-      - run:
-          name: Install torchvision
-          command: docker run -t --gpus all -v $PWD:$PWD -w $PWD -e UPLOAD_CHANNEL -e CU_VERSION "${image_name}" .circleci/unittest/linux/scripts/install.sh
-      - run:
-          name: Run tests
-          command: docker run --env-file ./env.list -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/run_test.sh
-      - run:
-          name: Post Process
-          command: docker run -t --gpus all -v $PWD:$PWD -w $PWD "${image_name}" .circleci/unittest/linux/scripts/post_process.sh
-      - store_test_results:
-          path: test-results
-
-  unittest_windows_cpu:
-    <<: *binary_common
-    executor:
-      name: windows-cpu
-    steps:
-      - checkout
-      - designate_upload_channel
-      - run:
-          name: Generate cache key
-          # This will refresh cache on Sundays, nightly build should generate new cache.
-          command: echo "$(date +"%Y-%U")" > .circleci-weekly
-      - restore_cache:
-          {% raw %}
-          keys:
-            - env-v2-windows-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/windows/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-          {% endraw %}
-      - run:
-          name: Setup
-          command: .circleci/unittest/windows/scripts/setup_env.sh
-      - save_cache:
-          {% raw %}
-          key: env-v2-windows-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/windows/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-          {% endraw %}
-          paths:
-            - conda
-            - env
-      - run:
-          name: Install torchvision
-          command: .circleci/unittest/windows/scripts/install.sh
-      - run:
-          name: Run tests
-          command: .circleci/unittest/windows/scripts/run_test.sh
-      - run:
-          name: Post process
-          command: .circleci/unittest/windows/scripts/post_process.sh
-      - store_test_results:
-          path: test-results
-
-  unittest_windows_gpu:
-    <<: *binary_common
-    executor:
-      name: windows-gpu
-    environment:
-      CUDA_VERSION: "11.6"
-      PYTHON_VERSION: << parameters.python_version >>
-    steps:
-      - checkout
-      - designate_upload_channel
-      - run:
-          name: Generate cache key
-          # This will refresh cache on Sundays, nightly build should generate new cache.
-          command: echo "$(date +"%Y-%U")" > .circleci-weekly
-      - restore_cache:
-          {% raw %}
-          keys:
-            - env-v1-windows-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/windows/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-          {% endraw %}
-      - run:
-          name: Setup
-          command: .circleci/unittest/windows/scripts/setup_env.sh
-      - save_cache:
-          {% raw %}
-          key: env-v1-windows-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/windows/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-          {% endraw %}
-          paths:
-            - conda
-            - env
-      - run:
-          name: Install CUDA
-          command: packaging/windows/internal/cuda_install.bat
-      - run:
-          name: Update CUDA driver
-          command: packaging/windows/internal/driver_update.bat
-      - run:
-          name: Install torchvision
-          command: .circleci/unittest/windows/scripts/install.sh
-      - run:
-          name: Run tests
-          command: .circleci/unittest/windows/scripts/run_test.sh
-      - run:
-          name: Post process
-          command: .circleci/unittest/windows/scripts/post_process.sh
-      - store_test_results:
-          path: test-results
-
-  unittest_macos_cpu:
-    <<: *binary_common
-    macos:
-      xcode: "14.0"
-    resource_class: large
-    steps:
-      - checkout
-      - designate_upload_channel
-      - run:
-          name: Install wget
-          command: HOMEBREW_NO_AUTO_UPDATE=1 brew install wget
-          # Disable brew auto update which is very slow
-      - run:
-          name: Generate cache key
-          # This will refresh cache on Sundays, nightly build should generate new cache.
-          command: echo "$(date +"%Y-%U")" > .circleci-weekly
-      - restore_cache:
-          {% raw %}
-          keys:
-            - env-v3-macos-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-          {% endraw %}
-      - run:
-          name: Setup
-          command: .circleci/unittest/linux/scripts/setup_env.sh
-      - save_cache:
-          {% raw %}
-          key: env-v3-macos-{{ arch }}-py<< parameters.python_version >>-{{ checksum ".circleci/unittest/linux/scripts/environment.yml" }}-{{ checksum ".circleci-weekly" }}
-          {% endraw %}
-          paths:
-            - conda
-            - env
-      - run:
-          name: Install torchvision
-          command: .circleci/unittest/linux/scripts/install.sh
-      - run:
-          name: Run tests
-          command: .circleci/unittest/linux/scripts/run_test.sh
-      - run:
-          name: Post process
-          command: .circleci/unittest/linux/scripts/post_process.sh
-      - store_test_results:
-          path: test-results
-
-  cmake_linux_cpu:
-    <<: *binary_common
-    docker:
-      - image: "pytorch/manylinux-cpu"
-    resource_class: 2xlarge+
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Setup conda
