mirror of
https://github.com/tencentmusic/cube-studio.git
synced 2024-11-27 05:33:10 +08:00
add mxnet job
This commit is contained in:
FerdinandWard
parent
a8d85312d4
commit
11b6fd38d6
33
job-template/job/mxnet/Dockerfile
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33
job-template/job/mxnet/Dockerfile
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FROM ubuntu:18.04
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RUN apt-get update && apt-get -y install gcc g++ libjpeg-dev zlib1g-dev cmake
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# 安装运维工具
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RUN apt install -y --force-yes --no-install-recommends vim apt-transport-https gnupg2 ca-certificates-java rsync jq wget git dnsutils iputils-ping net-tools curl mysql-client locales zip
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# 安装python
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RUN apt install -y python3.6-dev python3-pip libsasl2-dev libpq-dev \
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&& ln -s /usr/bin/python3 /usr/bin/python \
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&& ln -s /usr/bin/pip3 /usr/bin/pip
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RUN wget https://github.com/stern/stern/releases/download/v1.21.0/stern_1.21.0_linux_amd64.tar.gz && tar -zxvf stern_1.21.0_linux_amd64.tar.gz && rm stern_1.21.0_linux_amd64.tar.gz && chmod +x stern && mv stern /usr/bin/stern
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# 安装中文
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RUN apt install -y --force-yes --no-install-recommends locales ttf-wqy-microhei ttf-wqy-zenhei xfonts-wqy && locale-gen zh_CN && locale-gen zh_CN.utf8
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ENV LANG zh_CN.UTF-8
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ENV LC_ALL zh_CN.UTF-8
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ENV LANGUAGE zh_CN.UTF-8
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# 便捷操作
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RUN echo "alias ll='ls -alF'" >> /root/.bashrc && \
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echo "alias la='ls -A'" >> /root/.bashrc && \
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echo "alias vi='vim'" >> /root/.bashrc && \
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/bin/bash -c "source /root/.bashrc"
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RUN pip install kubernetes==18.20.0 pysnooper psutil
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COPY job/mxnet/* /app/
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COPY job/pkgs /app/job/pkgs
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WORKDIR /app
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ENV PYTHONPATH=/app:$PYTHONPATH
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ENTRYPOINT ["python3", "launcher.py"]
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0
job-template/job/mxnet/README.md
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0
job-template/job/mxnet/README.md
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8
job-template/job/mxnet/build.sh
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8
job-template/job/mxnet/build.sh
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#!/bin/bash
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set -ex
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docker build -t ccr.ccs.tencentyun.com/cube-studio/mxnet:20221010 -f job/mxnet/Dockerfile .
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docker push ccr.ccs.tencentyun.com/cube-studio/mxnet:20221010
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42
job-template/job/mxnet/demo.yaml
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42
job-template/job/mxnet/demo.yaml
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apiVersion: "kubeflow.org/v1"
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kind: "MXJob"
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metadata:
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name: "mxnet-job"
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namespace: pipeline
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spec:
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runPolicy:
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cleanPodPolicy: None
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jobMode: MXTrain
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mxReplicaSpecs:
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Scheduler:
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replicas: 1
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restartPolicy: Never
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template:
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spec:
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containers:
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- name: mxnet
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image: mxjob/mxnet:gpu
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Server:
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replicas: 1
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restartPolicy: Never
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template:
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spec:
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containers:
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- name: mxnet
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image: mxjob/mxnet:gpu
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Worker:
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replicas: 1
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restartPolicy: Never
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template:
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spec:
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containers:
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- name: mxnet
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image: mxjob/mxnet:gpu
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command: ["python"]
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args: ["/incubator-mxnet/example/image-classification/train_mnist.py","--num-epochs","10","--num-layers","2","--kv-store","dist_device_sync","--gpus","0"]
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resources:
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limits:
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nvidia.com/gpu: 1
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ports:
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- containerPort: 9991
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name: mxjob-port
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352
job-template/job/mxnet/launcher.py
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352
job-template/job/mxnet/launcher.py
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import os,sys
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base_dir = os.path.split(os.path.realpath(__file__))[0]
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sys.path.append(base_dir)
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import argparse
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import datetime
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import json
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import time
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import uuid
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import os
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import pysnooper
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import os,sys
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import re
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import threading
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import psutil
