def _load_raw_user_info(self):
        """In MovieLens, the user attributes file have the following formats:

        ml-100k:
        user id | age | gender | occupation | zip code

        ml-1m:
        UserID::Gender::Age::Occupation::Zip-code

        For ml-10m, there is no user information. We read the user id from the rating file.

        Parameters
        ----------
        name : str

        Returns
        -------
        user_info : pd.DataFrame
        """
        if self._name == "ml-100k":
            self.user_info = pd.read_csv(
                os.path.join(self._dir, "u.user"),
                sep="|",
                header=None,
                names=["id", "age", "gender", "occupation", "zip_code"],
                engine="python",
            )
        elif self._name == "ml-1m":
            self.user_info = pd.read_csv(
                os.path.join(self._dir, "users.dat"),
                sep="::",
                header=None,
                names=["id", "gender", "age", "occupation", "zip_code"],
                engine="python",
            )
        elif self._name == "ml-10m":
            rating_info = pd.read_csv(
                os.path.join(self._dir, "ratings.dat"),
                sep="::",
                header=None,
                names=["user_id", "movie_id", "rating", "timestamp"],
                dtype={
                    "user_id": np.int32,
                    "movie_id": np.int32,
                    "ratings": np.float32,
                    "timestamp": np.int64,
                },
                engine="python",
            )
            self.user_info = pd.DataFrame(
                np.unique(rating_info["user_id"].values.astype(np.int32)),
                columns=["id"],
            )
        else:
            raise NotImplementedError
In MovieLens, the user attributes file have the following formats:

        ml-100k:
        user id | age | gender | occupation | zip code

        ml-1m:
        UserID::Gender::Age::Occupation::Zip-code

        For ml-10m, there is no user information. We read the user id from the rating file.

        Parameters
        ----------
        name : str

        Returns
        -------
        user_info : pd.DataFrame
        
examples/pytorch/gcmc/data.py