code: def default_dqn_hparams():
      """Generates the default hparams for RLTuner DQN model."""
      return contrib_training.HParams(
          random_action_probability=0.1,
          store_every_nth=1,
          train_every_nth=5,
          minibatch_size=32,
          discount_rate=0.95,
          max_experience=100000,
          target_network_update_rate=0.01,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import random
  from magenta.contrib import training
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling a global function with example usage: default_dqn_hparams() and returns: contrib_training