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,
      info_spec,
      name=None,
  ):
      self._distribution_value = distribution
      super(DistributionPolicy, self).__init__(
          time_step_spec=time_step_spec,
          action_spec=action_spec,
          info_spec=info_spec,
          name=name,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import tensorflow.compat.v2
  import tensorflow_probability
  from tf_agents.policies import policy_info_updater_wrapper
  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, info_spec, name)