mirror of
https://github.com/tencentmusic/cube-studio.git
synced 2024-12-21 06:19:31 +08:00
2510 lines
99 KiB
JSON
2510 lines
99 KiB
JSON
{
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||
"自定义镜像":{
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"project_name":"基础命令",
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"image_describe":"有序分布式任务",
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"job_template_command":"",
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"--image":{
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"choice":[
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"range":"",
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"placeholder":"",
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"describe":"worker镜像,直接运行你代码的环境镜像<a target='_blank' href='https://github.com/tencentmusic/cube-studio/tree/master/images'>基础镜像</a>",
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"--working_dir":{
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"type":"str",
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"item_type":"str",
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"label":"启动目录",
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"require":1,
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"choice":[
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],
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"range":"",
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"default":"/mnt/xx",
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"placeholder":"",
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"describe":"启动目录",
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"editable":1,
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"condition":"",
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"sub_args":{
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}
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},
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"--command":{
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"type":"str",
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"item_type":"str",
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"label":"启动命令",
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"require":1,
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"choice":[
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],
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"range":"",
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"default":"echo aa",
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"describe":"启动命令",
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"editable":1,
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"condition":"",
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"sub_args":{
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}
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},
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"--num_worker":{
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"type":"str",
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"item_type":"str",
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"label":"占用机器个数",
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"require":1,
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"choice":[
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],
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"range":"",
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"describe":"占用机器个数",
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"condition":"",
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"sub_args":{
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}
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}
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}
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}
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},
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"ray":{
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"project_name":"数据处理",
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"image_name":"ccr.ccs.tencentyun.com/cube-studio/ray:gpu-20210601",
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||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/ray",
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||
"image_describe":"ray分布式任务",
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||
"job_template_name":"ray",
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||
"job_template_describe":"python多机分布式任务",
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"job_template_command":"",
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"job_template_volume":"",
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"job_template_account":"kubeflow-pipeline",
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||
"job_template_expand":{
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||
"index":2,
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||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/ray"
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||
},
|
||
"job_template_args":{
|
||
"参数":{
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||
"-n":{
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||
"type":"str",
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||
"item_type":"",
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||
"label":"分布式任务worker的数量",
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||
"require":1,
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||
"choice":[
|
||
],
|
||
"range":"$min,$max",
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||
"default":"3",
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"placeholder":"",
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||
"describe":"分布式任务worker的数量",
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"editable":1,
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||
"condition":"",
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"sub_args":{
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||
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||
}
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||
},
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||
"-i":{
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||
"type":"str",
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||
"item_type":"str",
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||
"label":"每个worker的初始化脚本文件地址,用来安装环境",
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||
"require":0,
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||
"choice":[
|
||
],
|
||
"range":"",
|
||
"default":"",
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||
"placeholder":"每个worker的初始化脚本文件地址,用来安装环境",
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"describe":"每个worker的初始化脚本文件地址,用来安装环境",
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||
"editable":1,
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"condition":"",
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||
"sub_args":{
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||
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||
}
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||
},
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||
"-f":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"python启动命令,例如 python3 /mnt/xx/xx.py",
|
||
"require":1,
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||
"choice":[
|
||
],
|
||
"range":"",
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||
"default":"python /mnt/admin/demo.py",
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||
"placeholder":"",
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||
"editable":1,
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||
"condition":"",
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||
"sub_args":{
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||
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||
}
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||
}
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||
}
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||
}
|
||
},
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||
"sparkjob":{
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||
"project_name":"数据处理",
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||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/spark:20221010",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/spark",
|
||
"image_describe":"spark serverless分布式任务",
|
||
"job_template_name":"sparkjob",
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||
"job_template_describe":"spark serverless分布式任务",
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||
"job_template_command":"",
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||
"job_template_volume":"",
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||
"job_template_account":"kubeflow-pipeline",
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||
"job_template_expand":{
|
||
"index":3,
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||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/spark"
|
||
},
|
||
"job_template_env":"NO_RESOURCE_CHECK=true\nTASK_RESOURCE_CPU=2\nTASK_RESOURCE_MEMORY=4G\nTASK_RESOURCE_GPU=0",
|
||
"job_template_args":{
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||
"参数":{
|
||
"--image": {
|
||
"type": "str",
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||
"item_type": "str",
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||
"label": "执行镜像",
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||
"require": 1,
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||
"choice": [],
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||
"range": "",
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||
"default": "ccr.ccs.tencentyun.com/cube-studio/spark-operator:spark-v3.1.1",
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"placeholder": "",
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"describe": "执行镜像",
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"editable": 1,
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||
"condition": "",
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||
"sub_args": {}
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||
},
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||
"--num_worker": {
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||
"type": "str",
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||