-          command: .circleci/unittest/linux/scripts/setup_env.sh
-      - run: packaging/build_cmake.sh
-
-  cmake_linux_gpu:
-    <<: *binary_common
-    machine:
-      image: ubuntu-2004-cuda-11.4:202110-01
-    resource_class: gpu.nvidia.small
-    environment:
-      PYTHON_VERSION: << parameters.python_version >>
-      PYTORCH_VERSION: << parameters.pytorch_version >>
-      UNICODE_ABI: << parameters.unicode_abi >>
-      CU_VERSION: << parameters.cu_version >>
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Setup conda
-          command: docker run -e CU_VERSION -e PYTHON_VERSION -e UNICODE_ABI -e PYTORCH_VERSION -t --gpus all -v $PWD:$PWD -w $PWD << parameters.wheel_docker_image >> .circleci/unittest/linux/scripts/setup_env.sh
-      - run:
-          name: Build torchvision C++ distribution and test
-          no_output_timeout: 30m
-          command: docker run -e CU_VERSION -e PYTHON_VERSION -e UNICODE_ABI -e PYTORCH_VERSION -e UPLOAD_CHANNEL -t --gpus all -v $PWD:$PWD -w $PWD << parameters.wheel_docker_image >> packaging/build_cmake.sh
-
-  cmake_macos_cpu:
-    <<: *binary_common
-    macos:
-      xcode: "14.0"
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          command: |
-            curl -o conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
-            sh conda.sh -b
-            source $HOME/miniconda3/bin/activate
-            conda install -yq conda-build cmake
-            packaging/build_cmake.sh
-
-  cmake_windows_cpu:
-    <<: *binary_common
-    executor:
-      name: windows-cpu
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          command: |
-            set -ex
-            source packaging/windows/internal/vc_install_helper.sh
-            packaging/build_cmake.sh
-
-  cmake_windows_gpu:
-    <<: *binary_common
-    executor:
-      name: windows-gpu
-    steps:
-      - checkout_merge
-      - designate_upload_channel
-      - run:
-          name: Update CUDA driver
-          command: packaging/windows/internal/driver_update.bat
-      - run:
-          command: |
-            set -ex
-            source packaging/windows/internal/vc_install_helper.sh
-            packaging/windows/internal/cuda_install.bat
-            packaging/build_cmake.sh
-
-  build_docs:
-    <<: *binary_common
-    docker:
-      - image: cimg/python:3.7
-    resource_class: 2xlarge+
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - checkout
-      - download_model_weights
-      - run:
-          name: Setup
-          command: .circleci/unittest/linux/scripts/setup_env.sh
-      - designate_upload_channel
-      - run:
-          name: Install torchvision
-          command: .circleci/unittest/linux/scripts/install.sh
-      - run:
-          name: Build docs
-          command: |
-            set -ex
-            # turn v1.12.0rc3 into 1.12.0
-            tag=$(echo $CIRCLE_TAG | sed -e 's/v*\([0-9.]*\).*/\1/')
-            VERSION=${tag:-main}
-            eval "$(./conda/bin/conda shell.bash hook)"
-            conda activate ./env
-            pushd docs
-            pip install --progress-bar=off -r requirements.txt
-            make html
-            popd
-      - persist_to_workspace:
-          root: ./
-          paths:
-            - "*"
-      - store_artifacts:
-          path: ./docs/build/html
-          destination: docs
-
-  upload_docs:
-    <<: *binary_common
-    docker:
-      - image: "pytorch/manylinux-cuda100"
-    resource_class: 2xlarge+
-    steps:
-      - attach_workspace:
-          at: ~/workspace
-      - run:
-          name: Generate netrc
-          command: |
-            # set credentials for https pushing
-            # requires the org-member context
-            cat > ~/.netrc \<<DONE
-              machine github.com
-              login pytorchbot
-              password ${GITHUB_PYTORCHBOT_TOKEN}
-            DONE
-      - run:
-          name: Upload docs
-          command: |
-            # Don't use "checkout" step since it uses ssh, which cannot git push
-            # https://circleci.com/docs/2.0/configuration-reference/#checkout
-            set -ex
-            # Change v1.12.1rc1 into 1.12 (only major.minor)
-            tag=$(echo $CIRCLE_TAG | sed -e 's/v*\([0-9]*\.[0-9]*\).*/\1/')
-            target=${tag:-main}
-            ~/workspace/.circleci/build_docs/commit_docs.sh ~/workspace $target
-
-
-workflows:
-  lint:
-    jobs:
-      - circleci_consistency
-      - lint_python_and_config
-      - lint_c
-      - type_check_python
-
-  build:
-    jobs:
-      {{ build_workflows(windows_latest_only=True) }}
-      {{ ios_workflows() }}
-      {{ android_workflows() }}
-
-  unittest:
-    jobs:
-      - unittest_torchhub
-      - unittest_onnx
-      - unittest_extended
-      {{ unittest_workflows() }}
-
-  cmake:
-    jobs:
-      {{ cmake_workflows() }}
-
-  nightly:
-    jobs:
-      {{ ios_workflows(nightly=True) }}
-      {{ android_workflows(nightly=True) }}
-      {{ build_workflows(prefix="nightly_", filter_branch="nightly", upload=True) }}
-  docker_build:
-    triggers:
-      - schedule:
-          cron: "0 10 * * 0"
-          filters:
-            branches:
-              only:
-                - main
-    jobs:
-      - smoke_test_docker_image_build:
-          context: org-member

