class_docstr: History Buffer.
code: def __init__(
      self,
      initial_frame_chooser,
      observ_shape,
      observ_dtype,
      num_initial_frames,
      batch_size,
  ):
      self.batch_size = batch_size
      self._observ_dtype = observ_dtype
      initial_shape = (batch_size, num_initial_frames) + observ_shape
      self._initial_frames = tf.py_func(
          initial_frame_chooser, [tf.constant(batch_size)], observ_dtype
      )
      self._initial_frames.set_shape(initial_shape)
      self._history_buff = tf.Variable(
          tf.zeros(initial_shape, observ_dtype), trainable=False
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import os
  import numpy
  from tensor2tensor.data_generators.gym_env import DummyWorldModelProblem
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import common_video
  from tensor2tensor.rl.envs import in_graph_batch_env
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import trainer_lib
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 1 to create a new HistoryBuffer object from inherited base classes: object with example: obj = HistoryBuffer(initial_frame_chooser, observ_shape, observ_dtype, num_initial_frames, batch_size)