TensorDictBase.lazy_stack#
- classmethod TensorDictBase.lazy_stack(input, dim: int = 0, *, out=None, **kwargs)#
Creates a lazy stack of tensordicts.
A lazy stack keeps the tensordicts as they are and stacks their values only when you read them. The tensordicts can have different keys and different feature shapes. See Stacking and variable-size data, and
tensordict.lazy_stack()for the arguments.Examples
>>> import torch >>> from tensordict import TensorDict >>> a = TensorDict(x=torch.zeros(3), batch_size=[3]) >>> b = TensorDict(y=torch.ones(3), batch_size=[3]) >>> stack = TensorDict.lazy_stack([a, b]) >>> type(stack).__name__, stack.batch_size ('LazyStackedTensorDict', torch.Size([2, 3]))
Every tensordict class and every tensorclass has this method. For the other methods, see Methods by task.