code: def make_dqn_agent(self, env, q_func, opt, explorer, rbuf, gpu):
      return CategoricalDQN(
          q_func,
          opt,
          rbuf,
          gpu=gpu,
          gamma=0.9,
          explorer=explorer,
          replay_start_size=100,
          target_update_interval=100,
          recurrent=True,
      )
  
imports: import unittest
  import basetest_dqn_like
  import numpy
  import pytest
  import torch
  from basetest_training import _TestBatchTrainingMixin
  import pfrl
  from pfrl.agents import CategoricalDQN, categorical_dqn
  from pfrl.agents.categorical_dqn import compute_value_loss, compute_weighted_value_loss
label_desc: Use image node_id 2 for calling the TestCategoricalDQNOnDiscretePOABC obj's underlying member method code with example usage: obj.make_dqn_agent(env, q_func, opt, explorer, rbuf, gpu) and returns: CategoricalDQN