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It would be nice to mention load_inline
(pytorch/pytorch#7059) in the tutorial
https://pytorch.org/tutorials/advanced/cpp_extension.html
A practical use-case for an example may be a bilateral filter from https://github.com/NVIDIA/FastPhotoStyle/blob/master/smooth_filter.py (currentlly uses CuPY and pynvrtc).
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[-][docs] Mention inline CUDA extensions in docs[/-][+][docs] Mention inline CUDA extensions in tutorial[/+]vadimkantorov commentedon Nov 4, 2021
At least load_inline now appears in docs
vadimkantorov commentedon Aug 17, 2022
Although, caching of compiled binaries was recently still broken: pytorch/pytorch#68066
quantized::linear_dynamic
on CUDA/eager, and other quantized and low-level int8 operators (matmul, gemm etc) on CUDA + integrate LLM.int8 + integrate ZeroQuant? pytorch/pytorch#69364