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# LeakyReLU

class torch.nn.LeakyReLU(negative_slope=0.01, inplace=False)

  Applies the element-wise function:

  LeakyReLU(x)=max⁡(0,x)+negative_slope∗min⁡(0,x)\text{LeakyReLU}(x) = \max(0, x) + \text{negative\_slope} * \min(0, x) LeakyReLU(x)=max(0,x)+negative_slope∗min(0,x)

  or

  LeakyReLU(x)={x, if x≥0 negative_slope×x, otherwise \text{LeakyReLU}(x) = \begin{cases} x, & \text{ if } x \geq 0 \\ \text{negative\_slope} \times x, & \text{ otherwise } \end{cases} LeakyReLU(x)={x,negative_slope×x,​ if x≥0 otherwise ​
  Parameters:

    - negative_slope (float) – Controls the angle of the negative slope (which is used for negative input values). Default: 1e-2

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

  Shape:

    - Input: (∗)(*)(∗) where * means, any number of additional dimensions

    - Output: (∗)(*)(∗), same shape as the input

  Examples:

      >>> m = nn.LeakyReLU(0.1)
      >>> input = torch.randn(2)
      >>> output = m(input)

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