class_docstr: A policy which always returns the configured distribution.
class_docstr_tok: ["A","policy","which","always","returns","the","configured","distribution","."]
code: def __init__(
      self, distribution, time_step_spec, action_spec, name=None
  ):
      self._distribution_value = distribution
      super(DistributionPolicy, self).__init__(
          time_step_spec, action_spec, name=name
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.policies import greedy_policy
  from tf_agents.policies import tf_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.utils import test_utils
label_desc: Use image node_id 1 to create a new DistributionPolicy object from inherited base classes: tf_policy with example: obj = DistributionPolicy(distribution, time_step_spec, action_spec, name)