code: def checker(data, dist_type):
      transformer = FloatTransformer()
      transformed = transformer.fit_transform(data)
      assert isinstance(transformed, ndarray)
      assert issubdtype(transformed.dtype, float)
      assert transformer.dist_type_ == dist_type
  
      original = transformer.inverse_transform(transformed)
      print(original)
      is_equal = original == data
      assert (
          isinstance(is_equal, bool)
          and is_equal
          or isinstance(is_equal, ndarray)
          and is_equal.all()
          or isinstance(is_equal, Series)
          and is_equal.all()
          or isinstance(is_equal, DataFrame)
          and is_equal.all().all()
      )
  
imports: from fairlearn.adversarial._preprocessor import FloatTransformer
  import pytest
  from pandas import DataFrame, Series
  from numpy import ndarray, asarray, issubdtype
  from fairlearn.datasets import fetch_adult
label_desc: Use image node_id 2 for calling a global function with example usage: checker(data, dist_type) without return types