def METHOD_NAME(self, save_path, model_class, pickle_module, outputs):
    """
    Test model saving and loading without pipeline
    """
    pickle_args = {'pickle_module': pickle_module}
    num_classes = 10
    dataset_size = 10
    image_shape = (2, 100, 100)
    model_config = {
        'classes': num_classes,
        'inputs_shapes': image_shape,
        'output': 'sigmoid'
    }
    model_save = model_class(config=model_config)
    batch_shape = (dataset_size, *image_shape)
    images_array = np.random.random(batch_shape)
    args = (images_array.astype('float32'),)
    kwargs = dict(outputs=outputs)
    saved_predictions = model_save.predict(*args, **kwargs)
    model_save.save(path=save_path, **pickle_args)
    model_load = model_class()
    model_load.load(path=save_path, **pickle_args)
    loaded_predictions = model_load.predict(*args, **kwargs)
    assert (np.concatenate(saved_predictions) == np.concatenate(loaded_predictions)).all()