code: def testBuilds(self):
      observation_spec = tensor_spec.BoundedTensorSpec(
          (8, 8, 3), tf.float32, 0, 1
      )
      time_step_spec = ts.time_step_spec(observation_spec)
      time_step = tensor_spec.sample_spec_nest(
          time_step_spec, outer_dims=(1,)
      )
  
      action_spec = [
          tensor_spec.BoundedTensorSpec((2,), tf.float32, 2, 3),
          tensor_spec.BoundedTensorSpec((3,), tf.float32, 0, 3),
      ]
      net = actor_rnn_network.ActorRnnNetwork(
          observation_spec,
          action_spec,
          conv_layer_params=[(4, 2, 2)],
          input_fc_layer_params=(5,),
          lstm_size=(3,),
          output_fc_layer_params=(5,),
      )
  
      actions, network_state = net(
          time_step.observation,
          time_step.step_type,
          net.get_initial_state(batch_size=1),
      )
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.assertEqual([1, 2], actions[0].shape.as_list())
      self.assertEqual([1, 3], actions[1].shape.as_list())
  
      self.assertEqual(13, len(net.variables))
      # Conv Net Kernel
      self.assertEqual((2, 2, 3, 4), net.variables[0].shape)
      # Conv Net bias
      self.assertEqual((4,), net.variables[1].shape)
      # Fc Kernel
      self.assertEqual((64, 5), net.variables[2].shape)
      # Fc Bias
      self.assertEqual((5,), net.variables[3].shape)
      # LSTM Cell Kernel
      self.assertEqual((5, 12), net.variables[4].shape)
      # LSTM Cell Recurrent Kernel
      self.assertEqual((3, 12), net.variables[5].shape)
      # LSTM Cell Bias
      self.assertEqual((12,), net.variables[6].shape)
      # Fc Kernel
      self.assertEqual((3, 5), net.variables[7].shape)
      # Fc Bias
      self.assertEqual((5,), net.variables[8].shape)
      # Action 1 Kernel
      self.assertEqual((5, 2), net.variables[9].shape)
      # Action 1 Bias
      self.assertEqual((2,), net.variables[10].shape)
      # Action 2 Kernel
      self.assertEqual((5, 3), net.variables[11].shape)
      # Action 2 Bias
      self.assertEqual((3,), net.variables[12].shape)
  
      # Assert LSTM cell is created.
      self.assertEqual((1, 3), network_state[0].shape)
      self.assertEqual((1, 3), network_state[1].shape)
  
file_path: agents/tf_agents/agents/ddpg/actor_rnn_network_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  from tf_agents.agents.ddpg import actor_rnn_network
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 1 for calling the ActorRnnNetworkTest obj's underlying member method code with example usage: obj.testBuilds() without return types