class_docstr: Trains a joint policy-and-value model using actor-critic methods.
class_docstr_tok: ["Trains","a","joint","policy-and-value","model","using","actor-critic","methods","."]
docstr: Use self.task to create inputs to the policy model.
docstr_tok: ["Use","self.task","to","create","inputs","to","the","policy","model","."]
code: def batches_stream(self):
      """Use self.task to create inputs to the policy model."""
      return NotImplementedError
  
imports: import functools
  from trax import data
  from trax import layers
  from trax import supervised
  from trax.fastmath import numpy
  from trax.fastmath import stop_gradient
  from trax.rl import actor_critic
  from trax.rl import distributions
  from trax.rl import rl_layers
  from trax.rl import training
  from trax.supervised import lr_schedules
label_desc: Use image node_id 3 for calling the ActorCriticJointAgent obj's underlying member method code with example usage: obj.batches_stream() and returns: NotImplementedError