code: def testHandlePreprocessingLayers(self):
      observation_spec = (
          tensor_spec.TensorSpec([1], tf.float32),
          tensor_spec.TensorSpec([], tf.float32),
      )
      observation = tensor_spec.sample_spec_nest(
          observation_spec, outer_dims=(3,)
      )
  
      preprocessing_layers = (
          tf.keras.layers.Dense(4),
          tf.keras.Sequential(
              [tf.keras.layers.Reshape((1,)), tf.keras.layers.Dense(4)]
          ),
      )
  
      net = value_network.ValueNetwork(
          observation_spec,
          preprocessing_layers=preprocessing_layers,
          preprocessing_combiner=tf.keras.layers.Add(),
      )
  
      value, _ = net(observation)
      self.assertEqual([3], value.shape.as_list())
      self.assertGreater(len(net.trainable_variables), 4)
  
file_path: agents/tf_agents/networks/value_network_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tf_agents.networks import value_network
  from tf_agents.specs import tensor_spec
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 3 for calling the ValueNetworkTest obj's underlying member method code with example usage: obj.testHandlePreprocessingLayers() without return types