class_docstr: Generator Loss module
class_docstr_tok: ["Generator","Loss","module"]
code: def forward(self, disc_outputs):
      loss = 0
      gen_losses = []
      for dg in disc_outputs:
          dg = dg.float()
          l = torch.mean((1 - dg) ** 2)
          gen_losses.append(l)
          loss += l
  
      return loss, gen_losses
  
imports: import torch
  from nemo.core.classes import Loss, typecheck
  from nemo.core.neural_types.elements import LossType, VoidType
  from nemo.core.neural_types.neural_type import NeuralType
label_desc: Use image node_id 3 for calling the GeneratorLoss obj's underlying member method code with example usage: obj.forward(disc_outputs) and returns: loss,  gen_losses