code: def configure_optimizers(self):
      optimizers = []
      # value net optimizer
      if self.value_net is not None:
          optimizers.append(
              self.optimizer_value_net.make_optimizer_scheduler(
                  self.value_net.parameters()
              )
          )
      # policy optimizer
      optimizers.append(
          self.optimizer.make_optimizer_scheduler(
              self.scorer.parameters()
          )
      )
  
      return optimizers
  
imports: import inspect
  import logging
  import math
  from dataclasses import field
  from typing import List, Optional
  import reagent.core.types
  import torch
  import torch.optim
  from reagent.gym.policies.policy import Policy
  from reagent.models.base import ModelBase
  from reagent.optimizer.union import Optimizer__Union
  from reagent.training.reagent_lightning_module import ReAgentLightningModule
  from reagent.training.utils import discounted_returns, whiten
label_desc: Use image node_id 3 for calling the ReinforceTrainer obj's underlying member method code with example usage: obj.configure_optimizers() and returns: optimizers