Method rename

torch/_tensor.py:1299–1339

Renames dimension names of :attr:`self`. There are two main usages: ``self.rename(**rename_map)`` returns a view on tensor that has dims renamed as specified in the mapping :attr:`rename_map`. ``self.rename(*names)`` returns a view on tensor, renaming all d

(self, *names, **rename_map)

        return update_names(self, names, rename_map, inplace=True)

    def rename(self, *names, **rename_map):
        """Renames dimension names of :attr:`self`.

        There are two main usages:

        ``self.rename(**rename_map)`` returns a view on tensor that has dims
        renamed as specified in the mapping :attr:`rename_map`.

        ``self.rename(*names)`` returns a view on tensor, renaming all
        dimensions positionally using :attr:`names`.
        Use ``self.rename(None)`` to drop names on a tensor.

        One cannot specify both positional args :attr:`names` and keyword args
        :attr:`rename_map`.

        Examples::

            >>> imgs = torch.rand(2, 3, 5, 7, names=('N', 'C', 'H', 'W'))
            >>> renamed_imgs = imgs.rename(N='batch', C='channels')
            >>> renamed_imgs.names
            ('batch', 'channels', 'H', 'W')

            >>> renamed_imgs = imgs.rename(None)
            >>> renamed_imgs.names
            (None, None, None, None)

            >>> renamed_imgs = imgs.rename('batch', 'channel', 'height', 'width')
            >>> renamed_imgs.names
            ('batch', 'channel', 'height', 'width')

        .. warning::
            The named tensor API is experimental and subject to change.

        """
        if has_torch_function_unary(self):
            return handle_torch_function(
                Tensor.rename, (self,), self, *names, **rename_map
            )

        # See Note [rename_ / rename API]
        return update_names(self, names, rename_map, inplace=False)

    def to_sparse_coo(self):
        """Convert a tensor to :ref:`coordinate format <sparse-coo-docs>`.