trainer.py 2.9 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.

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import abc
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import os
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import time
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import sys
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import yaml
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from paddle import fluid
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from paddlerec.core.utils import envs
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class Trainer(object):
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    """R
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    """
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    __metaclass__ = abc.ABCMeta
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    def __init__(self, config=None):
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        self._status_processor = {}
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        self._place = fluid.CPUPlace()
        self._exe = fluid.Executor(self._place)
        self._exector_context = {}
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        self._context = {'status': 'uninit', 'is_exit': False}
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        self._config_yaml = config
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        self._config = envs.load_yaml(config)
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    def regist_context_processor(self, status_name, processor):
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        """
        regist a processor for specify status
        """
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        self._status_processor[status_name] = processor

    def context_process(self, context):
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        """
        select a processor to deal specify context
        Args:
            context : context with status
        Return:
            None : run a processor for this status
        """
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        if context['status'] in self._status_processor:
            self._status_processor[context['status']](context)
        else:
            self.other_status_processor(context)
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    def other_status_processor(self, context):
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        """
        if no processor match context.status, use defalut processor
        Return:
            None, just sleep in base
        """
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        print('unknow context_status:%s, do nothing' % context['status'])
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        time.sleep(60)
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    def reload_train_context(self):
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        """
        context maybe update timely, reload for update
        """
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        pass

    def run(self):
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        """
        keep running by statu context.
        """
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        while True:
            self.reload_train_context()
            self.context_process(self._context)
            if self._context['is_exit']:
                break
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def user_define_engine(engine_yaml):
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    _config = envs.load_yaml(engine_yaml)
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    envs.set_runtime_environs(_config)
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    train_location = envs.get_global_env("engine.file")
    train_dirname = os.path.dirname(train_location)
    base_name = os.path.splitext(os.path.basename(train_location))[0]
    sys.path.append(train_dirname)
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    trainer_class = envs.lazy_instance_by_fliename(base_name,
                                                   "UserDefineTraining")
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    return trainer_class