Source code for flwr_datasets.partitioner.natural_id_partitioner
# Copyright 2023 Flower Labs GmbH. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Natural id partitioner class that works with Hugging Face Datasets."""
from typing import Dict
import numpy as np
from tqdm import tqdm
import datasets
from flwr_datasets.common.typing import NDArrayInt
from flwr_datasets.partitioner.partitioner import Partitioner
[docs]class NaturalIdPartitioner(Partitioner):
"""Partitioner for a dataset that can be divided by a column with partition ids.
Parameters
----------
partition_by: str
The name of the column that contains the unique values of partitions.
Examples
--------
"flwrlabs/shakespeare" dataset
>>> from flwr_datasets import FederatedDataset
>>> from flwr_datasets.partitioner import NaturalIdPartitioner
>>>
>>> partitioner = NaturalIdPartitioner(partition_by="character_id")
>>> fds = FederatedDataset(dataset="flwrlabs/shakespeare",
>>> partitioners={"train": partitioner})
>>> partition = fds.load_partition(0)
"sentiment140" (aka Twitter) dataset
>>> from flwr_datasets import FederatedDataset
>>> from flwr_datasets.partitioner import NaturalIdPartitioner
>>>
>>> partitioner = NaturalIdPartitioner(partition_by="user")
>>> fds = FederatedDataset(dataset="sentiment140",
>>> partitioners={"train": partitioner})
>>> partition = fds.load_partition(0)
"""
def __init__(
self,
partition_by: str,
):
super().__init__()
self._partition_id_to_natural_id: Dict[int, str] = {}
self._natural_id_to_partition_id: Dict[str, int] = {}
self._partition_id_to_indices: Dict[int, NDArrayInt] = {}
self._partition_by = partition_by
def _create_int_partition_id_to_natural_id(self) -> None:
"""Create a mapping from int indices to unique client ids from dataset.
Natural ids come from the column specified in `partition_by`.
"""
unique_natural_ids = self.dataset.unique(self._partition_by)
self._partition_id_to_natural_id = dict(
zip(range(len(unique_natural_ids)), unique_natural_ids)
)
def _create_natural_id_to_int_partition_id(self) -> None:
"""Create a mapping from unique client ids from dataset to int indices.
Natural ids come from the column specified in `partition_by`. This object is
inverse of the `self._partition_id_to_natural_id`. This method assumes that
`self._partition_id_to_natural_id` already exist.
"""
self._natural_id_to_partition_id = {
value: key for key, value in self._partition_id_to_natural_id.items()
}
def _create_partition_id_to_indices(self) -> None:
natural_id_to_indices = {} # type: ignore
natural_ids = np.array(self.dataset[self._partition_by])
for index, natural_id in tqdm(
enumerate(natural_ids), desc="Generating partition_id_to_indices"
):
if natural_id not in natural_id_to_indices:
natural_id_to_indices[natural_id] = []
natural_id_to_indices[natural_id].append(index)
self._partition_id_to_indices = {
self._natural_id_to_partition_id[natural_id]: indices
for natural_id, indices in natural_id_to_indices.items()
}
[docs] def load_partition(self, partition_id: int) -> datasets.Dataset:
"""Load a single partition corresponding to a single `partition_id`.
The choice of the partition is based on unique integers assigned to each
natural id present in the dataset in the `partition_by` column.
Parameters
----------
partition_id : int
the index that corresponds to the requested partition
Returns
-------
dataset_partition : Dataset
single dataset partition
"""
if len(self._partition_id_to_natural_id) == 0:
self._create_int_partition_id_to_natural_id()
self._create_natural_id_to_int_partition_id()
if len(self._partition_id_to_indices) == 0:
self._create_partition_id_to_indices()
return self.dataset.select(self._partition_id_to_indices[partition_id])
@property
def num_partitions(self) -> int:
"""Total number of partitions."""
if len(self._partition_id_to_natural_id) == 0:
self._create_int_partition_id_to_natural_id()
self._create_natural_id_to_int_partition_id()
return len(self._partition_id_to_natural_id)
@property
def partition_id_to_natural_id(self) -> Dict[int, str]:
"""Node id to corresponding natural id present.
Natural ids are the unique values in `partition_by` column in dataset.
"""
return self._partition_id_to_natural_id
# pylint: disable=R0201
@partition_id_to_natural_id.setter
def partition_id_to_natural_id(self, value: Dict[int, str]) -> None:
raise AttributeError(
"Setting the partition_id_to_natural_id dictionary is not allowed."
)