code: def __init__(self, input_tensor_spec, output_tensor_spec):
      super(DummyActionNet, self).__init__(
          input_tensor_spec=input_tensor_spec,
          state_spec=(),
          name="DummyActionNet",
      )
      self._forward = tf.keras.layers.Dense(
          output_tensor_spec.shape.num_elements(),
          activation=tf.nn.tanh,
          kernel_initializer=None,
          bias_initializer=None,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from absl import flags
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tf_agents.networks import network
  from tf_agents.policies import actor_policy
  from tf_agents.policies import ou_noise_policy
  from tf_agents.policies import py_tf_policy
  from tf_agents.policies import q_policy
  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 DummyActionNet object from inherited base classes: network with example: obj = DummyActionNet(input_tensor_spec, output_tensor_spec)