ELU

class torch.nn.modules.activation.ELU(alpha=1.0, inplace=False)

Applies the Exponential Linear Unit (ELU) function, element-wise.

Method described in the paper: Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

ELU is defined as:

$$\text{ELU}(x)=\{\begin{array}{ll}x,& \text{ if }x>0\\ \alpha \ast (\exp (x)-1),& \text{ if }x\le 0\end{array}$$

Parameters

• alpha (float) – the $\alpha$ value for the ELU formulation. Default: 1.0

• inplace (bool) – can optionally do the operation in-place. Default: False

Shape:

• Input: $(\ast )$, where $\ast$ means any number of dimensions.

• Output: $(\ast )$, same shape as the input.

Examples:

>>> m = nn.ELU()
>>> input = torch.randn(2)
>>> output = m(input)

extra_repr()

Return the extra representation of the module.

Return type

str

forward(input)

Runs the forward pass.

Return type

Tensor