code: def __init__(self, input_tensor_spec, output_tensor_spec):
      num_actions = output_tensor_spec.shape.num_elements()
      self._sequential = sequential_lib.Sequential(
          [
              tf.keras.layers.Dense(50),
              tf.keras.layers.Dense(10),
              tf.keras.layers.Dense(num_actions),
          ],
          input_spec=input_tensor_spec,
      )  # pytype: disable=wrong-arg-types
      super(ActorNetwork, self).__init__(
          input_tensor_spec=input_tensor_spec,
          state_spec=self._sequential.state_spec,
          name="TestActorNetwork",
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl import flags
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.distributions import utils
  from tf_agents.keras_layers import dynamic_unroll_layer
  from tf_agents.keras_layers import inner_reshape
  from tf_agents.networks import nest_map
  from tf_agents.networks import network
  from tf_agents.networks import sequential
  from tf_agents.policies import actor_policy
  from tf_agents.policies import policy_saver
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tf_agents.utils import common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 1 to create a new ActorNetwork object from inherited base classes: network with example: obj = ActorNetwork(input_tensor_spec, output_tensor_spec)