code: def generate_cifar10_batch(batch_name):
      images = np.random.randint(
          256,
          size=(NUMBER_IMAGES_PER_BATCH, HEIGHT * WIDTH * 3),
          dtype=np.uint8,
      )
      labels = np.random.randint(
          NUMBER_LABELS, size=(NUMBER_IMAGES_PER_BATCH), dtype=np.uint8
      )
      dump(cifar10_output_dir(), batch_name, images, labels)
  
file_path: datasets/tensorflow_datasets/testing/fake_data_generation/cifar.py
imports: import os
  from absl import app
  from absl import flags
  import numpy
  import tensorflow_datasets
  from tensorflow_datasets.core import utils
  from tensorflow_datasets.testing import test_utils
label_desc: Use image node_id 5 for calling a global function with example usage: generate_cifar10_batch(batch_name) without return types