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paddlepaddle--paddle/python/paddle/distributed/launch/job/job.py
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2026-07-13 12:40:42 +08:00

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2.2 KiB
Python

# Copyright (c) 2022 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.
class JobMode:
COLLECTIVE = 'collective'
PS = 'ps'
HETER = 'heter'
class Job:
def __init__(self, jid='default', mode=JobMode.COLLECTIVE, nnodes="1"):
self._mode = mode
self._id = jid
self._replicas = 0
self._replicas_min = self._replicas
self._replicas_max = self._replicas
self._elastic = False
self.set_replicas(str(nnodes))
def __str__(self):
return f"Job: {self.id}, mode {self.mode}, replicas {self._replicas}[{self._replicas_min}:{self._replicas_max}], elastic {self.elastic}"
@property
def mode(self):
return self._mode
@property
def id(self):
return self._id
@property
def elastic(self):
return self._elastic
@property
def replicas(self):
return self._replicas
@property
def replicas_min(self):
return self._replicas_min
@property
def replicas_max(self):
return self._replicas_max
@replicas.setter
def replicas(self, replicas):
self._replicas = replicas
def set_replicas(self, nnodes: str):
np = str(nnodes) if nnodes else '1'
if ':' in np:
nps = np.split(':')
self._replicas_min, self._replicas_max = int(nps[0]), int(nps[1])
self._replicas = self._replicas_max # default to max
self._elastic = True
else:
self._replicas = int(np)
self._replicas_min, self._replicas_max = (
self._replicas,
self._replicas,
)
self._elastic = False