reference/generated/tensordict.TensorDictBase.addcdiv

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TensorDictBase.addcdiv

TensorDictBase.addcdiv(other1: TensorDictBase | Tensor, other2: TensorDictBase | Tensor, value: float | None = 1) → Self

Returns a new tensordict with value * other1 / other2 added to every leaf.

\[\text{out}_i = \text{input}_i + \text{value} \times \frac{\text{other1}_i}{\text{other2}_i}\]

Parameters:

• other1 (TensorDictBase or Tensor) – the numerator. A tensordict is paired with the tensordict key by key and must have all its keys. A tensor is aligned with the batch dimensions of each leaf and expanded over its feature dimensions.

• other2 (TensorDictBase or Tensor) – the denominator, paired like other1. One of other1 and other2 can be a tensordict and the other a tensor.

• value (Number, optional) – the multiplier for \(\text{other1} / \text{other2}\). Defaults to 1.

Examples

>>> import torch
>>> from tensordict import TensorDict
>>> td = TensorDict(x=torch.ones(2), batch_size=[2])
>>> td.addcdiv(torch.tensor([1.0, 2.0]), torch.tensor([2.0, 2.0]), value=2)["x"]
tensor([2., 3.])

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