.circleci/regenerate.py

-#!/usr/bin/env python3
-
-"""
-This script should use a very simple, functional programming style.
-Avoid Jinja macros in favor of native Python functions.
-
-Don't go overboard on code generation; use Python only to generate
-content that can't be easily declared statically using CircleCI's YAML API.
-
-Data declarations (e.g. the nested loops for defining the configuration matrix)
-should be at the top of the file for easy updating.
-
-See this comment for design rationale:
-https://github.com/pytorch/vision/pull/1321#issuecomment-531033978
-"""
-
-import os.path
-
-import jinja2
-import yaml
-from jinja2 import select_autoescape
-
-
-PYTHON_VERSIONS = ["3.7", "3.8", "3.9", "3.10"]
-
-RC_PATTERN = r"/v[0-9]+(\.[0-9]+)*-rc[0-9]+/"
-
-
-def build_workflows(prefix="", filter_branch=None, upload=False, indentation=6, windows_latest_only=False):
-    w = []
-    for btype in ["wheel", "conda"]:
-        for os_type in ["linux", "macos", "win"]:
-            python_versions = PYTHON_VERSIONS
-            cu_versions_dict = {
-                "linux": ["cpu", "cu116", "cu117", "rocm5.1.1", "rocm5.2"],
-                "win": ["cpu", "cu116", "cu117"],
-                "macos": ["cpu"],
-            }
-            cu_versions = cu_versions_dict[os_type]
-            for python_version in python_versions:
-                for cu_version in cu_versions:
-                    # ROCm conda packages not yet supported
-                    if cu_version.startswith("rocm") and btype == "conda":
-                        continue
-                    for unicode in [False]:
-                        fb = filter_branch
-                        if (
-                            windows_latest_only
-                            and os_type == "win"
-                            and filter_branch is None
-                            and (
-                                python_version != python_versions[-1]
-                                or (cu_version not in [cu_versions[0], cu_versions[-1]])
-                            )
-                        ):
-                            fb = "main"
-                        if not fb and (
-                            os_type == "linux" and cu_version == "cpu" and btype == "wheel" and python_version == "3.7"
-                        ):
-                            # the fields must match the build_docs "requires" dependency
-                            fb = "/.*/"
-                        w += workflow_pair(
-                            btype, os_type, python_version, cu_version, unicode, prefix, upload, filter_branch=fb
-                        )
-
-    if not filter_branch:
-        # Build on every pull request, but upload only on nightly and tags
-        w += build_doc_job("/.*/")
-        w += upload_doc_job("nightly")
-    return indent(indentation, w)
-
-
-def workflow_pair(btype, os_type, python_version, cu_version, unicode, prefix="", upload=False, *, filter_branch=None):
-
-    w = []
-    unicode_suffix = "u" if unicode else ""
-    base_workflow_name = f"{prefix}binary_{os_type}_{btype}_py{python_version}{unicode_suffix}_{cu_version}"
-
-    w.append(
-        generate_base_workflow(
-            base_workflow_name, python_version, cu_version, unicode, os_type, btype, filter_branch=filter_branch
-        )
-    )
-
-    if upload:
-        w.append(generate_upload_workflow(base_workflow_name, os_type, btype, cu_version, filter_branch=filter_branch))
-        # disable smoke tests, they are broken and needs to be fixed
-        # if filter_branch == "nightly" and os_type in ["linux", "win"]:
-        #     pydistro = "pip" if btype == "wheel" else "conda"
-        #     w.append(generate_smoketest_workflow(pydistro, base_workflow_name, filter_branch, python_version, os_type))
-
-    return w
-
-
-def build_doc_job(filter_branch):
-    job = {
-        "name": "build_docs",
-        "python_version": "3.7",
-        "requires": [
-            "binary_linux_wheel_py3.7_cpu",
-        ],
-    }
-
-    if filter_branch:
-        job["filters"] = gen_filter_branch_tree(filter_branch, tags_list=RC_PATTERN)
-    return [{"build_docs": job}]
-
-
-def upload_doc_job(filter_branch):
-    job = {
-        "name": "upload_docs",
-        "context": "org-member",
-        "python_version": "3.7",
-        "requires": [
-            "build_docs",
-        ],
-    }
-
-    if filter_branch:
-        job["filters"] = gen_filter_branch_tree(filter_branch, tags_list=RC_PATTERN)
-    return [{"upload_docs": job}]
-
-
-manylinux_images = {
-    "cu116": "pytorch/manylinux-cuda116",
-    "cu117": "pytorch/manylinux-cuda117",
-}
-
-
-def get_manylinux_image(cu_version):
-    if cu_version == "cpu":
-        return "pytorch/manylinux-cpu"
-    elif cu_version.startswith("cu"):
-        cu_suffix = cu_version[len("cu") :]
-        return f"pytorch/manylinux-cuda{cu_suffix}"
-    elif cu_version.startswith("rocm"):
-        rocm_suffix = cu_version[len("rocm") :]
-        return f"pytorch/manylinux-rocm:{rocm_suffix}"
-
-
-def get_conda_image(cu_version):
-    if cu_version == "cpu":
-        return "pytorch/conda-builder:cpu"
-    elif cu_version.startswith("cu"):
-        cu_suffix = cu_version[len("cu") :]
-        return f"pytorch/conda-builder:cuda{cu_suffix}"
-
-
-def generate_base_workflow(
-    base_workflow_name, python_version, cu_version, unicode, os_type, btype, *, filter_branch=None
-):
-
-    d = {
-        "name": base_workflow_name,
-        "python_version": python_version,
-        "cu_version": cu_version,
-    }
-
-    if os_type != "win" and unicode:
-        d["unicode_abi"] = "1"
-
-    if os_type != "win":
-        d["wheel_docker_image"] = get_manylinux_image(cu_version)
-        # ROCm conda packages not yet supported
-        if "rocm" not in cu_version:
-            d["conda_docker_image"] = get_conda_image(cu_version)
-
-    if filter_branch is not None:
-        d["filters"] = {
-            "branches": {"only": filter_branch},
-            "tags": {
-                # Using a raw string here to avoid having to escape
-                # anything
