code: def _get_multi_labels_and_problematic_images(
      dl_manager: tfds.download.DownloadManager,
  ):
      """Returns multi-labels and problematic images from download json.
  
      Args:
        dl_manager: tfds.download.DownloadManager for downloading the json file
  
      Returns:
        val_annotated_images: Dictionary mapping image name to an inner dictionary
          containing the multi_label annotations for that image. The inner multi-
          label annotation dictionary has keys 'correct', 'wrong', or 'unclear'
          (keys will be missing if the image does not have a set of labels of the
          given type) and values that are lists of wnids.
        problematic_images: List of image names for problematic images.
        imagenet_m_2022:  List of image names comprising ImageNet-M 2022 evaluation
          slice.
      """
      with tf.io.gfile.GFile(
          dl_manager.download(_MULTI_LABELS_URL), "r"
      ) as f:
          human_accuracy_data = json.load(f)
      val_annotated_images = {}
      prefix = "ILSVRC2012_val_"
      len_prefix = len(prefix)
      for image_name in human_accuracy_data["initial_annots"].keys():
          if image_name[:len_prefix] == prefix:
              val_annotated_images[image_name] = human_accuracy_data[
                  "initial_annots"
              ][image_name]
  
      problematic_images = list(
          human_accuracy_data["problematic_images"].keys()
      )
      imagenet_m_2022 = human_accuracy_data["imagenet_m"]
      return val_annotated_images, problematic_images, imagenet_m_2022
  
file_path: datasets/tensorflow_datasets/datasets/imagenet2012_multilabel/imagenet2012_multilabel_dataset_builder.py
imports: import json
  import os
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  from tensorflow_datasets.datasets.imagenet2012 import imagenet_common
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling a global function with example usage: _get_multi_labels_and_problematic_images(dl_manager) and returns: val_annotated_images,  problematic_images,  imagenet_m_2022