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3e6b8d159a
Add support for PyTorch `resize_` operation. The PyTorch API method is documented here: https://pytorch.org/docs/stable/generated/torch.Tensor.resize_.html Implementation notes: There are some implementation details that might deviate from expectations: - As the Onnxruntime::tensor does not support resize operation, this functionality is supported on the TensorImpl by swapping out the backing tensor if the size changes. - In the ORT model the shape of the TensorImpl is defined by the backing onnxruntime::tensor, so it is not supported to have a TensorImpl with a different shape / size than the backing onnxruntime::tensor. This means when resizing to a smaller TensorImpl, other implementations might keep the same backing storage, ORT will re-allocate a new onnxruntime::tensor and copy over as many of the existing elements that fit. Functionally, you will end up with same output, but the underlying buffer will be re-allocated. A future change could be to allow ORTTensorImpl to have a different size / shape than the onnxrutime::tensor backing it, and then we could improve this behavior. The canonical CPU / CUDA implementations in PyTorch repository: CPU: aten/src/ATen/native/Resize.cpp CUDA: aten/src/ATen/native/cuda/Resize.cpp |
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