-                "only": r"/v[0-9]+(\.[0-9]+)*-rc[0-9]+/"
-            },
-        }
-
-    w = f"binary_{os_type}_{btype}"
-    return {w: d}
-
-
-def gen_filter_branch_tree(*branches, tags_list=None):
-    filter_dict = {"branches": {"only": [b for b in branches]}}
-    if tags_list is not None:
-        filter_dict["tags"] = {"only": tags_list}
-    return filter_dict
-
-
-def generate_upload_workflow(base_workflow_name, os_type, btype, cu_version, *, filter_branch=None):
-    d = {
-        "name": f"{base_workflow_name}_upload",
-        "context": "org-member",
-        "requires": [base_workflow_name],
-    }
-
-    if btype == "wheel":
-        d["subfolder"] = "" if os_type == "macos" else cu_version + "/"
-
-    if filter_branch is not None:
-        d["filters"] = {
-            "branches": {"only": filter_branch},
-            "tags": {
-                # Using a raw string here to avoid having to escape
-                # anything
-                "only": r"/v[0-9]+(\.[0-9]+)*-rc[0-9]+/"
-            },
-        }
-
-    return {f"binary_{btype}_upload": d}
-
-
-def generate_smoketest_workflow(pydistro, base_workflow_name, filter_branch, python_version, os_type):
-
-    required_build_suffix = "_upload"
-    required_build_name = base_workflow_name + required_build_suffix
-
-    smoke_suffix = f"smoke_test_{pydistro}"
-    d = {
-        "name": f"{base_workflow_name}_{smoke_suffix}",
-        "requires": [required_build_name],
-        "python_version": python_version,
-    }
-
-    if filter_branch:
-        d["filters"] = gen_filter_branch_tree(filter_branch)
-
-    return {f"smoke_test_{os_type}_{pydistro}": d}
-
-
-def indent(indentation, data_list):
-    return ("\n" + " " * indentation).join(yaml.dump(data_list, default_flow_style=False).splitlines())
-
-
-def unittest_workflows(indentation=6):
-    jobs = []
-    for os_type in ["linux", "windows", "macos"]:
-        for device_type in ["cpu", "gpu"]:
-            if os_type == "macos" and device_type == "gpu":
-                continue
-            for i, python_version in enumerate(PYTHON_VERSIONS):
-                job = {
-                    "name": f"unittest_{os_type}_{device_type}_py{python_version}",
-                    "python_version": python_version,
-                }
-
-                if device_type == "gpu":
-                    if python_version != "3.8":
-                        job["filters"] = gen_filter_branch_tree("main", "nightly")
-                    job["cu_version"] = "cu116"
-                else:
-                    job["cu_version"] = "cpu"
-
-                jobs.append({f"unittest_{os_type}_{device_type}": job})
-
-    return indent(indentation, jobs)
-
-
-def cmake_workflows(indentation=6):
-    jobs = []
-    python_version = "3.8"
-    for os_type in ["linux", "windows", "macos"]:
-        # Skip OSX CUDA
-        device_types = ["cpu", "gpu"] if os_type != "macos" else ["cpu"]
-        for device in device_types:
-            job = {"name": f"cmake_{os_type}_{device}", "python_version": python_version}
-
-            job["cu_version"] = "cu116" if device == "gpu" else "cpu"
-            if device == "gpu" and os_type == "linux":
-                job["wheel_docker_image"] = "pytorch/manylinux-cuda116"
-            jobs.append({f"cmake_{os_type}_{device}": job})
-    return indent(indentation, jobs)
-
-
-def ios_workflows(indentation=6, nightly=False):
-    jobs = []
-    build_job_names = []
-    name_prefix = "nightly_" if nightly else ""
-    env_prefix = "nightly-" if nightly else ""
-    for arch, platform in [("x86_64", "SIMULATOR"), ("arm64", "OS")]:
-        name = f"{name_prefix}binary_libtorchvision_ops_ios_12.0.0_{arch}"
-        build_job_names.append(name)
-        build_job = {
-            "build_environment": f"{env_prefix}binary-libtorchvision_ops-ios-12.0.0-{arch}",
-            "ios_arch": arch,
-            "ios_platform": platform,
-            "name": name,
-        }
-        if nightly:
-            build_job["filters"] = gen_filter_branch_tree("nightly")
-        jobs.append({"binary_ios_build": build_job})
-
-    if nightly:
-        upload_job = {
-            "build_environment": f"{env_prefix}binary-libtorchvision_ops-ios-12.0.0-upload",
-            "context": "org-member",
-            "filters": gen_filter_branch_tree("nightly"),
-            "requires": build_job_names,
-        }
-        jobs.append({"binary_ios_upload": upload_job})
-    return indent(indentation, jobs)
-
-
-def android_workflows(indentation=6, nightly=False):
-    jobs = []
-    build_job_names = []
-    name_prefix = "nightly_" if nightly else ""
-    env_prefix = "nightly-" if nightly else ""
-
-    name = f"{name_prefix}binary_libtorchvision_ops_android"
-    build_job_names.append(name)
-    build_job = {
-        "build_environment": f"{env_prefix}binary-libtorchvision_ops-android",
-        "name": name,
-    }
-
-    if nightly:
-        upload_job = {
-            "build_environment": f"{env_prefix}binary-libtorchvision_ops-android-upload",
-            "context": "org-member",
-            "filters": gen_filter_branch_tree("nightly"),
-            "name": f"{name_prefix}binary_libtorchvision_ops_android_upload",
-        }
-        jobs.append({"binary_android_upload": upload_job})
-    else:
-        jobs.append({"binary_android_build": build_job})
-    return indent(indentation, jobs)
-
-
-if __name__ == "__main__":
-    d = os.path.dirname(__file__)
-    env = jinja2.Environment(
-        loader=jinja2.FileSystemLoader(d),
-        lstrip_blocks=True,
-        autoescape=select_autoescape(enabled_extensions=("html", "xml")),
-        keep_trailing_newline=True,
-    )
-
-    with open(os.path.join(d, "config.yml"), "w") as f:
-        f.write(
-            env.get_template("config.yml.in").render(
-                build_workflows=build_workflows,
-                unittest_workflows=unittest_workflows,
-                cmake_workflows=cmake_workflows,
-                ios_workflows=ios_workflows,
-                android_workflows=android_workflows,
-            )
-        )

