class_docstr: Exposes a Python policy as an in-graph TensorFlow policy.
  
  # TODO(kbanoop): This class does not seem to handle batching/unbatching when
  # converting between TF and Py policies.
class_docstr_tok: ["Exposes","a","Python","policy","as","an","in-graph","TensorFlow","policy",".","#","TODO","(","kbanoop",")",":","This","class","does","not","seem","to","handle","batching\/unbatching","when","#","converting","between","TF","and","Py","policies","."]
code: def _distribution(self, time_step, policy_state):
      raise NotImplementedError(
          "%s does not support distribution yet."
          % self.__class__.__name__
      )
  
file_path: agents/tf_agents/policies/tf_py_policy.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Optional, Text
  import tensorflow
  from tf_agents.policies import py_policy
  from tf_agents.policies import tf_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.typing import types
  from tf_agents.utils import common
  from tf_agents.utils import nest_utils
label_desc: Use image node_id 5 for calling the TFPyPolicy obj's underlying member method code with example usage: obj._distribution(time_step, policy_state) without return types