code: def load_image_level_labels(filepath):
      """Returns a dictionary mapping image IDs to a list of image-level labels."""
      image2labels = collections.defaultdict(list)
      with tf.io.gfile.GFile(filepath, "r") as csvfile:
          reader = csv.reader(csvfile)
          next(reader)  # Skip header.
          for row in reader:
              if len(row) == 3:
                  image_id, label, confidence = row
                  source = "verification"
              elif len(row) == 4:
                  image_id, source, label, confidence = row
              image2labels[image_id].append(
                  (label, source, float(confidence))
              )
      return image2labels
  
imports: import collections
  import csv
  import io
  import json
  import os
  from absl import logging
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling a global function with example usage: load_image_level_labels(filepath) and returns: image2labels