def __init__()

in part_generator.py [0:0]

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

    def __init__(self, image_size, latent_dim, network_capacity=16):
        super().__init__()
        self.image_size = image_size
        self.latent_dim = latent_dim
        self.num_layers = int(log2(image_size) - 1)

        init_channels = 4 * network_capacity
        self.initial_block = nn.Parameter(torch.randn((init_channels, 4, 4)))
        filters = [init_channels] + [network_capacity * (2 ** (i + 1)) for i in range(self.num_layers)][::-1]
        in_out_pairs = zip([ch+network_capacity*(2 ** (self.num_layers-1-i)) for i, ch in enumerate(filters[0:-1])], filters[1:])

        self.blocks = nn.ModuleList([])
        for ind, (in_chan, out_chan) in enumerate(in_out_pairs):
            not_first = ind != 0
            not_last = ind != (self.num_layers - 1)

            block = GeneratorBlock(
                latent_dim,
                in_chan,
                out_chan,
                upsample = not_first,
                upsample_rgb = not_last
            )
            self.blocks.append(block)