pytorch

63f1b780 - Support exporting aten::copy_ and aten::index_put to ONNX opset 11 (#26941)

Support exporting aten::copy_ and aten::index_put to ONNX opset 11 (#26941) Summary: - [x] Add more comments and refactor the logic of `ReshapeToAdvancedIndexingFormat` - [x] Add more description here. Cases that are/aren't supported, and how they are supported. - [x] Need to merge this PR https://github.com/pytorch/pytorch/issues/27186 to enable testing inplace operators. We are now supporting exporting aten::copy_ and aten::index_put to ONNX. Here's a breakdown of the different cases in PyTorch code. ``` # Case 1: Scalar Indices x[0, 1, 2] = data # Case 2: Slice Indices x[1:3, :, ::2] = data # Case 3: Ellipsis Indices x[..., 0] = data # Case 4: Tensor Indices ind1 = torch.tensor([0, 2]) ind2 = torch.tensor([1, 1]) x[ind1, ind2] = data # Case 5: Mixing all the above cases ind1 = torch.tensor([0, 2]) ind2 = torch.tensor([1, 1]) x[1:3, ind1, ind2, ..., 3] = data ``` Limitations: Tensor indices must be consecutive, and 1-d tensors. ``` # Supported ind1 = torch.tensor([0, 2]) ind2 = torch.tensor([1, 1]) x[ind1, ind2] = data # Not supported ind1 = torch.tensor([0, 2]) ind2 = torch.tensor([1, 1]) ind3 = torch.tensor([[0], [1]]) x[ind1, :, ind2] = data x[ind3] = data ``` Negative indices are not supported. ``` # Not supported x[-1] = data ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/26941 Differential Revision: D17951030 Pulled By: houseroad fbshipit-source-id: 4357777072f53aa0bc4b297aa1ee53457a7f8dec