code: def get_onehot_num_classes(
      labels: list, pred_probs: Optional[np.ndarray] = None
  ) -> Tuple[np.ndarray, int]:
      """Returns OneHot encoding of MultiLabel Data, and number of classes"""
      num_classes = get_num_classes(
          labels=labels, pred_probs=pred_probs
      )
      try:
          y_one = int2onehot(labels, K=num_classes)
      except TypeError:
          raise ValueError(
              "wrong format for labels, should be a list of list[indices], please check the documentation in find_label_issues for further information"
          )
      return y_one, num_classes
  
file_path: cleanlab/cleanlab/internal/multilabel_utils.py
imports: from typing import Tuple, Optional, List
  import numpy
  from cleanlab.internal.util import get_num_classes
label_desc: Use image node_id 3 for calling a global function with example usage: get_onehot_num_classes(labels, pred_probs) and returns: y_one,  num_classes