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Merge branch 'main' of github.com:pytorch/vision into please_dont_modify_this_branch_unless_you_are_just_merging_with_main__
2 parents c8aa0cf + fab1188 commit 49b2bd4

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‎.github/scripts/setup-env.sh‎

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@@ -45,11 +45,7 @@ echo '::endgroup::'
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if [[ "${OS_TYPE}" == windows && "${GPU_ARCH_TYPE}" == cuda ]]; then
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echo '::group::Install VisualStudio CUDA extensions on Windows'
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if [[ "${VC_YEAR:-}" == "2022" ]]; then
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TARGET_DIR="/c/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/MSBuild/Microsoft/VC/v170/BuildCustomizations"
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else
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TARGET_DIR="/c/Program Files (x86)/Microsoft Visual Studio/2019/BuildTools/MSBuild/Microsoft/VC/v160/BuildCustomizations"
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fi
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TARGET_DIR="/c/Program Files (x86)/Microsoft Visual Studio/2022/BuildTools/MSBuild/Microsoft/VC/v170/BuildCustomizations"
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mkdir -p "${TARGET_DIR}"
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cp -r "${CUDA_HOME}/MSBuildExtensions/"* "${TARGET_DIR}"
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echo '::endgroup::'
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python setup.py develop
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echo '::endgroup::'
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echo '::group::Install torchvision-extra-decoders'
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# This can be done after torchvision was built
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pip install torchvision-extra-decoders
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echo '::endgroup::'
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echo '::group::Collect environment information'
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conda list
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python -m torch.utils.collect_env

‎.github/workflows/build-cmake.yml‎

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gpu-arch-version: "11.8"
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fail-fast: false
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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permissions:
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id-token: write
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contents: read
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with:
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repository: pytorch/vision
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runner: ${{ matrix.runner }}

‎.github/workflows/build-conda-linux.yml‎

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‎.github/workflows/build-conda-m1.yml‎

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‎.github/workflows/build-conda-windows.yml‎

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‎.github/workflows/docs.yml‎

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jobs:
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build:
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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permissions:
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id-token: write
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contents: read
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with:
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repository: pytorch/vision
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upload-artifact: docs
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needs: build
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if: github.repository == 'pytorch/vision' && github.event_name == 'push' &&
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((github.ref_type == 'branch' && github.ref_name == 'main') || github.ref_type == 'tag')
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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permissions:
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id-token: write
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contents: write
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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with:
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repository: pytorch/vision
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download-artifact: docs

‎.github/workflows/lint.yml‎

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jobs:
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python-source-and-configs:
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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permissions:
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id-token: write
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contents: read
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with:
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repository: pytorch/vision
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test-infra-ref: main
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c-source:
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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permissions:
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id-token: write
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contents: read
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with:
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repository: pytorch/vision
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test-infra-ref: main
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python-types:
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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permissions:
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id-token: write
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contents: read
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with:
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test-infra-ref: main

‎.github/workflows/prototype-tests-linux-gpu.yml‎

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gpu-arch-type: cuda
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gpu-arch-version: "11.8"
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fail-fast: false
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uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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permissions:
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id-token: write
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contents: read
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with:
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repository: pytorch/vision
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runner: ${{ matrix.runner }}

‎.github/workflows/tests.yml‎

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gpu-arch-type: cuda
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fail-fast: false
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uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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permissions:
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id-token: write
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contents: read
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uses: pytorch/test-infra/.github/workflows/windows_job.yml@main
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permissions:
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id-token: write
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contents: read
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set -euxo pipefail
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export PYTHON_VERSION=${{ matrix.python-version }}
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export VC_YEAR=2019
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export VC_YEAR=2022
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export VSDEVCMD_ARGS=""
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export GPU_ARCH_TYPE=${{ matrix.gpu-arch-type }}
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export GPU_ARCH_VERSION=${{ matrix.gpu-arch-version }}
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./.github/scripts/unittest.sh
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uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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permissions:
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id-token: write
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contents: read
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echo '::endgroup::'
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unittests-extended:
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uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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permissions:
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id-token: write
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contents: read
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if: contains(github.event.pull_request.labels.*.name, 'run-extended')
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‎docs/source/io.rst‎

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Image Decoding
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--------------
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Torchvision currently supports decoding JPEG, PNG, WEBP and GIF images. JPEG
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decoding can also be done on CUDA GPUs.
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Torchvision currently supports decoding JPEG, PNG, WEBP, GIF, AVIF, and HEIC
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images. JPEG decoding can also be done on CUDA GPUs.
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The main entry point is the :func:`~torchvision.io.decode_image` function, which
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you can use as an alternative to ``PIL.Image.open()``. It will decode images
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:func:`~torchvision.io.decode_image` will automatically detect the image format,
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and call the corresponding decoder. You can also use the lower-level
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format-specific decoders which can be more powerful, e.g. if you want to
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encode/decode JPEGs on CUDA.
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and call the corresponding decoder (except for HEIC and AVIF images, see details
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in :func:`~torchvision.io.decode_avif` and :func:`~torchvision.io.decode_heic`).
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You can also use the lower-level format-specific decoders which can be more
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powerful, e.g. if you want to encode/decode JPEGs on CUDA.
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.. autosummary::
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:toctree: generated/
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decode_image
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decode_jpeg
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encode_png
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decode_gif
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decode_webp
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decode_avif
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decode_heic
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decode_gif
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.. autosummary::
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:toctree: generated/

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