code: def test_fit(self):
      labels = np.argmax(self.y_test_mnist, axis=1)
      classifier = get_image_classifier_kr_tf()
  
      acc = (
          np.sum(
              np.argmax(classifier.predict(self.x_test_mnist), axis=1)
              == labels
          )
          / NB_TEST
      )
      logger.info("Accuracy: %.2f%%", (acc * 100))
  
      classifier.fit(
          self.x_train_mnist,
          self.y_train_mnist,
          batch_size=BATCH_SIZE,
          nb_epochs=2,
      )
      acc2 = (
          np.sum(
              np.argmax(classifier.predict(self.x_test_mnist), axis=1)
              == labels
          )
          / NB_TEST
      )
      logger.info("Accuracy: %.2f%%", (acc2 * 100))
  
      self.assertEqual(acc, 0.32)
      self.assertEqual(acc2, 0.77)
  
      classifier.fit(
          self.x_train_mnist,
          y=self.y_train_mnist,
          batch_size=BATCH_SIZE,
          nb_epochs=2,
      )
      classifier.fit(
          x=self.x_train_mnist,
          y=self.y_train_mnist,
          batch_size=BATCH_SIZE,
          nb_epochs=2,
      )
  
file_path: adversarial-robustness-toolbox/tests/estimators/classification/test_input_filter.py
imports: import logging
  import unittest
  import numpy
  from tests.utils import TestBase, master_seed, get_image_classifier_kr_tf
label_desc: Use image node_id 3 for calling the TestInputFilter obj's underlying member method code with example usage: obj.test_fit() without return types