code: def test_input_types(self, dask_df, pandas_df):
      a = dpp.StandardScaler()
      b = spp.StandardScaler()
  
      assert_estimator_equal(
          a.fit(dask_df.values),
          a.fit(dask_df),
      )
  
      assert_estimator_equal(
          a.fit(dask_df),
          b.fit(pandas_df),
          exclude="n_samples_seen_",
      )
  
      assert_estimator_equal(
          a.fit(dask_df.values),
          b.fit(pandas_df),
          exclude={"n_samples_seen_", "feature_names_in_"},
      )
  
      assert_estimator_equal(
          a.fit(dask_df),
          b.fit(pandas_df.values),
          exclude={"n_samples_seen_", "feature_names_in_"},
      )
  
      assert_estimator_equal(
          a.fit(dask_df.values),
          b.fit(pandas_df.values),
          exclude="n_samples_seen_",
      )
  
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 TestStandardScaler obj's underlying member method code with example usage: obj.test_input_types(dask_df, pandas_df) without return types