LeakyReLU# class torch.nn.LeakyReLU(negative_slope=0.01, inplace=False)[source]# Applies the LeakyReLU function element-wise. 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≥0negative_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) extra_repr()[source]# Return the extra representation of the module. Return type str forward(input)[source]# Run forward pass. Return type Tensor
