[JIT][ONNX] Expose dim() on type and use it in ONNX symbolics#15933
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[JIT][ONNX] Expose dim() on type and use it in ONNX symbolics#15933jamesr66a wants to merge 2 commits into
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houseroad
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Looks good. We should record the recommended way to get the dim of the tensors somewhere (probably at the beginning of the symbolic.py)
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Summary: While integrating fork/join into production translation, we found that trying to export `transpose()` where the input is of `TensorType` (rather than `CompleteTensorType`) failed. This is not ideal, since `TensorType` still contains the number of dimensions of the tensor, and that's all the `transpose` symbolic needs. This PR introduces a pybind binding for `dim()` on `TensorType` (and `CompleteTensorType` by inheritance). We now use this in places where it logically makes sense in the symbolics: those symbolics which only require knowledge of the number of dimensions rather than concrete sizes. Pull Request resolved: pytorch#15933 Differential Revision: D13639657 Pulled By: jamesr66a fbshipit-source-id: 6e50e407e93060085fd00a686a928764d0ec888d
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While integrating fork/join into production translation, we found that trying to export
transpose()where the input is ofTensorType(rather thanCompleteTensorType) failed. This is not ideal, sinceTensorTypestill contains the number of dimensions of the tensor, and that's all thetransposesymbolic needs.This PR introduces a pybind binding for
dim()onTensorType(andCompleteTensorTypeby inheritance). We now use this in places where it logically makes sense in the symbolics: those symbolics which only require knowledge of the number of dimensions rather than concrete sizes.