code: def _create_chunk(prefix, random_state):
      """Creates fake dat, cat, and info files with the given prefix."""
      # Create the images.
      image_shape = (
          NUM_IMAGES,
          2,
          96,
          96,
      )  # Data file contains pairs of images.
      images = random_state.randint(256, size=image_shape).astype(
          "uint8"
      )
      write_binary_matrix("%s-dat.mat" % prefix, images)
  
      # Create the class label file.
      class_labels = random_state.choice(range(5), size=(NUM_IMAGES))
      write_binary_matrix(
          "%s-cat.mat" % prefix, class_labels.astype("int32")
      )
  
      # Create the auxiliary info file that contains additional labels.
      info = []
      for values in FACTOR_VALUES:
          info.append(random_state.choice(values, size=(NUM_IMAGES)))
      write_binary_matrix(
          "%s-info.mat" % prefix, np.array(info).T.astype("int32")
      )
  
file_path: datasets/tensorflow_datasets/testing/fake_data_generation/smallnorb.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.testing import test_utils
label_desc: Use image node_id 2 for calling a global function with example usage: _create_chunk(prefix, random_state) without return types