code: def make_agent(self, env, gpu):
      model = self.make_model(env)
      policy = model["policy"]
      q_func = model["q_function"]
  
      actor_opt = optimizers.Adam(alpha=1e-4)
      actor_opt.setup(policy)
  
      critic_opt = optimizers.Adam(alpha=1e-3)
      critic_opt.setup(q_func)
  
      explorer = self.make_explorer(env)
      rbuf = self.make_replay_buffer(env)
      return self.make_ddpg_agent(
          env=env,
          model=model,
          actor_opt=actor_opt,
          critic_opt=critic_opt,
          explorer=explorer,
          rbuf=rbuf,
          gpu=gpu,
      )
  
imports: from chainer import optimizers
  import numpy
  from chainerrl.agents.ddpg import DDPGModel
  from chainerrl.envs.abc import ABC
  from chainerrl.explorers.epsilon_greedy import LinearDecayEpsilonGreedy
  from chainerrl.policy import FCBNDeterministicPolicy
  from chainerrl.policy import FCLSTMDeterministicPolicy
  from chainerrl.q_functions import FCBNLateActionSAQFunction
  from chainerrl.q_functions import FCLSTMSAQFunction
  from chainerrl import replay_buffer
  from basetest_training import _TestTraining
label_desc: Use image node_id 1 for calling the _TestDDPGOnABC obj's underlying member method code with example usage: obj.make_agent(env, gpu) and returns: self