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Resolved universally, the lock settled on ml-dtypes 0.4.1, and onnx 1.19.0's reference implementation uses ml_dtypes.float4_e2m1fn (added in 0.5), so the fixture generator failed at import for mlicpp, snac, dcvc and glc. The .in now asks for ml-dtypes>=0.5.0; on Python 3.11 that is 0.5.4 with numpy 1.26.4. Co-Authored-By: Claude Opus 5.5 <[email protected]>
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14 lines
746 B
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# The Python stack of wai-neural-e2e.yml (wai_validate_synthetic.py), as wanted. CI installs
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# the hashed closure, requirements-neural-e2e.txt, generated from this file by its header's
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# command. torch and torchvision come from the CPU wheel index, so their compiled ops
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# match (compressai imports torchvision) and Linux does not resolve the CUDA builds.
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# torch and torchvision: the CPU builds, pinned by torch-cpu-overrides.txt.
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compressai
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# `onnx` (the exporter) is separate from `onnxruntime` (the decoder).
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onnx
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onnxruntime
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numpy
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pillow>=13.0.0
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# onnx's reference implementation uses ml_dtypes.float4_e2m1fn, which 0.5 added; without
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# this floor the universal resolution settles on 0.4.1 and the exporter fails at import.
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ml-dtypes>=0.5.0
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