sklearn_wrapper.py 文件源码

def _check_X_y(self, X, y=None):
        #print('check_X_y', type(X), type(y))
        if not is_dataset(X) and not isinstance(X, list):
            if isinstance(X, numpy.ndarray):
                X = check_array(X, dtype=self._data_x_dtype)
            else:
                print('[WARNING] skip check type for dataset X with type {}'
                      .format(type(X)))
        if y is not None:
            y = check_array(y, dtype=self._data_y_dtype, ensure_2d=False)
        return X, y