code: def _generate_data():
      """Generates training archives for both train and valiation."""
      output_dir = os.path.join(
          FLAGS.tfds_dir,
          "testing",
          "test_data",
          "fake_examples",
          "imagenet_resized",
      )
  
      train = {}
      train["data"] = np.zeros(shape=[3, 8, 8, 3], dtype=np.uint8)
      train["labels"] = np.zeros(shape=[3], dtype=np.int64)
  
      _write_zipped(
          output_dir,
          train,
          "Imagenet8_train.npz",
          "Imagenet8_train_npz.zip",
      )
  
      valid = {}
      valid["data"] = np.ones(shape=[1, 8, 8, 3], dtype=np.uint8)
      valid["labels"] = np.ones(shape=[1], dtype=np.int64)
  
      _write_zipped(
          output_dir,
          valid,
          "Imagenet8_val.npz",
          "Imagenet8_val_npz.zip",
      )
  
file_path: datasets/tensorflow_datasets/testing/fake_data_generation/imagenet_resized.py
imports: import os
  import zipfile
  from absl import app
  from absl import flags
  import numpy
  from tensorflow_datasets.core import utils
label_desc: Use image node_id 2 for calling a global function with example usage: _generate_data() without return types