code: def extract_images(f):
      """Extract the images into a 4D uint8 np array [index, y, x, depth].
  
      Args:
        f: A file object that can be passed into a gzip reader.
  
      Returns:
        data: A 4D uint8 np array [index, y, x, depth].
  
      Raises:
        ValueError: If the bytestream does not start with 2051.
      """
      tf.logging.info("Extracting", f.name)
      with gzip.GzipFile(fileobj=f) as bytestream:
          magic = _read32(bytestream)
          if magic != 2051:
              raise ValueError(
                  "Invalid magic number %d in MNIST image file: %s"
                  % (magic, f.name)
              )
          num_images = _read32(bytestream)
          rows = _read32(bytestream)
          cols = _read32(bytestream)
          buf = bytestream.read(rows * cols * num_images)
          data = np.frombuffer(buf, dtype=np.uint8)
          data = data.reshape(num_images, rows, cols, 1)
          return data
  
file_path: magenta/magenta/models/latent_transfer/local_mnist.py
imports: import gzip
  import os
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling a global function with example usage: extract_images(f) and returns: data