activation.py 文件源码

def forward(self, x):
        """
        Conditional Image Generation with PixelCNN Decoders
        http://arxiv.org/abs/1606.05328

        1D gated activation unit that models the forget gates and
        real gates of an activation unit using convolutions.

        :param x: (batch size, # channels, height)
        :return: tanh(conv(Wr, x)) * sigmoid(conv(Wf, x))
        """

        real_gate_weights, forget_gate_weights = self.weights.split(self.kernel_size, dim=2)
        real_gate_weights = real_gate_weights.contiguous()
        forget_gate_weights = forget_gate_weights.contiguous()

        real_gate = F.tanh(F.conv1d(input=x, weight=real_gate_weights, stride=1))
        forget_gate = F.sigmoid(F.conv1d(input=x, weight=forget_gate_weights, stride=1))
        return real_gate * forget_gate