torch-mlir/lib/CAPI
zjgarvey de28c8540b
[ONNX] add int16 quantization support (#3446)
There is currently no int16 quantization support in torch. This patch
adds a new mlir type to correspond to the missing "torch.qint16" type,
and enables lowering of quantization-related onnx ops using int16 types.

In follow-up patches, custom quantization logic for ops like
aten.matmul/aten.mm/aten.convolution may need to be revisited to allow
support for qint16. The passes in FuseQuantizedOps.cpp may also need
slight modifications.
2024-06-12 10:37:22 +05:30
..
CMakeLists.txt Re-organize project structure to separate PyTorch dependencies from core project. (#2542) 2023-11-02 19:45:55 -07:00
Dialects.cpp Clang format refresh (#2812) 2024-01-29 12:59:33 -05:00
Registration.cpp Revert "python: trim registration and loading of dialects and passes" (#1093) 2022-07-21 09:35:42 -07:00
TorchOps.cpp Rework how global slot initializers work. 2022-08-08 18:12:06 -07:00
TorchTypes.cpp [ONNX] add int16 quantization support (#3446) 2024-06-12 10:37:22 +05:30
Transforms.cpp Fix Base Lazy Backend Type Conversion (#1412) 2022-10-04 15:53:28 -07:00