class_docstr: Mean Squared Generator Loss 
class_docstr_tok: ["Mean","Squared","Generator","Loss"]
code: def forward(self, score_real):
      loss_fake = F.mse_loss(
          score_real, score_real.new_ones(score_real.shape)
      )
      return loss_fake
  
imports: import torch
  from torch import nn
  from torch.nn import functional
label_desc: Use image node_id 1 for calling the MSEGLoss obj's underlying member method code with example usage: obj.forward(score_real) and returns: loss_fake