code: def _generate_images():
      """Generates training images."""
      names_file = tfds.core.tfds_path(
          caltech._LABELS_FNAME
      )  # pylint: disable=protected-access
      label_names = tfds.features.ClassLabel(
          names_file=names_file
      ).names[:NUM_CLASSES]
      for label in label_names:
          for i in range(IMAGES_PER_CLASS):
              height = np.random.randint(
                  low=MIN_EDGE_LENGTH, high=MAX_EDGE_LENGTH
              )
              width = np.random.randint(
                  low=MIN_EDGE_LENGTH, high=MAX_EDGE_LENGTH
              )
              jpeg = _get_jpeg(height=height, width=width)
              _save_image(jpeg, label, i + 1)
  
file_path: datasets/tensorflow_datasets/testing/fake_data_generation/caltech.py
imports: import os
  from absl import app
  from absl import flags
  import numpy
  from tensorflow_datasets.core import utils
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  from tensorflow_datasets.image_classification import caltech
  import tensorflow_datasets.public_api
  from tensorflow_datasets.testing import fake_data_utils
label_desc: Use image node_id 4 for calling a global function with example usage: _generate_images() without return types