diff --git a/python/paddle/distributed/backup_env.py b/python/paddle/distributed/backup_env.py new file mode 100644 index 0000000000000000000000000000000000000000..60428b9a2025d1266d4e7f0b338157a2d98b599a --- /dev/null +++ b/python/paddle/distributed/backup_env.py @@ -0,0 +1,35 @@ +# Copyright (c) 2023 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 json +import os + +g_backup_envs = None + + +def getenv_or_backup(name, default=None): + global g_backup_envs + if g_backup_envs is None: + backup_path = os.getenv('PADDLE_BACKUP_ENV_PATH') + if backup_path is None: + g_backup_envs = {} + else: + with open(backup_path, 'r') as f: + g_backup_envs = json.load(f) + + value = os.getenv(name) + if value is not None: + return value + else: + return g_backup_envs.get(name, default) diff --git a/python/paddle/distributed/fleet/base/role_maker.py b/python/paddle/distributed/fleet/base/role_maker.py index 3f2b22d8795c288fe216436174ef76b894cdbe60..113a0132f4c124547e449073c9c5c68df93e518c 100755 --- a/python/paddle/distributed/fleet/base/role_maker.py +++ b/python/paddle/distributed/fleet/base/role_maker.py @@ -25,6 +25,8 @@ from paddle.distributed.fleet.base.private_helper_function import ( ) from paddle.fluid import core +from ...backup_env import getenv_or_backup + __all__ = [] @@ -844,7 +846,9 @@ class PaddleCloudRoleMaker(RoleMakerBase): self._server_endpoints = self._server_endpoints.split(",") - self._worker_endpoints = os.getenv("PADDLE_TRAINER_ENDPOINTS", None) + self._worker_endpoints = getenv_or_backup( + "PADDLE_TRAINER_ENDPOINTS", None + ) if self._worker_endpoints is not None: self._worker_endpoints = self._worker_endpoints.split(",") else: @@ -1066,7 +1070,7 @@ class PaddleCloudRoleMaker(RoleMakerBase): self._training_role = os.getenv("PADDLE_TRAINING_ROLE", "TRAINER") assert self._training_role == "TRAINER" self._role = Role.WORKER - self._worker_endpoints = os.getenv("PADDLE_TRAINER_ENDPOINTS") + self._worker_endpoints = getenv_or_backup("PADDLE_TRAINER_ENDPOINTS") self._cur_endpoint = os.getenv("PADDLE_CURRENT_ENDPOINT") if self._worker_endpoints is None: # back to non_distributed execution. diff --git a/python/paddle/distributed/fleet/elastic/manager.py b/python/paddle/distributed/fleet/elastic/manager.py index 5e0de5c3120e371ca43c22d9bfb95aa6db40c134..00151a8dee5f18ca2f63313ef63ad52cb9ead7f1 100644 --- a/python/paddle/distributed/fleet/elastic/manager.py +++ b/python/paddle/distributed/fleet/elastic/manager.py @@ -25,6 +25,8 @@ import traceback from paddle.distributed.fleet import cloud_utils, launch_utils from paddle.distributed.utils.log_utils import get_logger +from ...backup_env import getenv_or_backup + logger = get_logger("INFO", "ELASTIC") ELASTIC_EXIT_CODE = 101 @@ -149,7 +151,7 @@ class ElasticManager: self.np = len(self.trainers.split(",")) self.start_port = int(os.getenv("PADDLE_PORT", "6170")) self.dist_endpoints = os.getenv('DISTRIBUTED_TRAINER_ENDPOINTS', '') - trainer_endpoints = os.getenv('PADDLE_TRAINER_ENDPOINTS', '') + trainer_endpoints = getenv_or_backup('PADDLE_TRAINER_ENDPOINTS', '') self.trainer_endpoints_list = trainer_endpoints.split(",") else: self.trainers = args.ips or os.getenv('PADDLE_TRAINERS', '') diff --git a/python/paddle/distributed/launch/controllers/controller.py b/python/paddle/distributed/launch/controllers/controller.py index 9769ec9d6bf3f233aba4c60ae476a766202c3008..25becbba6f329ca206fb8b8edae98da7a0f55b7a 100644 --- a/python/paddle/distributed/launch/controllers/controller.py +++ b/python/paddle/distributed/launch/controllers/controller.py @@ -12,6 +12,7 @@ # See the License for the specific language governing permissions and # limitations under the License. +import copy import os import signal import sys @@ -244,6 +245,8 @@ class Controller(ControllerBase): is_init=False, ): if not container: + envs = copy.deepcopy(envs) + envs['PADDLE_LOG_DIR'] = str(os.path.abspath(self.ctx.args.log_dir)) container = self.new_container( entrypoint=entrypoint, envs=envs, out=log_file, err=log_file ) diff --git a/python/paddle/distributed/launch/utils/process_context.py