code: def test_featurevalidator_unsupported_numpy(input_data_featuretest):
      validator = FeatureValidator()
      with pytest.raises(
          ValueError,
          match=r".*When providing a numpy array.*not supported.",
      ):
          validator.fit(input_data_featuretest)
  
imports: import numpy
  import pandas
  import sklearn.datasets
  import sklearn.model_selection
  from pandas.api.types import is_categorical_dtype, is_numeric_dtype, is_string_dtype
  from scipy import sparse
  from autosklearn.data.feature_validator import FeatureValidator
  import pytest
label_desc: Use image node_id 3 for calling a global function with example usage: test_featurevalidator_unsupported_numpy(input_data_featuretest) without return types