# Codeblock 9
class UpSample(nn.Module):
    def __init__(self, in_channels, out_channels):
        super().__init__()
        
        self.conv_transpose = nn.ConvTranspose2d(in_channels=in_channels,  #(1)
                                                 out_channels=out_channels, 
                                                 kernel_size=2, stride=2)  #(2)
        self.double_conv = DoubleConv(in_channels=in_channels,  #(3)
                                      out_channels=out_channels)
        
    def forward(self, x, t, connection):  #(4)
        print(f'original\t\t: {x.size()}')
        print(f'timesteps\t\t: {t.size()}, {t}')
        print(f'connection\t\t: {connection.size()}')
        
        x = self.conv_transpose(x)  #(5)
        print(f'\nafter conv transpose\t: {x.size()}')
        
        x = torch.cat([x, connection], dim=1)  #(6)
        print(f'after concat\t\t: {x.size()}')
        
        x = self.double_conv(x, t)  #(7)
        print(f'after double conv\t: {x.size()}')
        
        return x