Source code for flwr.client.client

# Copyright 2020 Adap 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.
# ==============================================================================
"""Flower client (abstract base class)."""


from abc import ABC, abstractmethod

from flwr.common import EvaluateIns, EvaluateRes, FitIns, FitRes, ParametersRes


[docs]class Client(ABC): """Abstract base class for Flower clients."""
[docs] @abstractmethod def get_parameters(self) -> ParametersRes: """Return the current local model parameters. Returns: ParametersRes: The current local model parameters. """
[docs] @abstractmethod def fit(self, ins: FitIns) -> FitRes: """Refine the provided weights using the locally held dataset. Args: ins (FitIns): The training instructions containing (global) model parameters received from the server and a dictionary of configuration values used to customize the local training process. Returns: FitRes: The training result containing updated parameters and other details such as the number of local training examples used for training. """
[docs] @abstractmethod def evaluate(self, ins: EvaluateIns) -> EvaluateRes: """Evaluate the provided weights using the locally held dataset. Args: ins (EvaluateIns): The evaluation instructions containing (global) model parameters received from the server and a dictionary of configuration values used to customize the local evaluation process. Returns: EvaluateRes: The evaluation result containing the loss on the local dataset and other details such as the number of local data examples used for evaluation. """