python main.py -h

  --discount_rate DISCOUNT_RATE
                        Initial discount rate.
  --replay_memory_length REPLAY_MEMORY_LENGTH
                        Number of replay memory episode.
  --target_update_count TARGET_UPDATE_COUNT
                        DQN Target Network update count.
  --max_episode_count MAX_EPISODE_COUNT
                        Number of maximum episodes.
  --batch_size BATCH_SIZE
                        Batch size. (Must divide evenly into the dataset
                        sizes)
  --frame_size FRAME_SIZE
                        Frame size. (Stack env's observation T-n ~ T)
  --model_name MODEL_NAME
                        DeepLearning Network Model name (MLPv1, ConvNetv1)
  --learning_rate LEARNING_RATE
                        Batch size. (Must divide evenly into the dataset
                        sizes)
  --gym_result_dir GYM_RESULT_DIR
                        Directory to put the gym results.
  --gym_env GYM_ENV     Name of Open Gym's enviroment name. (CartPole-v0,
                        CartPole-v1, MountainCar-v0)
  --step_verbose [STEP_VERBOSE]
                        verbose every step count
  --step_verbose_count STEP_VERBOSE_COUNT
                        verbose step count