mirror of https://github.com/llvm/torch-mlir
88d4c475d3
NonValueSemantic Ops like Add_, div_, etc. expect result DType to be the same as the first input. However, current implementation would result in wrong result type for case like: ```python a = torch.randn(3, 3).half() # float16 b = torch.randn(3, 3) # float32 a += b # i.e. torch.ops.aten.add_(a, b) ``` torch expects `a` to be float16, but dtype refinement would infer float32 type, since it's replaced by `aten.add`. |
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| .. | ||
| test | ||
| torch_mlir | ||
| torch_mlir_e2e_test | ||
| CMakeLists.txt | ||
| TorchMLIRModule.cpp | ||