class_docstr: Critic Regularized Regression (CRR) algorithm trainer
  as described in https://arxiv.org/abs/2006.15134
code: def configure_optimizers(self):
      optimizers = []
      target_params = list(self.q1_network_target.parameters())
      source_params = list(self.q1_network.parameters())
  
      optimizers.append(
          self.q_network_optimizer.make_optimizer_scheduler(
              self.q1_network.parameters()
          )
      )
      if self.q2_network:
          target_params += list(self.q2_network_target.parameters())
          source_params += list(self.q2_network.parameters())
          optimizers.append(
              self.q_network_optimizer.make_optimizer_scheduler(
                  self.q2_network.parameters()
              )
          )
  
      target_params += list(self.actor_network_target.parameters())
      source_params += list(self.actor_network.parameters())
      optimizers.append(
          self.actor_network_optimizer.make_optimizer_scheduler(
              self.actor_network.parameters()
          )
      )
  
      if self.calc_cpe_in_training:
          (
              cpe_target_params,
              cpe_source_params,
              cpe_optimizers,
          ) = self._configure_cpe_optimizers()
          target_params += cpe_target_params
          source_params += cpe_source_params
          optimizers += cpe_optimizers
  
      optimizers.append(
          SoftUpdate.make_optimizer_scheduler(
              target_params, source_params, tau=self.tau
          )
      )
  
      return optimizers
  
imports: import logging
  from typing import List, Tuple
  import reagent.core.types
  import torch
  import torch.nn.functional
  from reagent.core.configuration import resolve_defaults
  from reagent.core.dataclasses import field
  from reagent.core.parameters import EvaluationParameters, RLParameters
  from reagent.optimizer import Optimizer__Union, SoftUpdate
  from reagent.training.dqn_trainer_base import DQNTrainerBaseLightning
  from torch import distributions
label_desc: Use image node_id 4 for calling the DiscreteCRRTrainer obj's underlying member method code with example usage: obj.configure_optimizers() and returns: optimizers