Missing dtype support for OnnxToTorch
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Description
Current support: https://github.com/llvm/torch-mlir/blob/main/lib/Conversion/TorchOnnxToTorch/Utils.cpp#L64
According to [onnx dtype](https://onnx.ai/onnx/intro/concepts.html) and [torch dtype](https://github.com/llvm/torch-mlir/blob/main/include/torch-mlir/Dialect/Torch/Utils/TorchUpstream.h#L88), missing support:
- 4: onnx.TensorProto.UINT16
- 8: onnx.TensorProto.STRING
- 12: onnx.TensorProto.UINT32
- 13: onnx.TensorProto.UINT64
- 17: onnx.TensorProto.FLOAT8E4M3FN
- 18: onnx.TensorProto.FLOAT8E4M3FNUZ
- 19: onnx.TensorProto.FLOAT8E5M2
- 20: onnx.TensorProto.FLOAT8E5M2FNUZ
- 21: onnx.TensorProto.UINT4
- 22: onnx.TensorProto.INT4
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- Read the whole issue, then the project's contributing guide.
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- Open a pull request that references the issue number.
Research direction
Start in lib/Conversion/TorchOnnxToTorch/Utils.cpp at the linked current dtype support and compare it with the ONNX dtype list and Torch types in include/torch-mlir/Dialect/Torch/Utils/TorchUpstream.h. Determine which listed UINT, STRING, FLOAT8, UINT4, and INT4 types have usable Torch representations; done means the supported mappings are handled consistently for every feasible listed dtype.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp
- Domain
- compilers
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100