code: def make_q_func(self, env):
      return q_functions.FCStateQFunctionWithDiscreteAction(
          env.observation_space.low.size, env.action_space.n, 10, 10
      )
  
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 _TestDQNOnDiscreteABC obj's underlying member method code with example usage: obj.make_q_func(env) and returns: q_functions