code: def create_trajectory(
      state: types.Array,
      action: types.Array,
      discount: types.Array,
      reward: types.Array,
      step_type: types.Array,
      next_step_type: types.Array,
  ) -> trajectory.Trajectory:
      """Creates a Trajectory from current and next state information."""
      return trajectory.Trajectory(
          step_type=step_type,
          observation=state,
          action=action,
          policy_info=(),
          next_step_type=next_step_type,
          reward=reward,
          discount=discount,
      )
  
file_path: agents/tf_agents/examples/cql_sac/kumar20/dataset/file_utils.py
imports: from typing import Dict
  from absl import logging
  import d4rl
  import numpy
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
  from tf_agents.typing import types
  from tf_agents.utils import example_encoding_dataset
label_desc: Use image node_id 1 for calling a global function with example usage: create_trajectory(state, action, discount, reward, step_type, next_step_type) and returns: trajectory