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# Motivation
This PR is a part of RFC pytorch#114848, and it is a successor PR of pytorch#116249 and pytorch#116019. This PR would depend on oneDNN compilation in pytorch#116249. Some runtime support is needed in pytorch#116019.
Aten operators like `addmm`, `baddmm` is defined in `Blas.cpp` in `aten/src/ATen/native/mkldnn/xpu/`.
Accompanied with these files provide core functionaliy, `BlasImpl.h`, `Utils.h` and other file provide basic utilities for them. For instance, `Utils.h` provide common memory descriptor query utils for `Matmul.h` and these utility function will also be used in other primitive, like `convolution`. `BlasImpl.h` is a header file that provide helper for handling shape info processing in matmul related operators. It would not only help basic GEMM operator like `addmm, baddmm` but also help fusion operators used in `torch.compile` like `linear_pointwise` in pytorch#117824.
In next stage, we would continually complete the oneDNN support through enabling `matmul fusion` and `convolution` related code.
Co-authored-by: xiaolil1 <[email protected]>
Co-authored-by: lei,zhenyuan <[email protected]>
Pull Request resolved: pytorch#117202
Approved by: https://github.com/EikanWang, https://github.com/jgong5, https://github.com/malfet
ghstack dependencies: pytorch#117098, pytorch#117112
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