# 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. from __future__ import print_function import warnings import paddle.fluid as fluid from paddlerec.core.utils import envs __all__ = ["StartupBase", "SingleStartup", "PSStartup", "CollectiveStartup"] class StartupBase(object): """R """ def __init__(self, context): pass def startup(self, context): pass def load(self, context, is_fleet=False, main_program=None): dirname = envs.get_global_env( "runner." + context["runner_name"] + ".init_model_path", None) if dirname is None or dirname == "": return print("going to load ", dirname) if is_fleet: context["fleet"].load_persistables(context["exe"], dirname) else: fluid.io.load_persistables( context["exe"], dirname, main_program=main_program) class SingleStartup(StartupBase): """R """ def __init__(self, context): print("Running SingleStartup.") pass def startup(self, context): for model_dict in context["phases"]: with fluid.scope_guard(context["model"][model_dict["name"]][ "scope"]): train_prog = context["model"][model_dict["name"]][ "main_program"] startup_prog = context["model"][model_dict["name"]][ "startup_program"] with fluid.program_guard(train_prog, startup_prog): context["exe"].run(startup_prog) self.load(context, main_program=train_prog) context["status"] = "train_pass" class PSStartup(StartupBase): def __init__(self, context): print("Running PSStartup.") pass def startup(self, context): model_dict = context["env"]["phase"][0] with fluid.scope_guard(context["model"][model_dict["name"]]["scope"]): train_prog = context["model"][model_dict["name"]]["main_program"] startup_prog = context["model"][model_dict["name"]][ "startup_program"] with fluid.program_guard(train_prog, startup_prog): context["exe"].run(startup_prog) self.load(context, True) context["status"] = "train_pass" class CollectiveStartup(StartupBase): def __init__(self, context): print("Running CollectiveStartup.") pass def startup(self, context): model_dict = context["env"]["phase"][0] with fluid.scope_guard(context["model"][model_dict["name"]]["scope"]): train_prog = context["model"][model_dict["name"]][ "default_main_program"] startup_prog = context["model"][model_dict["name"]][ "startup_program"] with fluid.program_guard(train_prog, startup_prog): context["exe"].run(startup_prog) self.load(context, True) context["status"] = "train_pass"