GLU# class torch.nn.GLU(dim=-1)[source]# Applies the gated linear unit function. GLU(a,b)=a⊗σ(b){GLU}(a, b)= a \otimes \sigma(b)GLU(a,b)=a⊗σ(b) where aaa is the first half of the input matrices and bbb is the second half. Parameters dim (int) – the dimension on which to split the input. Default: -1 Shape: Input: (∗1,N,∗2)(\ast_1, N, \ast_2)(∗1,N,∗2) where * means, any number of additional dimensions Output: (∗1,M,∗2)(\ast_1, M, \ast_2)(∗1,M,∗2) where M=N/2M=N/2M=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
