code: def test_normalize_image_and_label_with_one_hot(self):
      self.setup_normalize_img_and_label()
      num_classes = 10
      expected_label = tf.convert_to_tensor(
          [0, 0, 0, 0, 1, 0, 0, 0, 0, 0], dtype=tf.dtypes.int8
      )
      result_img, result_label = models.normalize_img_and_label(
          self.big_img,
          self.label,
          self.image_size,
          self.width_ratio,
          num_classes,
          True,
      )
      self.assertEqual(result_img.shape, self.expected_img_shape)
      self.assertTrue((result_label == expected_label).numpy().all())
  
imports: import os
  import uuid
  from absl.testing import absltest
  import mock
  import tensorflow
  from tensorflow_cloud.core import machine_config
  from tensorflow_cloud.core import run
  from tensorflow_cloud.core.experimental import models
  from official.legacy.image_classification.efficientnet import efficientnet_model
label_desc: Use image node_id 12 for calling the ModelsTest obj's underlying member method code with example usage: obj.test_normalize_image_and_label_with_one_hot() without return types