code: def test_type_of_target_unsupported(input_data_targettest):
      """
      Makes sure we raise a proper message to the user,
      when providing not supported data input
      """
      validator = TargetValidator()
      with pytest.raises(
          ValueError, match=r"legacy multi-.* data representation."
      ):
          validator.fit(input_data_targettest)
  
imports: import numpy
  import pandas
  import sklearn.datasets
  import sklearn.model_selection
  from pandas.api.types import is_bool_dtype, is_numeric_dtype
  from scipy import sparse
  from sklearn.utils.multiclass import type_of_target
  from autosklearn.data.target_validator import TargetValidator
  import pytest
label_desc: Use image node_id 10 for calling a global function with example usage: test_type_of_target_unsupported(input_data_targettest) without return types