| """This file provides a location for operators that help exporting models via onnx. | |
| E.g. `shape_as_tensor` and `reshape_from_tensor_shape` | |
| are to make all dynamic sizes operations traceable. | |
| NOTE: at one point these functions were implemented differently. | |
| Since then we have implemented these directly in ATen, so this | |
| file is kept purely for backward-compatibility. | |
| """ | |
| from __future__ import annotations | |
| __all__: list[str] = [] | |
| import torch | |
| """Get the shape of a tensor as a tensor. | |
| Args: | |
| x (Tensor): The input tensor. | |
| Returns: | |
| Tensor: A tensor of shape [len(x.shape)] containing the size of each dimension of x. | |
| Example: | |
| >>> x = torch.randn(2, 3) | |
| >>> shape_as_tensor(x) | |
| tensor([2, 3]) | |
| """ | |
| shape_as_tensor = torch._shape_as_tensor | |
| """Reshape a tensor to the given shape. | |
| This function is used to make dynamic size operations traceable when exporting models via ONNX. | |
| This function is kept for backward-compatibility. It is implemented directly in ATen. | |
| Parameters: | |
| x (Tensor): the tensor to be reshaped. | |
| shape (Tensor): the target shape. | |
| Returns: | |
| Tensor: the reshaped tensor. | |
| """ | |
| reshape_from_tensor_shape = torch._reshape_from_tensor | |