code: def testNumericFeatureColumnInput(self):
      key = "feature_key"
      batch_size = 3
      state_dims = 5
      column = tf.feature_column.numeric_column(key, [state_dims])
      state = {key: tf.ones([batch_size, state_dims], tf.int32)}
      state_spec = {key: tensor_spec.TensorSpec([state_dims], tf.int32)}
  
      dense_features = tf.compat.v2.keras.layers.DenseFeatures([column])
      online_network = (
          heteroscedastic_q_network.HeteroscedasticQNetwork(
              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)[0].q_value_logits
      q_target = target_network(state)[0].q_value_logits
      self.evaluate(tf.compat.v1.global_variables_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 math
  import gin
  import tensorflow
  from tf_agents.bandits.networks import heteroscedastic_q_network
  from tf_agents.specs import tensor_spec
label_desc: Use image node_id 8 for calling the SingleObservationSingleActionTest obj's underlying member method code with example usage: obj.testNumericFeatureColumnInput() without return types