code: def make_trajectory(observations):
      """Make a simple trajectory from a sequence of observations.
  
      Arguments:
        observations: a sequence of observations.
  
      Returns:
        a tuple (first, steps) where first contains the initial dm_env.TimeStep
        object and steps contains a list of (action, step) tuples. The length of
        steps is given by episode_length.
      """
      first = dm_env.restart(observations[0])
      middle = [
          (0, dm_env.transition(reward=0.0, observation=observation))
          for observation in observations[1:-1]
      ]
      last = (
          0,
          dm_env.termination(reward=0.0, observation=observations[-1]),
      )
      return first, middle + [last]
  
imports: from typing import Any, Callable, Optional, Sequence, Tuple, TypeVar, Union
  from acme import specs
  from acme import types
  from acme.adders import base
  from acme.adders import reverb
  from acme.utils import tree_utils
  import dm_env
  import numpy
  import reverb
  import tensorflow
  import tree
  from absl.testing import absltest
label_desc: Use image node_id 1 for calling a global function with example usage: make_trajectory(observations) and returns: first,  unknown