flsim/utils/example_utils.py [178:218]:
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    def __init__(self, data_loader):
        self.data_loader = data_loader
        self.train_users = self._create_fl_users(data_loader.fl_train_set())
        self.eval_users = self._create_fl_users(data_loader.fl_eval_set())
        self.test_users = self._create_fl_users(data_loader.fl_test_set())

    def user_ids(self) -> List[int]:
        return list(self.train_users.keys())

    def num_users(self) -> int:
        return len(self.train_users)

    def get_user_data(self, user_index: int) -> IFLUserData:
        if user_index in self.train_users:
            return self.train_users[user_index]
        else:
            raise IndexError(
                f"Index {user_index} is out of bound for list with len {self.num_users()}"
            )

    def train_data(self) -> Iterable[IFLUserData]:
        for user_data in self.train_users.values():
            yield user_data

    def eval_data(self) -> Iterable[Dict[str, torch.Tensor]]:
        for user_data in self.eval_users.values():
            for batch in user_data:
                yield batch

    def test_data(self) -> Iterable[Dict[str, torch.Tensor]]:
        for user_data in self.test_users.values():
            for batch in user_data:
                yield batch

    def _create_fl_users(self, iterator: Iterator) -> Dict[int, IFLUserData]:
        return {
            user_index: UserData(user_data)
            for user_index, user_data in tqdm(
                enumerate(iterator), desc="Creating FL User", unit="user"
            )
        }
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flsim/utils/example_utils.py [409:449]:
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    def __init__(self, data_loader):
        self.data_loader = data_loader
        self.train_users = self._create_fl_users(data_loader.fl_train_set())
        self.eval_users = self._create_fl_users(data_loader.fl_eval_set())
        self.test_users = self._create_fl_users(data_loader.fl_test_set())

    def user_ids(self) -> List[int]:
        return list(self.train_users.keys())

    def num_users(self) -> int:
        return len(self.train_users)

    def get_user_data(self, user_index: int) -> IFLUserData:
        if user_index in self.train_users:
            return self.train_users[user_index]
        else:
            raise IndexError(
                f"Index {user_index} is out of bound for list with len {self.num_users()}"
            )

    def train_data(self) -> Iterable[IFLUserData]:
        for user_data in self.train_users.values():
            yield user_data

    def eval_data(self) -> Iterable[Dict[str, torch.Tensor]]:
        for user_data in self.eval_users.values():
            for batch in user_data:
                yield batch

    def test_data(self) -> Iterable[Dict[str, torch.Tensor]]:
        for user_data in self.test_users.values():
            for batch in user_data:
                yield batch

    def _create_fl_users(self, iterator: Iterator) -> Dict[int, IFLUserData]:
        return {
            user_index: UserData(user_data)
            for user_index, user_data in tqdm(
                enumerate(iterator), desc="Creating FL User", unit="user"
            )
        }
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