code: def __init__(self, action_spec, emit_distribution=True, name=None):
      super(DummyActorNet, self).__init__(
          tensor_spec.TensorSpec([2], tf.float32), (), "DummyActorNet"
      )
      self._action_spec = action_spec
      self._flat_action_spec = tf.nest.flatten(self._action_spec)[0]
  
      self._dummy_layers = [
          tf.keras.layers.Dense(
              self._flat_action_spec.shape.num_elements(),
              kernel_initializer=tf.constant_initializer([2, 1]),
              bias_initializer=tf.constant_initializer([5]),
              activation=tf.keras.activations.tanh,
          )
      ]
  
      self._emit_distribution = emit_distribution
  
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 DummyActorNet object from inherited base classes: network with example: obj = DummyActorNet(action_spec, emit_distribution, name)