class_docstr: Wrapper around `crit_loss_func` and `gen_loss_func`
class_docstr_tok: ["Wrapper","around","`","crit_loss_func","`","and","`","gen_loss_func","`"]
docstr: Evaluate the `output` with the critic then uses `self.gen_loss_func` to evaluate how well the critic was fooled by `output`
docstr_tok: ["Evaluate","the","`","output","`","with","the","critic","then","uses","`","self.gen_loss_func","`","to","evaluate","how","well","the","critic","was","fooled","by","`","output","`"]
code: def generator(
      self, output, target  # Generator outputs  # Real images
  ):
      "Evaluate the `output` with the critic then uses `self.gen_loss_func` to evaluate how well the critic was fooled by `output`"
      fake_pred = self.gan_model.critic(output)
      self.gen_loss = self.gen_loss_func(fake_pred, output, target)
      return self.gen_loss
  
imports: from __future__ import annotations
  from ..basics import *
  from .all import *
label_desc: Use image node_id 2 for calling the GANLoss obj's underlying member method code with example usage: obj.generator(output, target) and returns: self