reference/generated/tensordict.TensorDictBase.rename_

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TensorDictBase.rename

TensorDictBase.rename_(*names, **rename_map)

Renames the batch dimensions of the tensordict in place and returns self.

Pass either the new names, one per batch dimension, or keyword arguments that map old names to new ones. The nested tensordicts get the new names for the batch dimensions they share with the tensordict.

Parameters:

• *names (str or None) – the new names, one per batch dimension, or a single None to clear every name. Exclusive with **rename_map.

• **rename_map (str or None) – new names by old name, as in rename_(old="new"). Exclusive with *names.

Raises:

ValueError – if both names and rename_map are passed, or neither (except on a tensordict with no batch dimension), or if a key of rename_map is not a name of the tensordict.

See also

rename(), which returns a renamed copy.

Examples

>>> from tensordict import TensorDict
>>> td = TensorDict(batch_size=[1, 2, 3, 4], names=list("abcd"))
>>> td.rename_(c="g") is td
True
>>> td.names
['a', 'b', 'g', 'd']
>>> td.rename_(None).names
[None, None, None, None]

Every tensordict class and every tensorclass has this method. For the other methods, see Methods by task.