def inverse_transform(self, X):
        names = np.array(self.get_feature_names())
        def get_names(x):
            indices = np.argwhere(x.toarray().flatten() > 0).flatten()
            if len(indices) == 0:
                return []
            else:
                return names[indices]
        return map(lambda x: get_names(x), X)
dataset/ETHPy150Open bizreach/common-ml/commonml/text/custom_dict_vectorizer.py/CustomDictVectorizer.inverse_transform/original