code: def rl_parameters(self):
      return self.trainer_param.rl
  
imports: import logging
  from typing import Dict, Optional
  import reagent.core.types
  import torch
  from reagent.core.dataclasses import dataclass, field
  from reagent.core.parameters import EvaluationParameters, NormalizationData, NormalizationKey, param_hash
  from reagent.evaluation.evaluator import get_metrics_to_score
  from reagent.gym.policies.policy import Policy
  from reagent.gym.policies.predictor_policies import create_predictor_policy_from_model
  from reagent.model_managers.discrete_dqn_base import DiscreteDQNBase
  from reagent.models.base import ModelBase
  from reagent.net_builder.discrete_actor.fully_connected import FullyConnected
  from reagent.net_builder.discrete_dqn.dueling import Dueling
  from reagent.net_builder.discrete_dqn.fully_connected import FullyConnected
  from reagent.net_builder.unions import DiscreteActorNetBuilder__Union, DiscreteDQNNetBuilder__Union
  from reagent.prediction.cfeval.predictor_wrapper import BanditRewardNetPredictorWrapper
  from reagent.reporting.discrete_crr_reporter import DiscreteCRRReporter
  from reagent.training import CRRTrainerParameters, DiscreteCRRTrainer, ReAgentLightningModule
  from reagent.workflow.types import RewardOptions
label_desc: Use image node_id 3 for calling the DiscreteCRR obj's underlying member method code with example usage: obj.rl_parameters() and returns: self