# Codeblock 5
class Residual(nn.Module):
    def __init__(self, num_channels):
        super().__init__()
        self.conv0 = Convolutional(in_channels=num_channels, 
                                   out_channels=num_channels//2,   #(1)
                                   kernel_size=1,       #(2)
                                   stride=1)
        
        self.conv1 = Convolutional(in_channels=num_channels//2,
                                   out_channels=num_channels,      #(3)
                                   kernel_size=3,       #(4)
                                   stride=1)
        
    def forward(self, x):
        original = x.clone()
        print(f'original\t: {x.size()}')
        
        x = self.conv0(x)
        print(f'after conv0\t: {x.size()}')
        
        x = self.conv1(x)
        print(f'after conv1\t: {x.size()}')
        
        x = x + original      #(5)
        print(f'after summation\t: {x.size()}')
        
        return x