code: def call(self, inputs, step_type=None, network_state=()):
      del step_type
      hidden_state = tf.cast(tf.nest.flatten(inputs), tf.float32)[0]
  
      # Calls coming from agent.train() has a time dimension. Direct loss calls
      # may not have a time dimension. It order to make BatchSquash work, we need
      # to specify the outer dimension properly.
      has_time_dim = (
          nest_utils.get_outer_rank(inputs, self.input_tensor_spec) == 2
      )
      outer_rank = 2 if has_time_dim else 1
      batch_squash = network_utils.BatchSquash(outer_rank)
      hidden_state = batch_squash.flatten(hidden_state)
  
      for layer in self._dummy_layers:
          hidden_state = layer(hidden_state)
  
      actions, stdevs = tf.split(hidden_state, 2, axis=1)
      actions = batch_squash.unflatten(actions)
      stdevs = batch_squash.unflatten(stdevs)
      actions = tf.nest.pack_sequence_as(self._action_spec, [actions])
      stdevs = tf.nest.pack_sequence_as(self._action_spec, [stdevs])
  
      return (
          self.output_spec.build_distribution(
              loc=actions, scale=stdevs
          ),
          network_state,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import tensorflow
  import tensorflow_probability
  from tf_agents.agents.cql import cql_sac_agent
  from tf_agents.agents.ddpg import critic_network
  from tf_agents.agents.ddpg import critic_rnn_network
  from tf_agents.agents.sac import tanh_normal_projection_network
  from tf_agents.networks import actor_distribution_network
  from tf_agents.networks import actor_distribution_rnn_network
  from tf_agents.networks import network
  from tf_agents.networks import utils
  from tf_agents.specs import distribution_spec
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.trajectories import trajectory
  from tf_agents.utils import common
  from tf_agents.utils import nest_utils
  from tf_agents.utils import test_utils
label_desc: Use image node_id 3 for calling the DummyActorNet obj's underlying member method code with example usage: obj.call(inputs, step_type, network_state) and returns: self,  network_state