code: def planner_base():
      return hparam.HParams(
          num_rollouts=96,
          batch_size=96,
          planning_horizon=8,
          rollout_agent_type="policy",
          env_type="simulated",
          uct_const=0.0,
          uniform_first_action=True,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import datetime
  import os
  from tensor2tensor.data_generators import gym_env
  from tensor2tensor.layers import common_video
  from tensor2tensor.models.research import rl
  from tensor2tensor.rl import rl_utils
  from tensor2tensor.rl import trainer_model_based_params
  from tensor2tensor.utils import flags
  from tensor2tensor.utils import hparam
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import trainer_lib
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling a global function with example usage: planner_base() and returns: hparam