code: def test_kneighbors_multioutput_regressor(self):
      for n_targets in [1, 2, 7]:
          X, y = datasets.make_regression(
              n_samples=1000,
              n_features=10,
              n_informative=5,
              n_targets=n_targets,
              random_state=1,
              noise=0.5,
          )
          model = KNeighborsRegressor()
          model.fit(X, y)
  
          extra_config = {
              hummingbird.ml.operator_converters.constants.BATCH_SIZE: X.shape[
                  0
              ]
          }
          torch_model = hummingbird.ml.convert(
              model, "torch", extra_config=extra_config
          )
          self.assertTrue(torch_model is not None)
          np.testing.assert_allclose(
              model.predict(X),
              torch_model.predict(X),
              rtol=1e-5,
              atol=1e-5,
          )
  
imports: import unittest
  from packaging.version import Version, parse
  import numpy
  import sklearn
  import torch
  from sklearn.neighbors import KNeighborsClassifier, KNeighborsRegressor
  from sklearn import datasets
  import hummingbird.ml
label_desc: Use image node_id 27 for calling the TestSklearnKNeighbors obj's underlying member method code with example usage: obj.test_kneighbors_multioutput_regressor() without return types