def rlmb_base_stochastic_discrete_20k():
  """Base setting with stochastic discrete model with 20k steps."""
  hparams = rlmb_base_stochastic_discrete()
  # Our num_real_env_frames should be divisible by real_ppo_epoch_length*epochs
  # Here we decrease epochs to 6 and make this number 16*200*6.
  hparams.num_real_env_frames = 19200
  hparams.epochs = 6
  hparams.ppo_epochs_num = 2000  # Increase PPO steps as we have less epochs.
  return hparams
Base setting with stochastic discrete model with 20k steps.
tensor2tensor/rl/trainer_model_based_params.py