code: def planner_tiny():
      return hparam.HParams(
          num_rollouts=1,
          planning_horizon=2,
          rollout_agent_type="random",
          batch_size=1,
          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 1 for calling a global function with example usage: planner_tiny() and returns: hparam