Пример #1
0
def local_mpi_engine(args):
    print("launch cluster engine with cluster to run model: {}".format(
        args.model))
    from paddlerec.core.engine.local_mpi import LocalMPIEngine

    print("use 1X1 MPI ClusterTraining at localhost to run model: {}".format(
        args.model))

    mpi = util.run_which("mpirun")
    if not mpi:
        raise RuntimeError("can not find mpirun, please check environment")

    _envs = envs.load_yaml(args.model)
    run_extras = get_all_inters_from_yaml(args.model, ["train.", "runner."])
    trainer_class = run_extras.get("runner." + _envs["mode"] + ".runner_class",
                                   None)
    executor_mode = "train"
    distributed_strategy = run_extras.get(
        "runner." + _envs["mode"] + ".distribute_strategy", "async")
    fleet_mode = run_extras.get("runner." + _envs["mode"] + ".fleet_mode",
                                "ps")

    if trainer_class:
        trainer = trainer_class
    else:
        trainer = "GeneralTrainer"

    cluster_envs = {}
    cluster_envs["mpirun"] = mpi
    cluster_envs["train.trainer.trainer"] = trainer
    cluster_envs["log_dir"] = "logs"
    cluster_envs["train.trainer.engine"] = "local_cluster"
    cluster_envs["train.trainer.executor_mode"] = executor_mode
    cluster_envs["fleet_mode"] = fleet_mode
    cluster_envs["train.trainer.strategy"] = distributed_strategy
    cluster_envs["train.trainer.threads"] = "2"
    cluster_envs["train.trainer.engine"] = "local_cluster"
    cluster_envs["train.trainer.platform"] = envs.get_platform()

    set_runtime_envs(cluster_envs, args.model)
    launch = LocalMPIEngine(cluster_envs, args.model)
    return launch
Пример #2
0
def local_mpi_engine(args):
    print("launch cluster engine with cluster to run model: {}".format(
        args.model))
    from paddlerec.core.engine.local_mpi import LocalMPIEngine

    print("use 1X1 MPI ClusterTraining at localhost to run model: {}".format(
        args.model))

    mpi = util.run_which("mpirun")
    if not mpi:
        raise RuntimeError("can not find mpirun, please check environment")
    cluster_envs = {}
    cluster_envs["mpirun"] = mpi
    cluster_envs["train.trainer.trainer"] = "CtrCodingTrainer"
    cluster_envs["log_dir"] = "logs"
    cluster_envs["train.trainer.engine"] = "local_cluster"

    cluster_envs["train.trainer.platform"] = envs.get_platform()

    set_runtime_envs(cluster_envs, args.model)
    launch = LocalMPIEngine(cluster_envs, args.model)
    return launch