GLU

class torch.nn.modules.activation.GLU(dim=-1) [source]

Applies the gated linear unit function.

${GLU}(a, b)= a \otimes \sigma(b)$ where $a$ is the first half of the input matrices and $b$ is the second half.

Parameters

dim (int) – the dimension on which to split the input. Default: -1

Shape:

• Input: $(\ast_1, N, \ast_2)$ where * means, any number of additional dimensions
• Output: $(\ast_1, M, \ast_2)$ where $M=N/2$

Examples:

>>> m = nn.GLU()
>>> input = torch.randn(4, 2)
>>> output = m(input)

extra_repr() [source]

Return the extra representation of the module.

Return type

str

forward(input) [source]

Runs the forward pass.

Return type

Tensor