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import copy
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from kubernetes import client
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# print(os.environ)
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from job.pkgs.k8s.py_k8s import K8s
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k8s_client = K8s()
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KFJ_NAMESPACE = os.getenv('KFJ_NAMESPACE', '')
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KFJ_TASK_ID = os.getenv('KFJ_TASK_ID', '')
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KFJ_TASK_NAME = os.getenv('KFJ_TASK_NAME', '')
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task_node_selectors = re.split(',|;|\n|\t', os.getenv('KFJ_TASK_NODE_SELECTOR', 'cpu=true,train=true'))
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KFJ_TASK_NODE_SELECTOR = {}
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for task_node_selector in task_node_selectors:
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KFJ_TASK_NODE_SELECTOR[task_node_selector.split('=')[0]] = task_node_selector.split('=')[1]
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KFJ_PIPELINE_ID = os.getenv('KFJ_PIPELINE_ID', '')
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KFJ_RUN_ID = os.getenv('KFJ_RUN_ID', '')
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KFJ_CREATOR = os.getenv('KFJ_CREATOR', '')
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KFJ_RUNNER = os.getenv('KFJ_RUNNER','')
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KFJ_PIPELINE_NAME = os.getenv('KFJ_PIPELINE_NAME', '')
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KFJ_TASK_IMAGES = os.getenv('KFJ_TASK_IMAGES', '')
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KFJ_TASK_VOLUME_MOUNT = os.getenv('KFJ_TASK_VOLUME_MOUNT', '')
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KFJ_TASK_RESOURCE_CPU = os.getenv('KFJ_TASK_RESOURCE_CPU', '')
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KFJ_TASK_RESOURCE_MEMORY = os.getenv('KFJ_TASK_RESOURCE_MEMORY', '')
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NUM_WORKER = 3
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INIT_FILE=''
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crd_info={
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"group": "kubeflow.org",
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"version": "v1",
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'kind': 'MXJob',
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"plural": "mxjobs",
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"timeout": 60 * 60 * 24 * 2
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}
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k8s_volumes, k8s_volume_mounts = k8s_client.get_volume_mounts(KFJ_TASK_VOLUME_MOUNT,KFJ_CREATOR)
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print(k8s_volumes)
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print(k8s_volume_mounts)
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GPU_TYPE= os.getenv('KFJ_GPU_TYPE', 'NVIDIA')
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GPU_RESOURCE= os.getenv('KFJ_TASK_RESOURCE_GPU', '0')
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print(GPU_TYPE,GPU_RESOURCE)
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def default_job_name():
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name = "mxjob-" + KFJ_PIPELINE_NAME.replace('_','-')+"-"+uuid.uuid4().hex[:4]
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return name[0:54]
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import subprocess
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# @pysnooper.snoop()
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def run_shell(shell):
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print('begin run shell: %s'%shell,flush=True)
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cmd = subprocess.Popen(shell, stdin=subprocess.PIPE, stderr=subprocess.PIPE,
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stdout=subprocess.PIPE, universal_newlines=True, shell=True, bufsize=1)
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# 实时输出
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while True:
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line = cmd.stdout.readline()
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status = subprocess.Popen.poll(cmd)
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if status:
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print(status,line,end='', flush=True)
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else:
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print(line, end='', flush=True)
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if status == 0: # 判断子进程是否结束
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print('shell finish %s'%status,flush=True)
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break
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if status==-9 or status==-15 or status==143: # 外界触发kill
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print('shell finish %s'%status,flush=True)
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break
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return cmd.returncode
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# 监控指定名称的mxjob
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def monitoring(crd_k8s,name,namespace):
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time.sleep(10)
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# 杀掉stern 进程
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def get_pid(name):
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'''
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作用：根据进程名获取进程pid
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'''
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pids = psutil.process_iter()
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print("[" + name + "]'s pid is:", flush=True)
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back=[]
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for pid in pids:
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if name in pid.name():
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print(pid.pid, flush=True)
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back.append(pid.pid)
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return back
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check_time = datetime.datetime.now()
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while(True):
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mxjob = crd_k8s.get_one_crd(group=crd_info['group'],version=crd_info['version'],plural=crd_info['plural'],namespace=namespace,name=name)
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if mxjob:
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print('mxjob status %s'%mxjob['status'], flush=True)
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else:
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print('mxjob not exist', flush=True)
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if mxjob and (mxjob['status']=="Succeeded" or mxjob['status']=="Failed"): # Created, Running, Restarting, Succeeded, or Failed
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pids = get_pid("stern")
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if pids:
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for pid in pids:
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pro = psutil.Process(int(pid))
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pro.terminate()
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print('kill process %s'%pid, flush=True)
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break
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if (datetime.datetime.now()-check_time).seconds>3600:
