reference/generated/tensordict.nn.biased_softplus

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biased_softplus

class tensordict.nn.biased_softplus(bias: float, min_val: float = 0.01)

Bases: Module

A biased softplus module.

The bias indicates the value that is to be returned when a zero-tensor is passed through the transform. The module computes softplus(x + inv_softplus(bias - min_val)) + min_val.

Parameters:

• bias (float) – the output for a zero input.

• min_val (float, optional) – minimum value of the output. Defaults to 0.01.

Examples

>>> import torch
>>> from tensordict.nn import biased_softplus
>>> f = biased_softplus(1.0)
>>> f(torch.zeros(2))
tensor([1., 1.])

forward(x: Tensor) → Tensor

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.