code: def make_agent(self, env, gpu):
      q_func = self.make_q_func(env)
      opt = self.make_optimizer(env, q_func)
      explorer = self.make_explorer(env)
      rbuf = self.make_replay_buffer(env)
      agent = self.make_dqn_agent(
          env=env,
          q_func=q_func,
          opt=opt,
          explorer=explorer,
          rbuf=rbuf,
          gpu=gpu,
      )
      return agent
  
imports: import numpy
  import torch.nn
  import torch.optim
  from basetest_training import _TestTraining
  from pfrl import q_functions, replay_buffers
  from pfrl.envs.abc import ABC
  from pfrl.explorers.epsilon_greedy import LinearDecayEpsilonGreedy
  from pfrl.nn import RecurrentSequential
label_desc: Use image node_id 1 for calling the _TestDQNLike obj's underlying member method code with example usage: obj.make_agent(env, gpu) and returns: agent