code: def test_image_dataset_from_directory_no_labels(self):
      # Test retrieving images without labels from a directory and its
      # subdirs.
  
      # Save a few extra images in the parent directory.
      directory = self._prepare_directory(count=7, num_classes=2)
      for i, img in enumerate(self._get_images(3)):
          filename = f"image_{i}.jpg"
          img.save(os.path.join(directory, filename))
  
      dataset = image_dataset_utils.image_dataset_from_directory(
          directory, batch_size=5, image_size=(18, 18), labels=None
      )
      if backend.config.image_data_format() == "channels_last":
          output_shape = [5, 18, 18, 3]
      else:
          output_shape = [5, 3, 18, 18]
      self.assertEqual(dataset.class_names, None)
      batch = next(iter(dataset))
      # We return plain images
      self.assertEqual(batch.shape, output_shape)
      self.assertEqual(batch.dtype.name, "float32")
      # Count samples
      batch_count = 0
      sample_count = 0
      for batch in dataset:
          batch_count += 1
          sample_count += batch.shape[0]
      self.assertEqual(batch_count, 2)
      self.assertEqual(sample_count, 10)
  
imports: import os
  import numpy
  from keras import backend
  from keras import testing
  from keras.utils import image_dataset_utils
  from keras.utils import image_utils
  from keras.utils.module_utils import tensorflow
label_desc: Use image node_id 3 for calling the ImageDatasetFromDirectoryTest obj's underlying member method code with example usage: obj.test_image_dataset_from_directory_no_labels() without return types