code: def test_basic(self, output_distribution):
      rs = da.random.RandomState(0)
      a = dpp.QuantileTransformer(
          output_distribution=output_distribution
      )
      b = spp.QuantileTransformer(
          output_distribution=output_distribution
      )
  
      X = rs.uniform(size=(1000, 3), chunks=50)
      a.fit(X)
      b.fit(X)
      assert_estimator_equal(a, b, atol=0.02)
  
      # set the quantiles, so that from here out, we're exact
      a.quantiles_ = b.quantiles_
      assert_eq_ar(a.transform(X), b.transform(X), atol=1e-7)
      assert_eq_ar(X, a.inverse_transform(a.transform(X)))
  
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 1 for calling the TestQuantileTransformer obj's underlying member method code with example usage: obj.test_basic(output_distribution) without return types