class_docstr: Base wrapper class.
class_docstr_tok: ["Base","wrapper","class","."]
docstr: Returns observations from the root simulated env's history_buffer.
  
  Transforms them with a wrapper-specific function if necessary.
  
  Raises:
    AttributeError: if root env doesn't have a history_buffer (i.e. is not
      simulated).
docstr_tok: ["Returns","observations","from","the","root","simulated","env","'s","history_buffer",".","Transforms","them","with","a","wrapper-specific","function","if","necessary",".","Raises",":","AttributeError",":","if","root","env","does","n't","have","a","history_buffer","(","i.e",".","is","not","simulated",")","."]
code: def history_observations(self):
      """Returns observations from the root simulated env's history_buffer.
  
      Transforms them with a wrapper-specific function if necessary.
  
      Raises:
        AttributeError: if root env doesn't have a history_buffer (i.e. is not
          simulated).
      """
      return self._transform_history_observations(
          self._batch_env.history_observations
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from six.moves import range
  from tensor2tensor.rl.envs.in_graph_batch_env import InGraphBatchEnv
  import tensorflow.compat.v1
label_desc: Use image node_id 8 for calling the WrapperBase obj's underlying member method code with example usage: obj.history_observations() and returns: self