code: def test_train_subclassed_base_model_with_label_input(self):
      w, x0, y0, lr, adv_config, _ = self._set_up_linear_regression()
  
      inputs = {"feature": tf.constant(x0), "label": tf.constant(y0)}
  
      class BaseModel(tf.keras.Model):
          def __init__(self):
              super(BaseModel, self).__init__()
              self.dense = tf.keras.layers.Dense(
                  w.shape[-1],
                  use_bias=False,
                  kernel_initializer=tf.keras.initializers.Constant(w),
              )
              self.seen_input_keys = set()
  
          def call(self, inputs):
              self.seen_input_keys |= set(inputs.keys())
              return self.dense(inputs["feature"])
  
      model = BaseModel()
      adv_model = adversarial_regularization.AdversarialRegularization(
          model,
          label_keys=["label"],
          adv_config=adv_config,
          base_with_labels_in_features=True,
      )
      adv_model.compile(
          optimizer=tf.keras.optimizers.SGD(lr),
          loss="MSE",
          metrics=["mae"],
      )
      adv_model.fit(x=inputs, batch_size=1, steps_per_epoch=1)
  
      self.assertIn("label", model.seen_input_keys)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  from absl.testing import parameterized
  import neural_structured_learning.configs
  from neural_structured_learning.keras import adversarial_regularization
  import numpy
  import tensorflow
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 15 for calling the AdversarialRegularizationTest obj's underlying member method code with example usage: obj.test_train_subclassed_base_model_with_label_input() and returns: self