code: def create_transition(
      state: types.Array,
      action: types.Array,
      next_state: types.Array,
      discount: types.Array,
      reward: types.Array,
      step_type: types.Array,
      next_step_type: types.Array,
  ) -> trajectory.Transition:
      """Creates a Transition from current and next state information."""
      tfagents_time_step = ts.TimeStep(
          step_type=step_type,
          reward=np.zeros_like(reward),  # unknown
          discount=np.zeros_like(discount),  # unknown
          observation=state,
      )
      action_step = policy_step.PolicyStep(
          action=action, state=(), info=()
      )
      tfagents_next_time_step = ts.TimeStep(
          step_type=next_step_type,
          reward=reward,
          discount=discount,
          observation=next_state,
      )
      return trajectory.Transition(
          time_step=tfagents_time_step,
          action_step=action_step,
          next_time_step=tfagents_next_time_step,
      )
  
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 2 for calling a global function with example usage: create_transition(state, action, next_state, discount, reward, step_type, next_step_type) and returns: trajectory