linear.py 文件源码

def forward(self, input1, input2, weight, bias=None):
        self.save_for_backward(input1, input2, weight, bias)

        output = input1.new(input1.size(0), weight.size(0))

        buff = input1.new()

        # compute output scores:
        for k, w in enumerate(weight):
            torch.mm(input1, w, out=buff)
            buff.mul_(input2)
            torch.sum(buff, 1, out=output.narrow(1, k, 1))

        if bias is not None:
            output.add_(bias.expand_as(output))

        return output