class_docstr:     ## Generator Loss
  
      Generator should **descend** on the gradient,
  
      $$
  abla_{  heta_g} rac{1}{m} \sum_{i=1}^m \Bigg[
          \log \Big(1 - D\Big(G\Big(\pmb{z}^{(i)}\Big)\Big)\Big)
      \Bigg]$$
      
code: def forward(self, logits: torch.Tensor):
      if len(logits) > len(self.fake_labels):
          self.register_buffer(
              "fake_labels",
              _create_labels(
                  len(logits), 1.0 - self.smoothing, 1.0, logits.device
              ),
              False,
          )
  
      return self.loss_true(logits, self.fake_labels[: len(logits)])
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/gan/original/__init__.py
imports: import torch
  import torch.nn
  import torch.utils.data
  import torch.utils.data
  from labml_helpers.module import Module
label_desc: Use image node_id 2 for calling the GeneratorLogitsLoss obj's underlying member method code with example usage: obj.forward(logits) and returns: self