class_docstr: ### Convolutional Generator Network
  
  This is similar to the de-convolutional network used for CelebA faces,
  but modified for MNIST images.
  
  ![DCGan Architecture](https://pytorch.org/tutorials/_images/dcgan_generator.png)
class_docstr_tok: ["#","#","#","Convolutional","Generator","Network","This","is","similar","to","the","de-convolutional","network","used","for","CelebA","faces",",","but","modified","for","MNIST","images",".","!","[","DCGan","Architecture","]","(","https",":","\/\/pytorch.org\/tutorials\/_images\/dcgan_generator.png",")"]
code: def forward(self, x):
      # Change from shape `[batch_size, 100]` to `[batch_size, 100, 1, 1]`
      x = x.unsqueeze(-1).unsqueeze(-1)
      x = self.layers(x)
      return x
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/gan/dcgan/__init__.py
imports: import torch.nn
  from labml import experiment
  from labml.configs import calculate
  from labml_helpers.module import Module
  from labml_nn.gan.original.experiment import Configs
label_desc: Use image node_id 2 for calling the Generator obj's underlying member method code with example usage: obj.forward(x) and returns: x