reference/generated/tensordict.TensorDictBase.copy_

Run in Google Colab

Colab

Download Notebook

Notebook

View on GitHub

GitHub

TensorDictBase.copy

TensorDictBase.copy_(tensordict: T, non_blocking: bool = False) → Self

Copies the entries of tensordict into the existing entries, and returns self.

The same as update_(), under the name of torch.Tensor.copy_(): the existing tensors keep their storage, and every key of tensordict must exist in the tensordict.

Parameters:

• tensordict (TensorDictBase or dict) – the entries to copy.

• non_blocking (bool, optional) – if True, copies between devices can run asynchronously with respect to the host. Defaults to False.

Raises:

• KeyError – if a key of tensordict is missing from the tensordict.

• RuntimeError – if a value does not fit the shape of its entry.

Examples

>>> import torch
>>> from tensordict import TensorDict
>>> x = torch.zeros(3)
>>> td = TensorDict(x=x, batch_size=[3])
>>> _ = td.copy_(TensorDict(x=torch.ones(3), batch_size=[3]))
>>> x
tensor([1., 1., 1.])

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