factory.py 2.5 KB
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# Copyright (c) 2020 PaddlePaddle Authors. 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.

import os
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import sys

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import yaml
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from fleetrec.core.utils import envs
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trainer_abs = os.path.join(os.path.dirname(os.path.abspath(__file__)), "trainers")
trainers = {}


def trainer_registry():
    trainers["SingleTrainer"] = os.path.join(trainer_abs, "single_trainer.py")
    trainers["ClusterTrainer"] = os.path.join(trainer_abs, "cluster_trainer.py")
    trainers["CtrCodingTrainer"] = os.path.join(trainer_abs, "ctr_coding_trainer.py")
    trainers["CtrModulTrainer"] = os.path.join(trainer_abs, "ctr_modul_trainer.py")


trainer_registry()

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class TrainerFactory(object):
    def __init__(self):
        pass

    @staticmethod
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    def _build_trainer(yaml_path):
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        print(envs.pretty_print_envs(envs.get_global_envs()))

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        train_mode = envs.get_trainer()
        trainer_abs = trainers.get(train_mode, None)

        if trainer_abs is None:
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            if not os.path.isfile(train_mode):
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                raise IOError("trainer {} can not be recognized".format(train_mode))
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            trainer_abs = train_mode
            train_mode = "UserDefineTrainer"

        train_dirname = os.path.dirname(trainer_abs)
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        base_name = os.path.splitext(os.path.basename(trainer_abs))[0]
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        sys.path.append(train_dirname)
        trainer_class = envs.lazy_instance(base_name, train_mode)
        trainer = trainer_class(yaml_path)
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        return trainer

    @staticmethod
    def create(config):
        _config = None
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        if os.path.isfile(config):
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            with open(config, 'r') as rb:
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                _config = yaml.load(rb.read(), Loader=yaml.FullLoader)
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        else:
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            raise ValueError("fleetrec's config only support yaml")
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        envs.set_global_envs(_config)
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        trainer = TrainerFactory._build_trainer(config)
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        return trainer
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# server num, worker num
if __name__ == "__main__":
    if len(sys.argv) != 2:
        raise ValueError("need a yaml file path argv")
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    trainer = TrainerFactory.create(sys.argv[1])
    trainer.run()