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pids = get_pid("stern")
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if pids:
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for pid in pids:
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pro = psutil.Process(int(pid))
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pro.terminate()
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print('kill process %s'%pid, flush=True)
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check_time=datetime.datetime.now()
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time.sleep(60)
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# @pysnooper.snoop()
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def make_mxjob(name,num_ps,num_workers,image,working_dir,command):
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pod_spec={
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"replicas": 1,
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"restartPolicy": "Never",
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"template": {
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"metadata": {
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"labels": {
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"pipeline-id": KFJ_PIPELINE_ID,
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"pipeline-name": KFJ_PIPELINE_NAME,
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"task-id": KFJ_TASK_ID,
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"task-name": KFJ_TASK_NAME,
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'rtx-user': KFJ_RUNNER,
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"component": name,
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"type": "mxjob",
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"run-id": KFJ_RUN_ID,
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}
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},
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"spec": {
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# "schedulerName": "kube-batch",
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"restartPolicy": "Never",
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"volumes": k8s_volumes,
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"imagePullSecrets": [
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{
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"name": "hubsecret"
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}
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],
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"affinity": {
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"nodeAffinity": {
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"requiredDuringSchedulingIgnoredDuringExecution": {
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"nodeSelectorTerms": [
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{
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"matchExpressions": [
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{
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"key": node_selector_key,
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"operator": "In",
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"values": [
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KFJ_TASK_NODE_SELECTOR[node_selector_key]
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]
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} for node_selector_key in KFJ_TASK_NODE_SELECTOR
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]
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}
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]
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}
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},
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"podAntiAffinity": {
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"preferredDuringSchedulingIgnoredDuringExecution": [
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{
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"weight": 5,
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"podAffinityTerm": {
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"topologyKey": "kubernetes.io/hostname",
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"labelSelector": {
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"matchLabels": {
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"component": name,
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"type": "mxjob"
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}
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}
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}
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}
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]
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}
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},
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"containers": [
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{
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"name": "mxnet",
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"image": image if image else KFJ_TASK_IMAGES,
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"imagePullPolicy": "Always",
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"workingDir":working_dir if working_dir else None,
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"command": ['bash','-c',command] if command else None,
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"volumeMounts": k8s_volume_mounts,
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"resources": {
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"requests": {
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"cpu": KFJ_TASK_RESOURCE_CPU,
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"memory": KFJ_TASK_RESOURCE_MEMORY,
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},
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"limits": {
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"cpu": KFJ_TASK_RESOURCE_CPU,
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"memory": KFJ_TASK_RESOURCE_MEMORY
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}
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}
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}
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]
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}
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}
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}
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if GPU_TYPE=='NVIDIA' and GPU_RESOURCE:
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pod_spec['template']['spec']['containers'][0]['resources']['requests']['nvidia.com/gpu'] = GPU_RESOURCE.split(',')[0]
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pod_spec['template']['spec']['containers'][0]['resources']['limits']['nvidia.com/gpu'] = GPU_RESOURCE.split(',')[0]
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worker_pod_spec = copy.deepcopy(pod_spec)
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worker_pod_spec['replicas']=int(num_workers)
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scheduler_pod_spec={
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"replicas": 1,
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"restartPolicy": "Never",
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"template": {
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"metadata": {
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"labels": {
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"pipeline-id": KFJ_PIPELINE_ID,
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"pipeline-name": KFJ_PIPELINE_NAME,
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"task-id": KFJ_TASK_ID,
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"task-name": KFJ_TASK_NAME,
