self = <tests.test_extensions.test_sklearn_extension.test_sklearn_extension.TestSklearnExtensionRunFunctions testMethod=test_run_model_on_task>
    def test_run_model_on_task(self):
        class MyDummy(sklearn.dummy.DummyClassifier):
            pass
        task = openml.tasks.get_task(1)
>       openml.runs.run_model_on_task(MyDummy(), task)
/home/travis/build/openml/openml-python/tests/test_extensions/test_sklearn_extension/test_sklearn_extension.py:1226: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/home/travis/build/openml/openml-python/openml/runs/functions.py:106: in run_model_on_task
    upload_flow=upload_flow,
/home/travis/build/openml/openml-python/openml/runs/functions.py:222: in run_flow_on_task
    add_local_measures=add_local_measures,
/home/travis/build/openml/openml-python/openml/runs/functions.py:446: in _run_task_get_arffcontent
    X_test=test_x,
/home/travis/build/openml/openml-python/openml/extensions/sklearn/extension.py:1248: in _run_model_on_fold
    pred_y = model_copy.predict(X_test)
/home/travis/miniconda/envs/testenv/lib/python3.6/site-packages/sklearn/dummy.py:174: in predict
    X = check_array(X, accept_sparse=['csr', 'csc', 'coo'])
/home/travis/miniconda/envs/testenv/lib/python3.6/site-packages/sklearn/utils/validation.py:407: in check_array
    _assert_all_finite(array)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
X = array([[nan,  0.,  1., ...,  0.,  0., nan],
       [ 8.,  0.,  1., ..., nan,  0., nan],
       [ 8.,  0.,  1., ..., na...nan,  0., nan],
       [nan,  0., nan, ..., nan,  0., nan],
       [ 8.,  0.,  0., ..., nan,  0., nan]], dtype=float32)
    def _assert_all_finite(X):
        """Like assert_all_finite, but only for ndarray."""
        X = np.asanyarray(X)
        # First try an O(n) time, O(1) space solution for the common case that
        # everything is finite; fall back to O(n) space np.isfinite to prevent
        # false positives from overflow in sum method.
        if (X.dtype.char in np.typecodes['AllFloat'] and not np.isfinite(X.sum())
                and not np.isfinite(X).all()):
            raise ValueError("Input contains NaN, infinity"
>                            " or a value too large for %r." % X.dtype)
E           ValueError: Input contains NaN, infinity or a value too large for dtype('float32').
/home/travis/miniconda/envs/testenv/lib/python3.6/site-packages/sklearn/utils/validation.py:58: ValueError