def __init__()

in src/hyperconv.py [0:0]

• 21 lines of code
• 2 McCabe index (conditional complexity)

    def __init__(self, ch_in, ch_out, z_dim, kernel_size, dilation=1):
        '''
        :param ch_in: (int) input channels
        :param ch_out: (int) output channels
        :param z_dim: (int) dimension of the weight-generating input
        :param kernel_size: (int) size of the filter
        :param dilation: (int) dilation
        '''
        super().__init__()

        self.kernel_size = kernel_size
        self.dilation = dilation
        self.ch_in = ch_in
        self.ch_out = ch_out
        self.conv = HyperConv(z_dim, ch_in, ch_out, kernel_size, dilation)
        self.residual = nn.Conv1d(ch_out, ch_out, kernel_size=1)
        self.residual.weight.data.uniform_(-np.sqrt(6.0/ch_out), np.sqrt(6.0/ch_out))
        self.skip = nn.Conv1d(ch_out, ch_out, kernel_size=1)
        self.skip.weight.data.uniform_(-np.sqrt(6.0/ch_out), np.sqrt(6.0/ch_out))
        if not ch_in == ch_out:
            self.equalize_channels = nn.Conv1d(ch_in, ch_out, kernel_size=1)
            self.equalize_channels.weight.data.uniform_(-np.sqrt(6.0 / ch_in), np.sqrt(6.0 / ch_in))