mirror of https://github.com/llvm/torch-mlir
0314188dbe
This patch adds basic support for lowering graphs with per-channel quantization. Per-channel quantized ops have to be excluded from `FuseQuantizedOps` for now but can be used in QDQ quantized form. Using this patch, we're able to import and execute (on the linalg backend) graphs with per-channel quantization applied using the "new" PyTorch 2.0 Export Quantization. |
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| .. | ||
| CMakeLists.txt | ||
| DataMovement.cpp | ||
| IndirectDataMovement.cpp | ||
| Linear.cpp | ||
| Pooling.cpp | ||
| PopulatePatterns.h | ||
| Random.cpp | ||
| Reduction.cpp | ||
| TensorConstructors.cpp | ||
| TensorScalarInterop.cpp | ||
| TorchToLinalg.cpp | ||
| Uncategorized.cpp | ||
| Utils.cpp | ||