.circleci/smoke_test/docker/Dockerfile

-# this Dockerfile is for torchvision smoke test, it will be created periodically via CI system
-# if you need to do it locally, follow below steps once you have Docker installed
-# assuming you're within the directory where this Dockerfile located
-#  $ docker build . -t torchvision/smoketest
-
-# if you want to push to aws ecr, make sure you have the rights to write to ECR, then run
-# $ eval $(aws ecr get-login --region us-east-1 --no-include-email)
-# $ export MYTAG=localbuild  ## you can choose whatever tag you like
-# $ docker tag torchvision/smoketest 308535385114.dkr.ecr.us-east-1.amazonaws.com/torchvision/smoke_test:${MYTAG}
-# $ docker push  308535385114.dkr.ecr.us-east-1.amazonaws.com/torchvision/smoke_test:${MYTAG}
-
-FROM ubuntu:latest
-
-RUN apt-get -qq update && apt-get -qq -y install curl bzip2 libsox-fmt-all \
-    && curl -sSL https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -o /tmp/miniconda.sh \
-    && bash /tmp/miniconda.sh -bfp /usr/local \
-    && rm -rf /tmp/miniconda.sh \
-    && conda install -y python=3 \
-    && conda update conda \
-    && apt-get -qq -y remove curl bzip2 \
-    && apt-get -qq -y autoremove \
-    && apt-get autoclean \
-    && rm -rf /var/lib/apt/lists/* /var/log/dpkg.log \
-    && conda clean --all --yes
-
-ENV PATH /opt/conda/bin:$PATH
-
-RUN conda create -y --name python3.7 python=3.7
-RUN conda create -y --name python3.8 python=3.8
-RUN conda create -y --name python3.9 python=3.9
-RUN conda create -y --name python3.10 python=3.10
-SHELL [ "/bin/bash", "-c" ]
-RUN echo "source /usr/local/etc/profile.d/conda.sh" >> ~/.bashrc
-CMD [ "/bin/bash"]

.circleci/unittest/android/scripts/binary_android_build.sh

-#!/bin/bash
-set -ex -o pipefail
-
-echo "DIR: $(pwd)"
-echo "ANDROID_HOME=${ANDROID_HOME}"
-echo "ANDROID_NDK_HOME=${ANDROID_NDK_HOME}"
-echo "JAVA_HOME=${JAVA_HOME}"
-
-WORKSPACE=/home/circleci/workspace
-VISION_ANDROID=/home/circleci/project/android
-
-. /home/circleci/project/.circleci/unittest/android/scripts/install_gradle.sh
-
-GRADLE_LOCAL_PROPERTIES=${VISION_ANDROID}/local.properties
-rm -f $GRADLE_LOCAL_PROPERTIES
-
-echo "sdk.dir=${ANDROID_HOME}" >> $GRADLE_LOCAL_PROPERTIES
-echo "ndk.dir=${ANDROID_NDK_HOME}" >> $GRADLE_LOCAL_PROPERTIES
-
-echo "GRADLE_PATH $GRADLE_PATH"
-echo "GRADLE_HOME $GRADLE_HOME"
-
-${GRADLE_PATH} --scan --stacktrace --debug --no-daemon -p ${VISION_ANDROID} assemble || true
-
-mkdir -p ~/workspace/artifacts
-find . -type f -name *aar -print | xargs tar cfvz ~/workspace/artifacts/artifacts-aars.tgz
-find . -type f -name *apk -print | xargs tar cfvz ~/workspace/artifacts/artifacts-apks.tgz

