code: def _get_vqa_v2_annotations(
      directory, annotation_url, annotation_filename="vqa_v2.tar.gz"
  ):
      """Extract the VQA V2 annotation files to directory unless it's there."""
      annotation_file = generator_utils.maybe_download_from_drive(
          directory, annotation_filename, annotation_url
      )
      with tarfile.open(annotation_file, "r:gz") as annotation_tar:
          annotation_tar.extractall(directory)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import base64
  import csv
  import json
  import os
  import random
  import sys
  import tarfile
  import zipfile
  import numpy
  from tensor2tensor.data_generators import generator_utils
  from tensor2tensor.data_generators import image_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.data_generators import text_encoder
  from tensor2tensor.data_generators import vqa_utils
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import metrics
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling a global function with example usage: _get_vqa_v2_annotations(directory, annotation_url, annotation_filename) without return types