code: def make_optimizer(self, env, q_func):
      # Stabilize training by large eps
      opt = optimizers.Adam(1e-2, eps=1)
      opt.setup(q_func)
      return opt
  
imports: from chainer import functions
  from chainer import links
  from chainer import optimizers
  import numpy
  from chainerrl.action_value import DiscreteActionValue
  from chainerrl.envs.abc import ABC
  from chainerrl.explorers.epsilon_greedy import LinearDecayEpsilonGreedy
  from chainerrl.links import StatelessRecurrentSequential
  from chainerrl import q_functions
  from chainerrl import replay_buffer
  from basetest_training import _TestTraining
label_desc: Use image node_id 4 for calling the _TestDQNOnDiscretePOABC obj's underlying member method code with example usage: obj.make_optimizer(env, q_func) and returns: opt