reference/generated/tensordict.TensorDictBase.cat_tensors

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TensorDictBase.cat_tensors

TensorDictBase.cat_tensors(*keys: NestedKey, out_key: NestedKey, dim: int = 0, keep_entries: bool = False) → Self

Concatenates entries into a new entry and possibly remove the original values.

Parameters:

keys (sequence of NestedKey) – entries to concatenate.

Keyword Arguments:

• out_key (NestedKey) – new key name for the concatenated inputs.

• keep_entries (bool, optional) – if False, entries in keys will be deleted. Defaults to False. Entries are deleted only after the result has been written. If concatenation fails, or if the result cannot be written, every input entry is kept with its original value.

• dim (int, optional) – the dimension along which the concatenation must occur. Defaults to 0.

Returns: self

Examples

>>> import torch
>>> from tensordict import TensorDict
>>> td = TensorDict(a=torch.zeros(1), b=torch.ones(1))
>>> _ = td.cat_tensors("a", "b", out_key="c")
>>> assert "a" not in td
>>> assert (td["c"] == torch.tensor([0, 1])).all()

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