code: def test_invalid_input_label_binarize(setup):
      with pytest.raises(ValueError):
          label_binarize(
              [0, 2], classes=[0, 2], pos_label=0, neg_label=1
          )
      with pytest.raises(
          ValueError, match="continuous target data is not "
      ):
          label_binarize([1.2, 2.7], classes=[0, 1])
      with pytest.raises(ValueError, match="mismatch with the labels"):
          label_binarize([[1, 3]], classes=[1, 2, 3])
  
imports: import numpy
  import pytest
  import scipy.sparse
  from sklearn.preprocessing._label import _inverse_binarize_thresholding
  from sklearn.preprocessing._label import _inverse_binarize_multiclass
  from sklearn.utils._testing import assert_array_equal, ignore_warnings
  from sklearn.utils.multiclass import type_of_target
  from ....None import tensor
  from ..None import LabelBinarizer, label_binarize, LabelEncoder
label_desc: Use image node_id 10 for calling a global function with example usage: test_invalid_input_label_binarize(setup) without return types