ELU
class torch.nn.ELU(alpha=1.0, inplace=False)
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:
  \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 \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.

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