code: def testEmbeddingFeatureColumnInput(self):
      key = "feature_key"
      vocab_list = ["a", "b"]
      column = (
          tf.feature_column.categorical_column_with_vocabulary_list(
              key, vocab_list
          )
      )
      column = tf.feature_column.embedding_column(column, 3)
      feature_tensor = tf.convert_to_tensor(["a", "b", "c", "a", "c"])
      state = {key: tf.expand_dims(feature_tensor, -1)}
      state_spec = {key: tensor_spec.TensorSpec([1], tf.string)}
  
      dense_features = tf.compat.v2.keras.layers.DenseFeatures([column])
      online_network = q_network.QNetwork(
          input_tensor_spec=state_spec,
          action_spec=tensor_spec.BoundedTensorSpec(
              [1], tf.int32, 0, 1
          ),
          preprocessing_combiner=dense_features,
      )
      target_network = online_network.copy(name="TargetNetwork")
      q_online, _ = online_network(state)
      q_target, _ = target_network(state)
      self.evaluate(tf.compat.v1.global_variables_initializer())
      self.evaluate(tf.compat.v1.initializers.tables_initializer())
      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 10 for calling the SingleObservationSingleActionTest obj's underlying member method code with example usage: obj.testEmbeddingFeatureColumnInput() without return types