part_generator.py [444:463]:
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    def __init__(self, input_channels, filters, downsample=True):
        super().__init__()
        self.conv_res = nn.Conv2d(input_channels, filters, 1)

        self.net = nn.Sequential(
            nn.Conv2d(input_channels, filters, 3, padding=1),
            leaky_relu(),
            nn.Conv2d(filters, filters, 3, padding=1),
            leaky_relu()
        )

        self.downsample = nn.Conv2d(filters, filters, 3, padding = 1, stride = 2) if downsample else None

    def forward(self, x):
        res = self.conv_res(x)
        x = self.net(x)
        x = x + res
        if self.downsample is not None:
            x = self.downsample(x)
        return x
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part_selector.py [228:247]:
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    def __init__(self, input_channels, filters, downsample=True):
        super().__init__()
        self.conv_res = nn.Conv2d(input_channels, filters, 1)

        self.net = nn.Sequential(
            nn.Conv2d(input_channels, filters, 3, padding=1),
            leaky_relu(),
            nn.Conv2d(filters, filters, 3, padding=1),
            leaky_relu()
        )

        self.downsample = nn.Conv2d(filters, filters, 3, padding = 1, stride = 2) if downsample else None

    def forward(self, x):
        res = self.conv_res(x)
        x = self.net(x)
        x = x + res
        if self.downsample is not None:
            x = self.downsample(x)
        return x
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