#from mpi4py import MPI

from .FedNASAggregator import FedNASAggregator
from .FedNASClientManager import FedNASClientManager
from .FedNASServerManager import FedNASServerManager
from .FedNASTrainer import FedNASTrainer


def FedML_init():
    comm = MPI.COMM_WORLD
    process_id = comm.Get_rank()
    worker_number = comm.Get_size()
    return comm, process_id, worker_number


def FedML_FedNAS_distributed(
    process_id,
    worker_number,
    device,
    comm,
    model,
    train_data_num,
    train_data_global,
    test_data_global,
    local_data_num,
    train_data_local,
    test_data_local,
    args,
):
    if process_id == 0:
        init_server(
            args,
            device,
            comm,
            process_id,
            worker_number,
            model,
            train_data_num,
            train_data_global,
            test_data_global,
        )
    else:
        init_client(
            args,
            device,
            comm,
            process_id,
            worker_number,
            model,
            train_data_num,
            local_data_num,
            train_data_local,
            test_data_local,
        )


def init_server(
    args,
    device,
    comm,
    process_id,
    worker_number,
    model,
    train_data_num,
    train_data_global,
    test_data_global,
):
    # aggregator
    client_num = worker_number - 1
    aggregator = FedNASAggregator(
        train_data_global,
        test_data_global,
        train_data_num,
        client_num,
        model,
        device,
        args,
    )

    # start the distributed training
    server_manager = FedNASServerManager(
        args, comm, process_id, worker_number, aggregator
    )
    server_manager.run()


def init_client(
    args,
    device,
    comm,
    process_id,
    worker_number,
    model,
    train_data_num,
    local_data_num,
    train_data_local,
    test_data_local,
):
    # trainer
    client_ID = process_id - 1
    trainer = FedNASTrainer(
        client_ID,
        train_data_local,
        test_data_local,
        local_data_num,
        train_data_num,
        model,
        device,
        args,
    )

    client_manager = FedNASClientManager(args, comm, process_id, worker_number, trainer)
    client_manager.run()
