code: def test_targetvalidator_supported_types_noclassification(
      input_data_targettest,
  ):
      y = input_data_targettest
  
      validator = TargetValidator(is_classification=False)
      validator.fit(input_data_targettest)
  
      y_encoded: np.ndarray = validator.transform(y)
  
      # Assert the validator was fitted
      assert validator._is_fitted
  
      # Assert no encoder if is_classification = False
      assert validator.encoder is None
  
      # Assert it returns y_inverse, y_encoded as ndarray
      assert isinstance(y_encoded, np.ndarray)
  
      # Assert the return value is equal to the one passed in
      np.testing.assert_array_equal(y_encoded, y)
  
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 2 for calling a global function with example usage: test_targetvalidator_supported_types_noclassification(input_data_targettest) without return types