.circleci/unittest/android/scripts/binary_android_upload.sh

-#!/bin/bash
-set -ex -o pipefail
-
-echo "DIR: $(pwd)"
-echo "ANDROID_HOME=${ANDROID_HOME}"
-echo "ANDROID_NDK_HOME=${ANDROID_NDK_HOME}"
-echo "JAVA_HOME=${JAVA_HOME}"
-
-WORKSPACE=/home/circleci/workspace
-VISION_ANDROID=/home/circleci/project/android
-
-. /home/circleci/project/.circleci/unittest/android/scripts/install_gradle.sh
-
-GRADLE_LOCAL_PROPERTIES=${VISION_ANDROID}/local.properties
-rm -f $GRADLE_LOCAL_PROPERTIES
-GRADLE_PROPERTIES=/home/circleci/project/android/gradle.properties
-
-echo "sdk.dir=${ANDROID_HOME}" >> $GRADLE_LOCAL_PROPERTIES
-echo "ndk.dir=${ANDROID_NDK_HOME}" >> $GRADLE_LOCAL_PROPERTIES
-
-echo "SONATYPE_NEXUS_USERNAME=${SONATYPE_NEXUS_USERNAME}" >> $GRADLE_PROPERTIES
-echo "mavenCentralRepositoryUsername=${SONATYPE_NEXUS_USERNAME}" >> $GRADLE_PROPERTIES
-echo "SONATYPE_NEXUS_PASSWORD=${SONATYPE_NEXUS_PASSWORD}" >> $GRADLE_PROPERTIES
-echo "mavenCentralRepositoryPassword=${SONATYPE_NEXUS_PASSWORD}" >> $GRADLE_PROPERTIES
-
-echo "signing.keyId=${ANDROID_SIGN_KEY}" >> $GRADLE_PROPERTIES
-echo "signing.password=${ANDROID_SIGN_PASS}" >> $GRADLE_PROPERTIES
-
-cat /home/circleci/project/android/gradle.properties | grep VERSION
-
-${GRADLE_PATH} --scan --stacktrace --debug --no-daemon -p ${VISION_ANDROID} ops:uploadArchives
-
-mkdir -p ~/workspace/artifacts
-find . -type f -name *aar -print | xargs tar cfvz ~/workspace/artifacts/artifacts-aars.tgz

.circleci/unittest/android/scripts/install_gradle.sh

-#!/bin/bash
-set -ex
-
-_https_amazon_aws=https://ossci-android.s3.amazonaws.com
-GRADLE_VERSION=6.8.3
-
-_gradle_home=/opt/gradle
-sudo rm -rf $gradle_home
-sudo mkdir -p $_gradle_home
-
-curl --silent --output /tmp/gradle.zip --retry 3 $_https_amazon_aws/gradle-${GRADLE_VERSION}-bin.zip
-
-sudo unzip -q /tmp/gradle.zip -d $_gradle_home
-rm /tmp/gradle.zip
-
-sudo chmod -R 777 $_gradle_home
-
-export GRADLE_HOME=$_gradle_home/gradle-$GRADLE_VERSION
-export GRADLE_PATH=${GRADLE_HOME}/bin/gradle

.circleci/unittest/ios/scripts/binary_ios_build.sh

-#!/bin/bash
-set -ex -o pipefail
-
-echo ""
-echo "DIR: $(pwd)"
-WORKSPACE=/Users/distiller/workspace
-PROJ_ROOT_IOS=/Users/distiller/project/ios
-PYTORCH_IOS_NIGHTLY_NAME=libtorch_ios_nightly_build.zip
-export TCLLIBPATH="/usr/local/lib"
-
-# install conda
-curl --retry 3 -o ~/conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
-chmod +x ~/conda.sh
-/bin/bash ~/conda.sh -b -p ~/anaconda
-export PATH="~/anaconda/bin:${PATH}"
-source ~/anaconda/bin/activate
-
-# install dependencies
-conda install numpy ninja pyyaml mkl mkl-include setuptools cmake cffi requests typing_extensions wget --yes
-conda install -c conda-forge valgrind --yes
-export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
-
-# sync submodules
-cd ${PROJ_ROOT_IOS}
-git submodule sync
-git submodule update --init --recursive
-
-# download pytorch-iOS nightly build and unzip it
-mkdir -p ${PROJ_ROOT_IOS}/lib
-mkdir -p ${PROJ_ROOT_IOS}/build
-mkdir -p ${PROJ_ROOT_IOS}/pytorch
-TORCH_ROOT="${PROJ_ROOT_IOS}/pytorch"
-
-cd ${TORCH_ROOT}
-wget https://ossci-ios-build.s3.amazonaws.com/${PYTORCH_IOS_NIGHTLY_NAME}
-mkdir -p ./build_ios
-unzip -d ./build_ios ./${PYTORCH_IOS_NIGHTLY_NAME}
-
-LIBTORCH_HEADER_ROOT="${TORCH_ROOT}/build_ios/install/include"
-cd ${PROJ_ROOT_IOS}
-IOS_ARCH=${IOS_ARCH} LIBTORCH_HEADER_ROOT=${LIBTORCH_HEADER_ROOT} ./build_ios.sh
-rm -rf ${TORCH_ROOT}
-
-# store the binary
-DEST_DIR=${WORKSPACE}/ios/${IOS_ARCH}
-mkdir -p ${DEST_DIR}
-cp ${PROJ_ROOT_IOS}/lib/*.a ${DEST_DIR}

