code: def test_type_override_quantile(self) -> None:
      # Take a feature that should be identified as CONTINUOUS
      feature_value_map = read_data()
      probability_values = feature_value_map[BOXCOX_FEATURE_ID]
  
      # And ask for a QUANTILE anyways
      parameter = normalization.identify_parameter(
          "_", probability_values, feature_type=identify_types.QUANTILE
      )
      self.assertEqual(parameter.feature_type, "QUANTILE")
  
imports: import unittest
  import numpy
  import numpy.testing
  import six
  import torch
  from reagent.preprocessing import identify_types, normalization, transforms
  from reagent.preprocessing.identify_types import BOXCOX, CONTINUOUS, DO_NOT_PREPROCESS, ENUM
  from reagent.preprocessing.normalization import MISSING_VALUE, NormalizationParameters, sort_features_by_normalization
  from reagent.preprocessing.preprocessor import Preprocessor
  from reagent.test.base.utils import NumpyFeatureProcessor
  from reagent.test.preprocessing.preprocessing_util import BOXCOX_FEATURE_ID, CONTINUOUS_FEATURE_ID, CONTINUOUS_SMALL_FEATURE_ID, ENUM_FEATURE_ID, id_to_type, PROBABILITY_FEATURE_ID, read_data
  from scipy import special
label_desc: Use image node_id 10 for calling the TestPreprocessing obj's underlying member method code with example usage: obj.test_type_override_quantile() without return types