code: def test_label_binarize_multiclass():
      y = [0, 1, 2]
      classes = [0, 1, 2]
      pos_label = 2
      neg_label = 0
      expected = 2 * np.eye(3)
  
      check_binarized_results(
          y, classes, pos_label, neg_label, expected
      )
  
      with pytest.raises(ValueError):
          label_binarize(
              y,
              classes=classes,
              neg_label=-1,
              pos_label=pos_label,
              sparse_output=True,
          )
  
imports: import numpy
  import pytest
  from scipy.sparse import issparse
  from sklearn import datasets
  from sklearn.preprocessing._label import LabelBinarizer, LabelEncoder, MultiLabelBinarizer, _inverse_binarize_multiclass, _inverse_binarize_thresholding, label_binarize
  from sklearn.utils import _to_object_array
  from sklearn.utils._testing import assert_array_equal, ignore_warnings
  from sklearn.utils.fixes import COO_CONTAINERS, CSC_CONTAINERS, CSR_CONTAINERS, DOK_CONTAINERS, LIL_CONTAINERS
  from sklearn.utils.multiclass import type_of_target
label_desc: Use image node_id 27 for calling a global function with example usage: test_label_binarize_multiclass() without return types