class_docstr: Stateful observer for writing fixed length trajectories to Reverb.
  
  This observer should be called at every environment step. It does not support
  batched trajectories.
  
  Steps are cached until `sequence_length` steps are gathered. At which point an
  item is created. From there on a new item is created every `stride_length`
  observer calls.
  
  If an episode terminates before enough steps are cached, the data is discarded
  unless `pad_end_of_episodes` is set.
code: def py_client(self) -> types.ReverbClient:
      return self._py_client
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Sequence, Text, Union
  from absl import logging
  import tensorflow
  from tf_agents.trajectories import trajectory
  from tf_agents.typing import types
  from tf_agents.utils import lazy_loader
label_desc: Use image node_id 3 for calling the ReverbAddTrajectoryObserver obj's underlying member method code with example usage: obj.py_client() and returns: self