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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _load_objects(csv_paths, csv_positions, prefix):
 """Returns objects listed within given CSV files."""

  logging.info('Loading CSVs %s from positions %s with prefix %s',
               csv_paths, csv_positions, prefix)
  objects = collections.defaultdict(list)
  for i, labels_path in enumerate(csv_paths):
    with tf.io.gfile.GFile(labels_path) as csv_f:
      if csv_positions[i] > 0:
        csv_f.seek(csv_positions[i])
      else:
        csv_f.readline()  # Drop headers
      reader = csv.reader(csv_f)
      for image_id, source, label, confidence in reader:
        if prefix and image_id[0] != prefix:
          break
        csv_positions[i] = csv_f.tell()
        image_id = int(image_id, 16)
        current_obj = _Object(label, int(float(confidence) * 10), source)
        objects[image_id].append(current_obj)
  return dict(objects)