code: def call(self, inputs, step_type=None, network_state=()):
      del step_type
      hidden_state = tf.cast(tf.nest.flatten(inputs), tf.float32)[0]
      batch_squash = network_utils.BatchSquash(self._outer_rank)
      hidden_state = batch_squash.flatten(hidden_state)
      for layer in self._dummy_layers:
          hidden_state = layer(hidden_state)
      value_pred = tf.squeeze(
          batch_squash.unflatten(hidden_state), axis=-1
      )
      return value_pred, network_state
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  from absl.testing.absltest import mock
  import tensorflow
  import tensorflow_probability
  from tf_agents.agents.reinforce import reinforce_agent
  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 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
label_desc: Use image node_id 2 for calling the DummyValueNet obj's underlying member method code with example usage: obj.call(inputs, step_type, network_state) and returns: value_pred,  network_state