def assertInvalidVectorTrain(self, network, input_vector, target=None,
                                 decimal=5, is_feature1d=True, **train_kwargs):
        input_vectors = vectors_for_testing(input_vector, is_feature1d)

        if target is not None:
            target_vectors = vectors_for_testing(target, is_feature1d)
            input_vectors = zip(input_vectors, target_vectors)

        train_args = inspect.getargspec(network.train).args

        if 'epochs' in train_args and 'epochs' not in train_kwargs:
            train_kwargs['epochs'] = 5

        elif 'epsilon' in train_args and 'epsilon' not in train_kwargs:
            train_kwargs['epsilon'] = 0.1

        for i, input_data in enumerate(input_vectors, start=1):
            if target is None:
                network.train(input_data, **train_kwargs)
            else:
                network.train(*input_data, **train_kwargs)
Method helps test network prediction training using different
dataset/ETHPy150Open itdxer/neupy/tests/base.py/BaseTestCase.assertInvalidVectorTrain