b/python/paddle/distributed/launch/utils/process_context.py index 6543d7bd9ebae25f4505eb99cb0be8cec9978a8e..8b14d5417a68b1d9f7650b879dab5f0cb9e6efe9 100644 --- a/python/paddle/distributed/launch/utils/process_context.py +++ b/python/paddle/distributed/launch/utils/process_context.py @@ -12,12 +12,15 @@ # See the License for the specific language governing permissions and # limitations under the License. +import json import os import signal import subprocess import sys import time +LIMIT_LEN_ENVS = ["TRAINER_IP_PORT_LIST", "PADDLE_TRAINER_ENDPOINTS"] + class ProcessContext: def __init__( @@ -42,9 +45,30 @@ class ProcessContext: def _start(self): pre_fn = os.setsid if self._group else None + log_dir = self._env["PADDLE_LOG_DIR"] + os.makedirs(log_dir, exist_ok=True) + + rank = self._env.get("PADDLE_TRAINER_ID") + if rank is not None: + rank = int(rank) + backup_env_path = str( + os.path.join(log_dir, f'backup_env.{rank}.json') + ) + envs = {"PADDLE_BACKUP_ENV_PATH": backup_env_path} + + max_len = int(os.getenv('PADDLE_ENV_LIMIT_LEN', 48000)) + for k, v in self._env.items(): + if k not in LIMIT_LEN_ENVS or len(v) < max_len: + envs[k] = v + + with open(backup_env_path, 'w') as f: + json.dump(dict(self._env), f, indent=4, sort_keys=True) + else: + envs = self._env + self._proc = subprocess.Popen( self._cmd, - env=self._env, + env=envs, stdout=self._stdout, stderr=self._stderr, preexec_fn=self._preexec_fn or pre_fn, diff --git a/python/paddle/distributed/parallel.py b/python/paddle/distributed/parallel.py index cc6ab5384ca4ef99e85495ab8e792d5516656f1d..a34807d2b7377ee1cea7864a828d8feaf65d689d 100644 --- a/python/paddle/distributed/parallel.py +++ b/python/paddle/distributed/parallel.py @@ -56,6 +56,7 @@ from paddle.nn.layer import layers from paddle.utils import deprecated from . import parallel_helper +from .backup_env import getenv_or_backup __all__ = [] @@ -704,7 +705,7 @@ class ParallelEnv: selected_xpus = os.getenv("FLAGS_selected_xpus", "0").split(",") self._device_id = int(selected_xpus[0]) - self._trainer_endpoints = os.getenv( + self._trainer_endpoints = getenv_or_backup( "PADDLE_TRAINER_ENDPOINTS", "" ).split(",") self._current_endpoint = os.getenv("PADDLE_CURRENT_ENDPOINT", "") @@ -878,7 +879,7 @@ def _is_cpuonly(backend): def _check_var_exists(var_name): - var = os.environ.get(var_name, None) + var = getenv_or_backup(var_name, None) if var is None: raise ValueError( "paddle.distributed initialize error, " @@ -1060,7 +1061,9 @@ def init_parallel_env(): if endpoints is None: endpoints = os.getenv("PADDLE_MASTER", None) if endpoints is None: - endpoints = os.getenv("PADDLE_TRAINER_ENDPOINTS").split(',')[0] + endpoints = getenv_or_backup("PADDLE_TRAINER_ENDPOINTS").split(',')[ + 0 + ] assert endpoints, ( "The environment variable 'MASTER_ADDR' and 'MASTER_PORT' " "must be specified, for example 'export MASTER_ADDR=127.0.0.1' " diff --git a/python/paddle/fluid/executor.py b/python/paddle/fluid/executor.py index b3deb787960e6580b7a9289add98b7958d01af5e..a9afe7f5c8d0d0c3e0dcffd319f754f0301606e1 100755 --- a/python/paddle/fluid/executor.py +++ b/python/paddle/fluid/executor.py @@ -525,8 +525,9 @@ def _to_name_str(var): def _prepare_fleet_executor(): from ..distributed.fleet.proto import fleet_executor_desc_pb2 + from ..distributed.backup_env import getenv_or_backup - trainer_endpoints_str = os.getenv("PADDLE_TRAINER_ENDPOINTS", "") + trainer_endpoints_str = getenv_or_backup("PADDLE_TRAINER_ENDPOINTS", "") trainer_endpoints = trainer_endpoints_str.split(',') fleet_exe_desc = fleet_executor_desc_pb2.FleetExecutorDesc() cur_rank = int(os.getenv("PADDLE_TRAINER_ID", 0)) diff --git a/test/legacy_test/test_run.py b/test/legacy_test/test_run.py index 467b9ef35c67b06bf5965150d9766c58e9263de3..3174dd7005ce6dae35c7928e20f59d67f7be225b 100644 --- a/test/legacy_test/test_run.py +++ b/test/legacy_test/test_run.py @@ -55,6 +55,7 @@ def get_files(pth, prefix): if isfile(join(pth, f)) and not f.endswith('gpu.log') and not f.startswith('envlog') + and not f.startswith('backup_env') ]