def forward()

in src/hyperconv.py [0:0]

• 15 lines of code
• 3 McCabe index (conditional complexity)

    def forward(self, x, z):
        '''
        :param x: input signal as a B x ch_in x T tensor
        :param z: weight-generating input as a B x z_dim x K tensor (K s.t. T is a multiple of K)
        :return: output: B x ch_out x T tensor as layer output
                 skip: B x ch_out x T tensor as skip connection output
        '''
        assert x.shape[-1] % z.shape[-1] == 0
        y = self.conv(x, z)
        y = th.sin(y)
        # residual and skip
        residual = self.residual(y)
        if not self.ch_in == self.ch_out:
            x = self.equalize_channels(x)
        skip = self.skip(y)
        return (residual + x) / 2, skip