code: def _images_to_mnist_file(images, filepath):
      assert len(images.shape) == 3
      assert images.dtype == np.uint8
  
      with open(filepath, "wb") as f:
          f.write(int(2051).to_bytes(4, "big"))
          f.write(
              np.array(images.shape)
              .astype(np.int32)
              .byteswap()
              .tobytes()
          )
          f.write(images.tobytes())
  
file_path: analytics-zoo/pyzoo/test/zoo/orca/data/test_write_parquet.py
imports: import tempfile
  import shutil
  import numpy
  import os
  from zoo.orca.data.image.parquet_dataset import ParquetDataset
  from zoo.orca.data.image.parquet_dataset import _write_ndarrays, write_from_directory, write_parquet
  from zoo.orca.data.image.utils import DType, FeatureType, SchemaField
  from zoo.orca.learn.tf.estimator import Estimator
  from zoo.orca.data.image import write_mnist, write_voc
label_desc: Use image node_id 3 for calling a global function with example usage: _images_to_mnist_file(images, filepath) without return types