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- # copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
- #
- # 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
- from .modules.base import (
- build_dataset_checker,
- build_trainer,
- build_evaluater,
- build_exportor,
- build_predictor,
- )
- from .utils.result_saver import try_except_decorator
- from .utils import config
- from .utils.errors import raise_unsupported_api_error
- class Engine(object):
- """Engine"""
- def __init__(self):
- args = config.parse_args()
- self.config = config.get_config(
- args.config, overrides=args.override, show=False
- )
- self.mode = self.config.Global.mode
- self.output = self.config.Global.output
- @try_except_decorator
- def run(self):
- """the main function"""
- if self.config.Global.mode == "check_dataset":
- dataset_checker = build_dataset_checker(self.config)
- return dataset_checker.check()
- elif self.config.Global.mode == "train":
- trainer = build_trainer(self.config)
- trainer.train()
- elif self.config.Global.mode == "evaluate":
- evaluator = build_evaluater(self.config)
- return evaluator.evaluate()
- elif self.config.Global.mode == "export":
- exportor = build_exportor(self.config)
- return exportor.export()
- elif self.config.Global.mode == "predict":
- predictor = build_predictor(self.config)
- return predictor.predict()
- else:
- raise_unsupported_api_error(f"{self.config.Global.mode}", self.__class__)
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