ca1dace7450bb597044dba651c3efae0b8430a46,implementations/acgan/acgan.py,Discriminator,__init__,#Discriminator#,75

Before Change

                block.append(nn.BatchNorm2d(out_filters, 0.8))
            return block

        layers = []
        in_filters = opt.channels
        for out_filters, bn in [(16, False), (32, True), (64, True), (128, False)]:
            layers.extend(discriminator_block(in_filters, out_filters, bn))
            in_filters = out_filters

        self.conv_blocks = nn.Sequential(*layers)

        // The height and width of downsampled image
        ds_size = opt.img_size // 2**4

After Change

                block.append(nn.BatchNorm2d(out_filters, 0.8))
            return block

        self.conv_blocks = nn.Sequential(
            *discrimintor_block(opt.channels, 16, bn=False),
            *discriminator_block(16, 32),
            *discriminator_block(32, 64),
            *discriminator_block(64, 128),
        )

        // The height and width of downsampled image
        ds_size = opt.img_size // 2**4

Instances