class_docstr: Returns random samples of the given action_spec.
  
  Note: the values in the info_spec (except for the log_probability) are random
    values that have nothing to do with the emitted actions.
  
  Note: The returned info.log_probabiliy will be an object matching the
  structure of action_spec, where each value is a tensor of size [batch_size].
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code: def _distribution(self, time_step, policy_state):
      raise NotImplementedError(
          "RandomTFPolicy does not support distributions yet."
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import cast
  import tensorflow
  from tf_agents.distributions import masked
  from tf_agents.policies import tf_policy
  from tf_agents.policies import utils
  from tf_agents.specs import bandit_spec_utils
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.typing import types
  from tf_agents.utils import nest_utils
label_desc: Use image node_id 4 for calling the RandomTFPolicy obj's underlying member method code with example usage: obj._distribution(time_step, policy_state) without return types