code: def testBuildsStackedLstm(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, 3)
      )
  
      net = value_rnn_network.ValueRnnNetwork(
          observation_spec,
          conv_layer_params=[(4, 2, 2)],
          input_fc_layer_params=(5,),
          lstm_size=(7, 5),
          output_fc_layer_params=(3,),
      )
  
      _, state = net(
          time_step.observation,
          step_type=time_step.step_type,
          network_state=net.get_initial_state(batch_size=1),
      )
      self.evaluate(tf.compat.v1.global_variables_initializer())
  
      # Assert LSTM cell is created.
      self.assertEqual((1, 7), state[0][0].shape)
      self.assertEqual((1, 7), state[0][1].shape)
  
      # Assert LSTM cell is created.
      self.assertEqual((1, 5), state[1][0].shape)
      self.assertEqual((1, 5), state[1][1].shape)
  
file_path: agents/tf_agents/networks/value_rnn_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_rnn_network
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import time_step
label_desc: Use image node_id 2 for calling the ValueRnnNetworkTest obj's underlying member method code with example usage: obj.testBuildsStackedLstm() without return types