Source code for nvflare.app_opt.pt.job_config.fed_avg

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from typing import List, Optional, Union

import torch.nn as nn

from nvflare.app_common.widgets.convert_to_fed_event import ConvertToFedEvent
from nvflare.app_common.workflows.fedavg import FedAvg
from nvflare.app_opt.pt.job_config.base_fed_job import BaseFedJob


[docs] class FedAvgJob(BaseFedJob): def __init__( self, initial_model: nn.Module, n_clients: int, num_rounds: int, name: str = "fed_job", min_clients: int = 1, mandatory_clients: Optional[List[str]] = None, key_metric: str = "accuracy", convert_to_fed_event: Union[bool, ConvertToFedEvent, None] = None, analytics_receiver: Union[bool, ConvertToFedEvent, None] = None, ): """PyTorch FedAvg Job. Configures server side FedAvg controller, persistor with initial model, and widgets. User must add executors. Args: initial_model (nn.Module): initial PyTorch Model n_clients (int): number of clients for this job num_rounds (int): number of rounds for FedAvg name (name, optional): name of the job. Defaults to "fed_job" min_clients (int, optional): the minimum number of clients for the job. Defaults to 1. mandatory_clients (List[str], optional): mandatory clients to run the job. Default None. key_metric (str, optional): Metric used to determine if the model is globally best. if metrics are a `dict`, `key_metric` can select the metric used for global model selection. Defaults to "accuracy". convert_to_fed_event (Union[bool, ConvertToFedEvent, None]): A component to convert certain events to fed events. If not provided, a ConvertToFedEvent object will be created and add to Client If provided, a ConvertToFedEvent object will be add to Client If set to True, a ConvertToFedEvent object will be created and add to Client If set to False, no ConvertToFedEvent will be created. analytics_receiver (Union[bool, AnalyticsReceiver, None]): A component to receive analytics. If not provided, a TBAnalyticsReceiver object will be created and add to seerver If provided, a AnalyticsReceiver object will be add to Server If set to True, a TBAnalyticsReceiver object will be created and add to seerver If set to False, no AnalyticsReceiver will be created. """ if not isinstance(initial_model, nn.Module): raise ValueError(f"Expected initial model to be nn.Module, but got type f{type(initial_model)}.") super().__init__( initial_model, name, min_clients, mandatory_clients, key_metric, convert_to_fed_event=convert_to_fed_event, analytics_receiver=analytics_receiver, ) controller = FedAvg( num_clients=n_clients, num_rounds=num_rounds, persistor_id=self.comp_ids["persistor_id"], ) self.to_server(controller)