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ELU

class torch.nn.ELU(alpha=1.0, inplace=False)[source]

Applies the Exponential Linear Unit (ELU) function, element-wise, as described in the paper: Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

ELU is defined as:

ELU(x)={x, if x>0α(exp(x)1), if x0\text{ELU}(x) = \begin{cases} x, & \text{ if } x > 0\\ \alpha * (\exp(x) - 1), & \text{ if } x \leq 0 \end{cases}
Parameters
  • alpha (float) – the α\alpha value for the ELU formulation. Default: 1.0

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

Shape:
  • Input: ()(*), where * means any number of dimensions.

  • Output: ()(*), same shape as the input.

../_images/ELU.png

Examples:

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

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