def test_log_decorator(self):

        class test_class(object):
            @helpers.log_method_call
            def test_method(self, arg1, arg2, arg3, *args, **kwargs):
                pass

            @classmethod
            @helpers.log_method_call
            def test_classmethod(cls, arg1, arg2, arg3, *args, **kwargs):
                pass

        args = tuple(range(6))
        kwargs = {'kwarg1': 6, 'kwarg2': 7}

        obj = test_class()
        for method_name in ('test_method', 'test_classmethod'):
            data = {'caller': helpers._get_full_class_name(test_class),
                    'method_name': method_name,
                    'args': args,
                    'kwargs': kwargs}

            method = getattr(obj, method_name)
            with mock.patch('logging.Logger.debug') as debug:
                method(*args, **kwargs)
                debug.assert_called_with(mock.ANY, data)
Get the prediction of the test samples from the model and do the
dataset/ETHPy150Open openstack/oslo.log/oslo_log/tests/unit/test_helpers.py/LogHelpersTestCase.test_log_decorator--crossover with--dataset/ETHPy150Open aalto-speech/morfessor/morfessor/evaluation.py/MorfessorEvaluation.evaluate_model