code: def __init__(self, action_spec, name=None):
      output_spec = tf.nest.map_structure(
          self._get_normal_distribution_spec, action_spec
      )
      super(DummyActorDistributionNet, self).__init__(
          tensor_spec.TensorSpec([2], tf.float32),
          (),
          output_spec=output_spec,
          name="DummyActorDistributionNet",
      )
      self._action_net = DummyActorNet(
          action_spec, emit_distribution=False
      )
  
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.agents.ppo import ppo_policy
  from tf_agents.networks import actor_distribution_network
  from tf_agents.networks import mask_splitter_network
  from tf_agents.networks import network
  from tf_agents.networks import sequential
  from tf_agents.networks import value_network
  from tf_agents.specs import distribution_spec
  from tf_agents.specs import tensor_spec
  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 DummyActorDistributionNet object from inherited base classes: network with example: obj = DummyActorDistributionNet(action_spec, name)