# Codeblock 8
class InvResidualS1(nn.Module):
    def __init__(self, in_channels, out_channels, t):
        super().__init__()
        
        in_channels  = int(in_channels*WIDTH_MULTIPLIER)    #(1)
        out_channels = int(out_channels*WIDTH_MULTIPLIER)   #(2)
        
        self.in_channels  = in_channels
        self.out_channels = out_channels
        
        self.pwconv0 = nn.Conv2d(in_channels=in_channels, 
                                 out_channels=in_channels*t, 
                                 kernel_size=1, 
                                 stride=1, 
                                 bias=False)
        
        self.bn_pwconv0 = nn.BatchNorm2d(num_features=in_channels*t)
        
        self.dwconv = nn.Conv2d(in_channels=in_channels*t, 
                                out_channels=in_channels*t, 
                                kernel_size=3, 
                                stride=1,            #(3)
                                padding=1,
                                groups=in_channels*t, 
                                bias=False)
        
        self.bn_dwconv = nn.BatchNorm2d(num_features=in_channels*t)
        
        self.pwconv1 = nn.Conv2d(in_channels=in_channels*t, 
                                 out_channels=out_channels, 
                                 kernel_size=1, 
                                 stride=1, 
                                 bias=False)
        
        self.bn_pwconv1 = nn.BatchNorm2d(num_features=out_channels)
        
        self.relu6 = nn.ReLU6()
        
    def forward(self, x):
        
        if self.in_channels == self.out_channels:    #(4)
            residual = x          #(5)
            print(f'residual\t\t: {residual.size()}')
        
        x = self.pwconv0(x)
        print('after pwconv0\t\t:', x.shape)
        x = self.bn_pwconv0(x)
        print('after bn_pwconv0\t:', x.shape)
        x = self.relu6(x)
        print('after relu\t\t:', x.shape)
        
        x = self.dwconv(x)
        print('after dwconv\t\t:', x.shape)
        x = self.bn_dwconv(x)
        print('after bn_dwconv\t\t:', x.shape)
        x = self.relu6(x)
        print('after relu\t\t:', x.shape)
        
        x = self.pwconv1(x)
        print('after pwconv1\t\t:', x.shape)
        x = self.bn_pwconv1(x)
        print('after bn_pwconv1\t:', x.shape)
        
        if self.in_channels == self.out_channels:
            x = x + residual      #(6)
            print('after summation\t\t:', x.shape)
        
        return x