source_code/SegMamba/monai/fl/client/client_algo.py

# Copyright (c) MONAI Consortium
# 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.

from __future__ import annotations

from monai.fl.utils.exchange_object import ExchangeObject


class BaseClient:
    """
    Provide an abstract base class to allow the client to return summary statistics of the data.

    To define a new stats script, subclass this class and implement the
    following abstract methods::

        - self.get_data_stats()

    initialize(), abort(), and finalize() -- inherited from `ClientAlgoStats`; can be optionally be implemented
    to help with lifecycle management of the class object.
    """

    def initialize(self, extra: dict | None = None) -> None:
        """
        Call to initialize the ClientAlgo class.

        Args:
            extra: optional extra information, e.g. dict of `ExtraItems.CLIENT_NAME` and/or `ExtraItems.APP_ROOT`.
        """
        pass

    def finalize(self, extra: dict | None = None) -> None:
        """
        Call to finalize the ClientAlgo class.

        Args:
            extra: Dict with additional information that can be provided by the FL system.
        """
        pass

    def abort(self, extra: dict | None = None) -> None:
        """
        Call to abort the ClientAlgo training or evaluation.

        Args:
            extra: Dict with additional information that can be provided by the FL system.
        """

        pass


class ClientAlgoStats(BaseClient):

    def get_data_stats(self, extra: dict | None = None) -> ExchangeObject:
        """
        Get summary statistics about the local data.

        Args:
            extra: Dict with additional information that can be provided by the FL system.
                For example, requested statistics.

        Returns:

            ExchangeObject: summary statistics.

        Extra dict example::

            requested_stats = {
                FlStatistics.STATISTICS: metrics,
                FlStatistics.NUM_OF_BINS: num_of_bins,
                FlStatistics.BIN_RANGES: bin_ranges
            }

        Returned ExchangeObject example::

            ExchangeObject(
                statistics = {...}
            )

        """
        raise NotImplementedError(f"Subclass {self.__class__.__name__} must implement this method.")


class ClientAlgo(ClientAlgoStats):
    """
    Provide an abstract base class for defining algo to run on any platform.
    To define a new algo script, subclass this class and implement the
    following abstract methods:

        - self.train()
        - self.get_weights()
        - self.evaluate()
        - self.get_data_stats() (optional, inherited from `ClientAlgoStats`)

    initialize(), abort(), and finalize() - inherited from `ClientAlgoStats` - can be optionally be implemented
    to help with lifecycle management of the class object.
    """

    def train(self, data: ExchangeObject, extra: dict | None = None) -> None:
        """
        Train network and produce new network from train data.

        Args:
            data: ExchangeObject containing current network weights to base training on.
            extra: Dict with additional information that can be provided by the FL system.

        Returns:
            None
        """
        raise NotImplementedError(f"Subclass {self.__class__.__name__} must implement this method.")

    def get_weights(self, extra: dict | None = None) -> ExchangeObject:
        """
        Get current local weights or weight differences.

        Args:
            extra: Dict with additional information that can be provided by the FL system.

        Returns:
            ExchangeObject: current local weights or weight differences.

        `ExchangeObject` example:

        .. code-block:: python

            ExchangeObject(
                weights = self.trainer.network.state_dict(),
                optim = None,  # could be self.optimizer.state_dict()
                weight_type = WeightType.WEIGHTS
            )

        """
        raise NotImplementedError(f"Subclass {self.__class__.__name__} must implement this method.")

    def evaluate(self, data: ExchangeObject, extra: dict | None = None) -> ExchangeObject:
        """
        Get evaluation metrics on test data.

        Args:
            data: ExchangeObject with network weights to use for evaluation.
            extra: Dict with additional information that can be provided by the FL system.

        Returns:
            metrics: ExchangeObject with evaluation metrics.
        """
        raise NotImplementedError(f"Subclass {self.__class__.__name__} must implement this method.")