@ptrblck Thanks for your response.  Yes, I checked the indentation. Indeed, my code runs normally and executes __init__ until the end, the problem rises when the __setattr__ function is called.
Here is the code of my Class:
class ResNetGenerator(nn.Module):
    def __init__(self, input_nc=3, output_nc=3, n_residual_blocks=9, use_dropout=False):
        print("*"*50)
        super(ResNetGenerator, self).__init__()
        # super().__init__()
        # nn.Module.__init__(self)

        # Input layer
        model = [nn.ReflectionPad2d(3),
                 nn.Conv2d(input_nc, 64, kernel_size=7, padding=0),
                 nn.InstanceNorm2d(64),
                 nn.ReLU(True)]

        # Encoding layers
        in_features = 64
        out_features = in_features * 2

        for _ in range(2):
            model += [nn.Conv2d(in_features, out_features, kernel_size=3, stride=2, padding=1),
                      nn.InstanceNorm2d(out_features),
                      nn.ReLU(True)]
            in_features = out_features
            out_features = in_features * 2

        # Transformations layers (Residual blocks)
        for _ in range(n_residual_blocks):
            model += [ResidualBlock(in_features, use_dropout)]
        # Decoding layers
        out_features = in_features // 2

        for _ in range(2):
            model += [nn.ConvTranspose2d(in_features, out_features, kernel_size=3, stride=2, padding=1, output_padding=1),
                      nn.InstanceNorm2d(out_features),
                      nn.ReLU(True)]
            in_features = out_features
            out_features = in_features // 2

        # Output layer
        model += [nn.ReflectionPad2d(3),
                  nn.Conv2d(64, output_nc, kernel_size=7, padding=0),
                  nn.Tanh()]

        self.model = nn.Sequential(*model)
        print("#"*50)

    def forward(self, x):
        return self.model(x)

And Here is the complete Traceback:
File "train.py", line 40, in <module>
    model = ColorizationCycleGAN(args)
File "/path/cycle_gan.py", line 27, in __init__
    self.G_A2B = ResNetGenerator(input_nc=self.input_nc, output_nc=self.output_nc, n_residual_blocks=9, use_dropout=False)
File "/path/.local/lib/python3.6/site packages/torch/nn/modules/module.py", line 544, in __setattr__
    "cannot assign module before Module.__init__() call")
AttributeError: cannot assign module before Module.__init__() call