torch-mlir/projects/pt1
Aart Bik 78e10ff09b
[torch-mlir][sparse] inline sparse helper methods (#2918)
Even though the reference compiler is not about performance, inlining
the generated sparse helper methods has a rather big positive impact on
performance, leaving a much better first impression. Therefore, we added
this inlining pass (which leaves all other PyTorch modules unaffected,
since they tend to be one big main() method to start with).

testing:

$./tools/e2e_test.sh --config linalg

Summary:
    Passed: 1164
    Expectedly Failed: 8

$ python -m e2e_testing.main --config=torchdynamo

Summary:
    Passed: 976
    Expectedly Failed: 162
2024-02-16 20:56:42 -08:00
..
e2e_testing [onnx] Fix `onnx.sigmoid` for integer inputs/outputs (#2914) 2024-02-16 13:35:25 -08:00
examples Rename torch_mlir.compile APIs and introduce FX based analogs (#2842) 2024-02-06 19:07:59 -08:00
python [torch-mlir][sparse] inline sparse helper methods (#2918) 2024-02-16 20:56:42 -08:00
test Rename torch_mlir.compile APIs and introduce FX based analogs (#2842) 2024-02-06 19:07:59 -08:00
tools Re-organize project structure to separate PyTorch dependencies from core project. (#2542) 2023-11-02 19:45:55 -07:00
CMakeLists.txt Re-organize project structure to separate PyTorch dependencies from core project. (#2542) 2023-11-02 19:45:55 -07:00