code: def testCombinedFeatureColumnInput(self):
      columns = {}
      state_tensors = {}
      state_specs = {}
      expected_dim = 0
  
      indicator_key = "indicator_key"
      vocab_list = [2, 3, 4]
      column1 = (
          tf.feature_column.categorical_column_with_vocabulary_list(
              indicator_key, vocab_list
          )
      )
      columns[indicator_key] = tf.feature_column.indicator_column(
          column1
      )
      state_tensors[indicator_key] = tf.expand_dims([3, 2, 2, 4, 3], -1)
      state_specs[indicator_key] = tensor_spec.TensorSpec([1], tf.int32)
      expected_dim += len(vocab_list)
  
      embedding_key = "embedding_key"
      embedding_dim = 3
      vocab_list = [2, 3, 4]
      column2 = (
          tf.feature_column.categorical_column_with_vocabulary_list(
              embedding_key, vocab_list
          )
      )
      columns[embedding_key] = tf.feature_column.embedding_column(
          column2, embedding_dim
      )
      state_tensors[embedding_key] = tf.expand_dims([3, 2, 2, 4, 3], -1)
      state_specs[embedding_key] = tensor_spec.TensorSpec([1], tf.int32)
      expected_dim += embedding_dim
  
      numeric_key = "numeric_key"
      batch_size = 5
      state_dims = 3
      input_shape = (batch_size, state_dims)
      columns[numeric_key] = tf.feature_column.numeric_column(
          numeric_key, [state_dims]
      )
      state_tensors[numeric_key] = tf.ones(input_shape, tf.int32)
      state_specs[numeric_key] = tensor_spec.TensorSpec(
          [state_dims], tf.int32
      )
      expected_dim += state_dims
  
      num_actions = 4
      action_spec = tensor_spec.BoundedTensorSpec(
          [1], tf.int32, 0, num_actions - 1
      )
      dense_features = tf.compat.v2.keras.layers.DenseFeatures(
          columns.values()
      )
      online_network = q_network.QNetwork(
          state_specs,
          action_spec,
          preprocessing_combiner=dense_features,
      )
      target_network = online_network.copy(name="TargetNetwork")
      q_online, _ = online_network(state_tensors)
      q_target, _ = target_network(state_tensors)
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.evaluate(tf.compat.v1.initializers.tables_initializer())
  
      expected_shape = (batch_size, num_actions)
      self.assertEqual(expected_shape, q_online.shape)
      self.assertEqual(expected_shape, q_target.shape)
      self.assertAllClose(q_online, q_target, rtol=1.0, atol=1.0)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import gin
  import tensorflow
  from tf_agents.networks import q_network
  from tf_agents.specs import tensor_spec
label_desc: Use image node_id 11 for calling the SingleObservationSingleActionTest obj's underlying member method code with example usage: obj.testCombinedFeatureColumnInput() without return types