# 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 import sys import abc import time import yaml from paddle import fluid from fleet_rec.core.utils import envs class Trainer(object): """R """ __metaclass__ = abc.ABCMeta def __init__(self, config=None): self._status_processor = {} self._place = fluid.CPUPlace() self._exe = fluid.Executor(self._place) self._exector_context = {} self._context = {'status': 'uninit', 'is_exit': False} self._config_yaml = config with open(config, 'r') as rb: self._config = yaml.load(rb.read(), Loader=yaml.FullLoader) def regist_context_processor(self, status_name, processor): """ regist a processor for specify status """ self._status_processor[status_name] = processor def context_process(self, context): """ select a processor to deal specify context Args: context : context with status Return: None : run a processor for this status """ if context['status'] in self._status_processor: self._status_processor[context['status']](context) else: self.other_status_processor(context) def other_status_processor(self, context): """ if no processor match context.status, use defalut processor Return: None, just sleep in base """ print('unknow context_status:%s, do nothing' % context['status']) time.sleep(60) def reload_train_context(self): """ context maybe update timely, reload for update """ pass def run(self): """ keep running by statu context. """ while True: self.reload_train_context() self.context_process(self._context) if self._context['is_exit']: break def user_define_engine(engine_yaml): with open(engine_yaml, 'r') as rb: _config = yaml.load(rb.read(), Loader=yaml.FullLoader) assert _config is not None envs.set_runtime_environs(_config) 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) trainer_class = envs.lazy_instance(base_name, "UserDefineTraining") return trainer_class