.circleci/unittest/ios/scripts/binary_ios_upload.sh

-#!/bin/bash
-set -ex -o pipefail
-
-echo ""
-echo "DIR: $(pwd)"
-
-WORKSPACE=/Users/distiller/workspace
-PROJ_ROOT=/Users/distiller/project
-ARTIFACTS_DIR=${WORKSPACE}/ios
-ls ${ARTIFACTS_DIR}
-ZIP_DIR=${WORKSPACE}/zip
-mkdir -p ${ZIP_DIR}/install/lib
-
-# build a FAT bianry
-cd ${ZIP_DIR}/install/lib
-libs=("${ARTIFACTS_DIR}/x86_64/libtorchvision_ops.a" "${ARTIFACTS_DIR}/arm64/libtorchvision_ops.a")
-lipo -create "${libs[@]}" -o ${ZIP_DIR}/install/lib/libtorchvision_ops.a
-lipo -i ${ZIP_DIR}/install/lib/*.a
-
-# copy the license
-cp ${PROJ_ROOT}/LICENSE ${ZIP_DIR}/
-# zip the library
-ZIPFILE=libtorchvision_ops_ios_nightly_build.zip
-cd ${ZIP_DIR}
-#for testing
-touch version.txt
-echo $(date +%s) > version.txt
-zip -r ${ZIPFILE} install version.txt LICENSE
-
-# upload to aws
-# Install conda then 'conda install' awscli
-curl --retry 3 -o ~/conda.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
-chmod +x ~/conda.sh
-/bin/bash ~/conda.sh -b -p ~/anaconda
-export PATH="~/anaconda/bin:${PATH}"
-source ~/anaconda/bin/activate
-conda install -c conda-forge awscli --yes
-set +x
-export AWS_ACCESS_KEY_ID=${AWS_S3_ACCESS_KEY_FOR_PYTORCH_BINARY_UPLOAD}
-export AWS_SECRET_ACCESS_KEY=${AWS_S3_ACCESS_SECRET_FOR_PYTORCH_BINARY_UPLOAD}
-set -x
-aws s3 cp ${ZIPFILE} s3://ossci-ios-build/ --acl public-read

.circleci/unittest/linux/scripts/environment.yml

-channels:
-  - pytorch
-  - defaults
-dependencies:
-  - pytest
-  - pytest-cov
-  - pytest-mock
-  - pip
-  - libpng
-  - jpeg
-  - ca-certificates
-  - h5py
-  - pip:
-    - future
-    - scipy
-    - av

.circleci/unittest/linux/scripts/install.sh

-#!/usr/bin/env bash
-
-unset PYTORCH_VERSION
-# For unittest, nightly PyTorch is used as the following section,
-# so no need to set PYTORCH_VERSION.
-# In fact, keeping PYTORCH_VERSION forces us to hardcode PyTorch version in config.
-
-set -e
-
-eval "$(./conda/bin/conda shell.bash hook)"
-conda activate ./env
-
-if [ "${CU_VERSION:-}" == cpu ] ; then
-    cudatoolkit="cpuonly"
-    version="cpu"
-else
-    if [[ ${#CU_VERSION} -eq 4 ]]; then
-        CUDA_VERSION="${CU_VERSION:2:1}.${CU_VERSION:3:1}"
-    elif [[ ${#CU_VERSION} -eq 5 ]]; then
-        CUDA_VERSION="${CU_VERSION:2:2}.${CU_VERSION:4:1}"
-    fi
-    echo "Using CUDA $CUDA_VERSION as determined by CU_VERSION: ${CU_VERSION} "
-    version="$(python -c "print('.'.join(\"${CUDA_VERSION}\".split('.')[:2]))")"
-    cudatoolkit="pytorch-cuda=${version}"
-fi
-
-case "$(uname -s)" in
-    Darwin*) os=MacOSX;;
-    *) os=Linux
-esac
-
-printf "Installing PyTorch with %s\n" "${cudatoolkit}"
-if [ "${os}" == "MacOSX" ]; then
-    conda install -y -c "pytorch-${UPLOAD_CHANNEL}" "pytorch-${UPLOAD_CHANNEL}"::pytorch "${cudatoolkit}"
-else
-    conda install -y -c "pytorch-${UPLOAD_CHANNEL}" -c nvidia "pytorch-${UPLOAD_CHANNEL}"::pytorch[build="*${version}*"] "${cudatoolkit}"
-fi
-
-printf "* Installing torchvision\n"
-python setup.py develop

.circleci/unittest/linux/scripts/post_process.sh

-#!/usr/bin/env bash
-
-set -e
-
-eval "$(./conda/bin/conda shell.bash hook)"
-conda activate ./env

.circleci/unittest/linux/scripts/run_test.sh

-#!/usr/bin/env bash
-
-set -e
-
-eval "$(./conda/bin/conda shell.bash hook)"
-conda activate ./env
-
-python -m torch.utils.collect_env
-pytest --junitxml=test-results/junit.xml -v --durations 20

