pytorch / 2 / generated / torch.nn.celu.html

CELU

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

Applies the element-wise function:

CELU ( x ) = max ( 0 , x ) + min ( 0 , α ( exp ( x / α ) 1 ) ) \text{CELU}(x) = \max(0,x) + \min(0, \alpha * (\exp(x/\alpha) - 1))

More details can be found in the paper Continuously Differentiable Exponential Linear Units .

Parameters
  • alpha (float) – the α \alpha value for the CELU 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/CELU.png

Examples:

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

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