old_contents: __author__ = 'sxjscience'
  import mxnet as mx
  import numpy.random
  import os
  _ctx = mx.cpu()
  _numpy_rng = numpy.random.RandomState(10000)
  def get_ctx():
      return _ctx
  
  def get_numpy_rng():
      return _numpy_rng
  
  class IteratorDefaults:
      ROM_PATH = os.path.dirname(os.path.realpath(__file__)) + "/roms/breakout.bin"
      DISPLAY_SCREEN = False
      FRAME_SKIP = 4
      SLICE_LENGTH = 4
      RESIZED_ROWS = 84
      RESIZED_COLS = 84
      EXPLORATION_PROB_START = 1.0
      EXPLORATION_PROB_MIN = .1
      EXPLORATION_PROB_DECAY = 1E-6
      EPOCH_MAX_STEP = 250000
      EPOCHS = 10000000
      STEPS_PER_TEST = 125000
      BATCH_SIZE = 32
      DISCOUNT = 0.95
  
  class ReplayMemoryDefaults:
      REPLAY_MEMORY_SIZE = 1000000
      REPLAY_START_SIZE = 50000
  
  class LossDefaults:
      CLIP_DELTA = 1.0
  
  class OptimizerDefaults:
      LEARNING_RATE = .0002
      RMS_DECAY = .99
      RMS_EPSILON = 1E-6
      FREEZE_INTERVAL = 10000
      RESIZE_METHOD = 'scale'
      MAX_START_NULLOPS = 30
  
  class DQNDefaults:
      SHORTCUT_INTERVAL = 100
      SAVE_INTERVAL = 10000
      SAVE_DIR = os.path.dirname(os.path.realpath(__file__)) + "/model"
      SAVE_PREFIX = 'dqn'
new_contents: __author__ = 'sxjscience'
  import mxnet as mx
  import numpy.random
  import os
  _ctx = mx.cpu()
  _numpy_rng = numpy.random.RandomState(10000)
  def get_ctx():
      return _ctx
  
  def get_numpy_rng():
      return _numpy_rng
  
  class IteratorDefaults:
      ROM_PATH = os.path.dirname(os.path.realpath(__file__)) + "/roms/breakout.bin"
      DISPLAY_SCREEN = False
      FRAME_SKIP = 4
      SLICE_LENGTH = 4
      RESIZED_ROWS = 84
      RESIZED_COLS = 84
      EXPLORATION_PROB_START = 1.0
      EXPLORATION_PROB_MIN = .1
      EXPLORATION_PROB_DECAY = 1E-6
      EPOCH_MAX_STEP = 250000
      EPOCHS = 10000000
      STEPS_PER_TEST = 125000
      BATCH_SIZE = 32
      DISCOUNT = 0.95
  
  class ReplayMemoryDefaults:
      REPLAY_MEMORY_SIZE = 1000000
      REPLAY_START_SIZE = 5000
  
  class LossDefaults:
      CLIP_DELTA = 1.0
  
  class OptimizerDefaults:
      LEARNING_RATE = .0002
      RMS_DECAY = .99
      RMS_EPSILON = 1E-6
      FREEZE_INTERVAL = 10000
      RESIZE_METHOD = 'scale'
      MAX_START_NULLOPS = 30
  
  class DQNDefaults:
      SHORTCUT_INTERVAL = 100
      SAVE_INTERVAL = 10000
      SAVE_DIR = os.path.dirname(os.path.realpath(__file__)) + "/model"
      SAVE_PREFIX = 'dqn'
subject: Update DQN