.circleci/unittest/linux/scripts/setup_env.sh

-#!/usr/bin/env bash
-
-# This script is for setting up environment in which unit test is ran.
-# To speed up the CI time, the resulting environment is cached.
-#
-# Do not install PyTorch and torchvision here, otherwise they also get cached.
-
-set -e
-
-this_dir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
-# Avoid error: "fatal: unsafe repository"
-git config --global --add safe.directory '*'
-root_dir="$(git rev-parse --show-toplevel)"
-conda_dir="${root_dir}/conda"
-env_dir="${root_dir}/env"
-
-cd "${root_dir}"
-
-case "$(uname -s)" in
-    Darwin*) os=MacOSX;;
-    *) os=Linux
-esac
-
-# 1. Install conda at ./conda
-if [ ! -d "${conda_dir}" ]; then
-    printf "* Installing conda\n"
-    wget -O miniconda.sh "http://repo.continuum.io/miniconda/Miniconda3-latest-${os}-x86_64.sh"
-    bash ./miniconda.sh -b -f -p "${conda_dir}"
-fi
-eval "$(${conda_dir}/bin/conda shell.bash hook)"
-
-# 2. Create test environment at ./env
-if [ ! -d "${env_dir}" ]; then
-    printf "* Creating a test environment\n"
-    conda create --prefix "${env_dir}" -y python="$PYTHON_VERSION"
-fi
-conda activate "${env_dir}"
-
-# 3. Install Conda dependencies
-printf "* Installing dependencies (except PyTorch)\n"
-FFMPEG_PIN="=4.2"
-if [[ "${PYTHON_VERSION}" = "3.9" ]]; then
-    FFMPEG_PIN=">=4.2"
-fi
-
-conda install -y -c pytorch "ffmpeg${FFMPEG_PIN}"
-conda env update --file "${this_dir}/environment.yml" --prune

.circleci/unittest/windows/scripts/environment.yml

-channels:
-  - pytorch
-  - defaults
-dependencies:
-  - pytest
-  - pytest-cov
-  - pytest-mock
-  - pip
-  - libpng
-  - jpeg
-  - ca-certificates
-  - hdf5
-  - setuptools
-  - pip:
-    - future
-    - scipy
-    - av != 9.1.1
-    - dataclasses
-    - h5py

.circleci/unittest/windows/scripts/install.sh

-#!/usr/bin/env bash
-
-unset PYTORCH_VERSION
-# For unittest, nightly PyTorch is used as the following section,
-# so no need to set PYTORCH_VERSION.
-# In fact, keeping PYTORCH_VERSION forces us to hardcode PyTorch version in config.
-
-set -ex
-
-this_dir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
-
-eval "$(./conda/Scripts/conda.exe 'shell.bash' 'hook')"
-conda activate ./env
-
-# TODO, refactor the below logic to make it easy to understand how to get correct cuda_version.
-if [ "${CU_VERSION:-}" == cpu ] ; then
-    cudatoolkit="cpuonly"
-    version="cpu"
-else
-    if [[ ${#CU_VERSION} -eq 4 ]]; then
-        CUDA_VERSION="${CU_VERSION:2:1}.${CU_VERSION:3:1}"
-    elif [[ ${#CU_VERSION} -eq 5 ]]; then
-        CUDA_VERSION="${CU_VERSION:2:2}.${CU_VERSION:4:1}"
-    fi
-
-    cuda_toolkit_pckg="cudatoolkit"
-    if [[ $CUDA_VERSION == 11.6 || $CUDA_VERSION == 11.7 ]]; then
-        cuda_toolkit_pckg="pytorch-cuda"
-    fi
-
-    echo "Using CUDA $CUDA_VERSION as determined by CU_VERSION"
-    version="$(python -c "print('.'.join(\"${CUDA_VERSION}\".split('.')[:2]))")"
-    cudatoolkit="${cuda_toolkit_pckg}=${version}"
-fi
-
-printf "Installing PyTorch with %s\n" "${cudatoolkit}"
-conda install -y -c "pytorch-${UPLOAD_CHANNEL}" -c nvidia "pytorch-${UPLOAD_CHANNEL}"::pytorch[build="*${version}*"] "${cudatoolkit}"
-
-torch_cuda=$(python -c "import torch; print(torch.cuda.is_available())")
-echo torch.cuda.is_available is $torch_cuda
-
-if [ ! -z "${CUDA_VERSION:-}" ] ; then
-    if [ "$torch_cuda" == "False" ]; then
-        echo "torch with cuda installed but torch.cuda.is_available() is False"
-        exit 1
-    fi
-fi
-
-source "$this_dir/set_cuda_envs.sh"
-
-printf "* Installing torchvision\n"
-"$this_dir/vc_env_helper.bat" python setup.py develop

.circleci/unittest/windows/scripts/install_conda.bat

-start /wait "" "%miniconda_exe%" /S /InstallationType=JustMe /RegisterPython=0 /AddToPath=0 /D=%tmp_conda%

.circleci/unittest/windows/scripts/post_process.sh

-#!/usr/bin/env bash
-
-set -e
-
-eval "$(./conda/Scripts/conda.exe 'shell.bash' 'hook')"
-conda activate ./env