code: def multilabel_to_multiclass(
      array: Union[List, np.ndarray]
  ) -> np.ndarray:
      array = binarization(array)
      return np.array(
          [np.nonzero(array[i, :])[0][0] for i in range(len(array))]
      )
  
imports: from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple, Type, Union, cast
  import warnings
  import numpy
  import pandas
  from scipy.sparse import spmatrix
  from sklearn.model_selection import train_test_split
  from autosklearn.evaluation.splitter import CustomStratifiedShuffleSplit
label_desc: Use image node_id 3 for calling a global function with example usage: multilabel_to_multiclass(array) and returns: np