2021SC@SDUSC 开源项目GFPGAN-3-2021-10-15-class ModulatedConv2d(nn.Module)分析-优快云博客

本文链接：https://blog.youkuaiyun.com/weixin_46915928/article/details/120772324

本文分析了GFPGAN开源项目中的ModulatedConv2d模块，详细探讨了其init方法的参数，如in_channels、out_channels、kernel_size等，并解释了forward方法的功能——对输入张量进行规范化卷积。内容涉及到深度学习中的神经网络和PyTorch库的应用。

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2021SC@SDUSC

一、分析的代码片段

1、代码展示

class ModulatedConv2d(nn.Module):
    """Modulated Conv2d used in StyleGAN2.

    There is no bias in ModulatedConv2d.

    Args:
        in_channels (int): Channel number of the input.
        out_channels (int): Channel number of the output.
        kernel_size (int): Size of the convolving kernel.
        num_style_feat (int): Channel number of style features.
        demodulate (bool): Whether to demodulate in the conv layer.
            Default: True.
        sample_mode (str | None): Indicating 'upsample', 'downsample' or None.
            Default: None.
        eps (float): A value added to the denominator for numerical stability.
            Default: 1e-8.
    """

    def __init__(self,
                 in_channels,
                 out_channels,
                 kernel_size,
                 num_style_feat,
                 demodulate=True,
                 sample_mode=None,
                 eps=1e-8):
        super(ModulatedConv2d, self).__init__()
        self.in_channels = in_channels
        self.out_channels = out_channels
        self.kernel_size = kernel_size
        self.demodulate = demodulate
        self.sample_mode = sample_mode
        self.eps = eps

        # modulation inside each modulated conv
        self.modulation = nn.Linear(num_style_feat, in_channels, bias=True)
        # initialization
        default_init_weights(self.modulation, scale=1, bias_fill=1, a=0, mode='fan_in',