code: def test_input_types(self):
      a = dpp.PolynomialFeatures()
      b = spp.PolynomialFeatures()
  
      assert_estimator_equal(
          a.fit(df), a.fit(df.compute()), exclude={"n_input_features_"}
      )
      assert_estimator_equal(
          a.fit(df),
          a.fit(df.compute().values),
          exclude={"n_input_features_", "feature_names_in_"},
      )
      assert_estimator_equal(
          a.fit(df.values),
          a.fit(df.compute().values),
          exclude={"n_input_features_"},
      )
      assert_estimator_equal(
          a.fit(df), b.fit(df.compute()), exclude={"n_input_features_"}
      )
      assert_estimator_equal(
          a.fit(df),
          b.fit(df.compute().values),
          exclude={"n_input_features_", "feature_names_in_"},
      )
  
imports: from copy import copy
  import dask
  import dask.array
  import dask.dataframe
  import numpy
  import pandas
  import pandas.testing
  import pytest
  import sklearn.preprocessing
  from dask import compute
  from dask.array.utils import assert_eq
  from dask.dataframe.utils import assert_eq
  from pandas.api.types import is_categorical_dtype, is_object_dtype
  from sklearn.exceptions import NotFittedError
  import dask_ml.preprocessing
  from dask_ml.datasets import make_classification
  from dask_ml.utils import assert_estimator_equal
label_desc: Use image node_id 2 for calling the TestPolynomialFeatures obj's underlying member method code with example usage: obj.test_input_types() without return types