[ONNX] Update export for topk and sort #25739
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@pytorchbot rebase this please |
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@pytorchbot retest this please |
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@pytorchbot retest this please |
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@pytorchbot rebase this please |
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@pytorchbot rebase this please |
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@houseroad please review as this op is requested |
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…oof/topk # Conflicts: # torch/onnx/symbolic_opset11.py
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@pytorchbot retest this please |
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@pytorchbot rebase this please |
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yf225
added
the
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cc @houseroad for review |
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@pytorchbot rebase this please |
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@neginraoof update the expect files please |
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@houseroad done, thanks |
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| start = g.op("Constant", value_t=torch.tensor(dim, dtype=torch.int64)) | ||
| end = g.op("Constant", value_t=torch.tensor(dim + 1, dtype=torch.int64)) | ||
| slice_ = _slice_helper(g, shape_, axes=axis, starts=start, ends=end, steps=None, dynamic_slice=True) | ||
| if _export_onnx_opset_version <= 10: |
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Ideally my preference is to not capture the entire implementation in a helper function like this, especially when the implementation differs between two opsets like in this case. We should write the implementation in the opset's respective symbolic_opset*. We can capture the common parts of the implementation in a helper function.
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Yeah, makes sense
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@houseroad merged this pull request in d93fc64. |
Summary: updated export for topk and sort as part of opset11 Pull Request resolved: pytorch#25739 Reviewed By: hl475 Differential Revision: D17467131 Pulled By: houseroad fbshipit-source-id: 653be138455728ec8e9bb81ae63dd7ce0c4d0793
Summary: updated export for topk and sort as part of opset11 Pull Request resolved: pytorch#25739 Reviewed By: hl475 Differential Revision: D17467131 Pulled By: houseroad fbshipit-source-id: 653be138455728ec8e9bb81ae63dd7ce0c4d0793
updated export for topk and sort as part of opset11