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fix(datasets): expand torchcodec platform coverage + rewrite pyav fallback for torchvision >0.26 (#3588)
* fix(deps): better versioning control for torchcodec * refactor(video_utils): replace torchvision with pyav * adding Torchcodec version to lerobot-info * chore(benchmarks): delete video benchmark --------- Co-authored-by: Maximellerbach <maxime.ellerbach@huggingface.co>
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@@ -99,7 +99,18 @@ dataset = [
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"pandas>=2.0.0,<3.0.0", # NOTE: Transitive dependency of datasets
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"pyarrow>=21.0.0,<30.0.0", # NOTE: Transitive dependency of datasets
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"lerobot[av-dep]",
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"torchcodec>=0.3.0,<0.12.0; sys_platform != 'win32' and (sys_platform != 'linux' or (platform_machine != 'aarch64' and platform_machine != 'arm64' and platform_machine != 'armv7l')) and (sys_platform != 'darwin' or platform_machine != 'x86_64')", # NOTE: Windows support starts at version 0.7 (needs torch==2.8), ffmpeg>=8 support starts at version 0.8.1 (needs torch==2.9), system-wide ffmpeg support starts at version 0.10 (needs torch==2.10), 0.11 needs torch==2.11, 0.12 needs torch==2.12.
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# NOTE: torchcodec wheel availability matrix (PyPI):
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# - linux x86_64/amd64 + macOS arm64 : wheels since 0.3.0 (the historic supported set).
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# - win32 x86_64 : wheels since 0.7.0 (needs torch>=2.8).
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# - linux aarch64/arm64 : wheels since 0.11.0 (needs torch>=2.11).
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# - macOS x86_64 (Intel) and linux armv7l: no wheels in any released version -> fall through to the PyAV decoder.
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# Each platform gets its own line so the resolver picks the minimum version that has a wheel for it.
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# Other torch/torchcodec pairings (informational): 0.8.1 = ffmpeg>=8 support, 0.10 = system-wide ffmpeg support, 0.12 needs torch==2.12.
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"torchcodec>=0.3.0,<0.12.0; (sys_platform == 'linux' and (platform_machine == 'x86_64' or platform_machine == 'AMD64')) or (sys_platform == 'darwin' and platform_machine == 'arm64')",
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"torchcodec>=0.7.0,<0.12.0; sys_platform == 'win32'",
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"torchcodec>=0.11.0,<0.12.0; sys_platform == 'linux' and (platform_machine == 'aarch64' or platform_machine == 'arm64')",
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"jsonlines>=4.0.0,<5.0.0",
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]
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training = [
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