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'rtx-user': KFJ_RUNNER,
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"component": name,
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"type": "mxjob",
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"run-id": KFJ_RUN_ID,
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}
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},
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"spec": {
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"containers": [
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{
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"name": "mxnet",
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"image": image
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}
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]
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}
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}
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}
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server_pod_spec = copy.deepcopy(scheduler_pod_spec)
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server_pod_spec['replicas']=int(num_ps)
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mx_deploy = {
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"apiVersion": "kubeflow.org/v1",
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"kind": "MXJob",
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"metadata": {
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"namespace": KFJ_NAMESPACE,
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"name": name,
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"labels":{
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"run-id":KFJ_RUN_ID,
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"run-rtx":KFJ_RUNNER,
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"pipeline-rtx": KFJ_CREATOR,
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"pipeline-id": KFJ_PIPELINE_ID,
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"pipeline-name": KFJ_PIPELINE_NAME,
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"task-id": KFJ_TASK_ID,
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"task-name": KFJ_TASK_NAME,
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}
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},
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"spec": {
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"jobMode":'MXTrain',
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"runPolicy":{
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"cleanPodPolicy": "None",
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},
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"mxReplicaSpecs": {
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"Scheduler":scheduler_pod_spec,
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"Server":server_pod_spec,
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"Worker":worker_pod_spec
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}
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}
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}
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return mx_deploy
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# @pysnooper.snoop()
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def launch_mxjob(name, num_ps,num_workers, image,working_dir, worker_command):
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if KFJ_RUN_ID:
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print('delete old mx, run-id %s'%KFJ_RUN_ID, flush=True)
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k8s_client.delete_crd(group=crd_info['group'],version=crd_info['version'],plural=crd_info['plural'],namespace=KFJ_NAMESPACE,labels={"run-id":KFJ_RUN_ID})
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time.sleep(10)
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# 删除旧的mx
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k8s_client.delete_crd(group=crd_info['group'], version=crd_info['version'], plural=crd_info['plural'],namespace=KFJ_NAMESPACE, name=name)
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time.sleep(10)
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# 创建新的mx
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mxjob_json = make_mxjob(name=name,num_ps=num_ps,num_workers= num_workers,image = image,working_dir=working_dir,command=worker_command)
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print('create new mx %s' % name, flush=True)
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k8s_client.create_crd(group=crd_info['group'],version=crd_info['version'],plural=crd_info['plural'],namespace=KFJ_NAMESPACE,body=mxjob_json)
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time.sleep(10)
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print('begin start monitoring thread', flush=True)
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# # 后台启动监控脚本
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monitoring_thread = threading.Thread(target=monitoring,args=(k8s_client,name,KFJ_NAMESPACE))
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monitoring_thread.start()
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while True:
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# 实时打印日志
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line='>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>'
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print('begin follow log\n%s'%line, flush=True)
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command = '''stern %s --namespace %s --exclude-container init-mx --since 10s --template '{{.PodName}} {{.Message}} {{"\\n"}}' '''%(name,KFJ_NAMESPACE)
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print(command, flush=True)
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run_shell(command)
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print('%s\nend follow log'%line, flush=True)
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time.sleep(10)
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mxjob = k8s_client.get_one_crd(group=crd_info['group'], version=crd_info['version'],plural=crd_info['plural'], namespace=KFJ_NAMESPACE, name=name)
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if mxjob and (mxjob['status'] == "Succeeded" or mxjob['status'] == "Failed"):
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break
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mxjob = k8s_client.get_one_crd(group=crd_info['group'],version=crd_info['version'],plural=crd_info['plural'],namespace=KFJ_NAMESPACE,name=name)
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print("mxJob %s finished, status %s"%(name, mxjob['status']))
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if mxjob['status']!='Succeeded':
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exit(1)
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if __name__ == "__main__":
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arg_parser = argparse.ArgumentParser("mxjob launcher")
|
||||
arg_parser.add_argument('--working_dir', type=str, help="运行job的工作目录", default='/mnt/')
|
||||
arg_parser.add_argument('--command', type=str, help="运行job的命令", default='python3 mnist.py')
|
||||
arg_parser.add_argument('--num_ps', type=int, help="运行ps的pod数目", default=0)
|
||||
arg_parser.add_argument('--num_worker', type=int, help="运行worker的pod数目", default=3)
|
||||
arg_parser.add_argument('--image', type=str, help="运行job的镜像", default='')
|
||||
|
||||
args = arg_parser.parse_args()
|
||||
print("{} args: {}".format(__file__, args))
|
||||
|
||||
|
||||
launch_mxjob(name=default_job_name(),num_ps=int(args.num_ps),num_workers=int(args.num_worker),image=args.image,working_dir=args.working_dir,worker_command=args.command)
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user