"item_type": "str",
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||
"label": "executor 数目",
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||
"require": 1,
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||
"choice": [],
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||
"range": "",
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||
"default": "3",
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||
"placeholder": "",
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||
"describe": "executor 数目",
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||
"editable": 1,
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||
"condition": "",
|
||
"sub_args": {}
|
||
},
|
||
"--code_type": {
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||
"type": "str",
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||
"item_type": "str",
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||
"label": "语言类型",
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||
"require": 1,
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||
"choice": [
|
||
"Java",
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||
"Python",
|
||
"Scala",
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||
"R"
|
||
],
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"range": "",
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||
"default": "Python",
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||
"placeholder": "",
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||
"describe": "语言类型",
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"editable": 1,
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||
"condition": "",
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||
"sub_args": {}
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||
},
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"--code_class": {
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"type": "str",
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"item_type": "str",
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||
"label": "Java/Scala类名",
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||
"require": 0,
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||
"choice": [],
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||
"range": "",
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||
"default": "",
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||
"placeholder": "",
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||
"describe": "Java/Scala类名,其他语言下不填",
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"editable": 1,
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||
"condition": "",
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||
"sub_args": {}
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||
},
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"--code_file": {
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"type": "str",
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"item_type": "str",
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"label": "代码文件地址",
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"require": 1,
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"choice": [],
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||
"range": "",
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||
"default": "local:///opt/spark/examples/src/main/python/pi.py",
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||
"placeholder": "",
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"describe": "代码文件地址,支持local://,http://,hdfs://,s3a://,gcs://",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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"--code_arguments": {
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"item_type": "str",
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"choice": [],
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"range": "",
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"default": "",
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"placeholder": "",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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"--sparkConf": {
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"type": "text",
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"item_type": "str",
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"label": "spark配置",
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"require": 0,
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||
"choice": [],
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"range": "",
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"default": "",
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"placeholder": "",
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"describe": "spark配置,每行一个配置,xx=yy",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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||
},
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"--hadoopConf": {
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||
"type": "text",
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"item_type": "str",
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"label": "hadoop配置,每行一个配置,xx=yy",
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"require": 0,
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"choice": [],
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"range": "",
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"default": "",
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"placeholder": "",
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"describe": "hadoop配置",
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"condition": "",
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"sub_args": {}
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}
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},
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"ray-sklearn":{
|
||
"project_name":"机器学习",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/sklearn_estimator:v1",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/ray_sklearn",
|
||
"image_describe":"sklearn基于ray的分布式",
|
||
"job_template_name":"ray-sklearn",
|
||
"job_template_describe":"sklearn基于ray的分布式",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
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"job_template_account":"kubeflow-pipeline",
|
||
"job_template_env":"NO_RESOURCE_CHECK=true",
|
||
"job_template_expand":{
|
||
"index":1,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/ray_sklearn"
|
||
},
|
||
"job_template_args":{
|
||
"参数":{
|
||
"--train_csv_file_path":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"训练集csv",
|
||
"require":1,
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||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"训练集csv,|分割符,首行是列名",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--predict_csv_file_path":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"预测数据集csv",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"预测数据集csv,格式和训练集一致,默认为空,需要predict时填",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--label_name":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"label的列名,必填",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"label的列名,必填",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--model_name":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"模型名称,必填",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"训练用到的模型名称,如LogisticRegression,必填。常用的都支持,要加联系管理员",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--model_args_dict":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"模型参数",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"模型参数,json格式,默认为空",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--model_file_path":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"模型文件保存文件名,必填",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"模型文件保存文件名,必填",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--predict_result_path":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"预测结果保存文件名,默认为空,需要predict时填",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"预测结果保存文件名,默认为空,需要predict时填",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--worker_num":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"ray worker数量",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"ray worker数量",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"xgb":{
|
||
"project_name":"机器学习",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/xgb_train_and_predict:v1",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/xgb_train_and_predict",
|
||
"image_describe":"xgb算法单机",
|
||
"job_template_name":"xgb",
|
||
"job_template_describe":"xgb算法单机",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"",
|
||
"job_template_env":"",
|
||
"job_template_expand":{
|
||
"index":2,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/xgb_train_and_predict"
|
||
},
|
||
"job_template_args":{
|
||
"训练":{
|
||
"--train_csv_file_path":{
|
||
"type":"str",
|
||
"item_type":"",
|
||
"label":"训练集csv路径",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"/app/train.csv",
|
||
"placeholder":"",
|
||
"describe":"训练集csv路径,首行是header,首列是label。为空则不做训练,尝试从model_load_path加载模型。",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--sep":{
|
||
"type":"str",
|
||
"item_type":"",
|
||
"label":"分隔符",
|
||
"require":1,
|
||
"choice":[
|
||
"space",
|
||
"TAB",
|
||
","
|
||
],
|
||
"range":"",
|
||
"default":",",
|
||
"placeholder":"",
|
||
"describe":"分隔符",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--classifier_or_regressor":{
|
||
"type":"str",
|
||
"item_type":"",
|
||
"label":"分类还是回归",
|
||
"require":1,
|
||
"choice":[
|
||
"classifier",
|
||
"regressor"
|
||
],
|
||
"range":"",
|
||
"default":"classifier",
|
||
"placeholder":"",
|
||
"describe":"分类还是回归",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--params":{
|
||
"type":"json",
|
||
"item_type":"str",
|
||
"label":"xgb参数",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":{
|
||
"max_depth":4,
|
||
"learning_rate":0.4,
|
||
"n_estimators":30,
|
||
"objective":"reg:linear",
|
||
"nthread":-1
|
||
},
|
||
"placeholder":"",
|
||
"describe":"xgb参数, json格式",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--eval_result_path":{
|
||
"type":"str",
|
||
"item_type":"",
|
||
"label":"模型评估报告保存路径",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"模型评估报告保存路径。默认为空,不进行模型评估。",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--model_save_path":{
|
||
"type":"str",
|
||
"item_type":"",
|
||
"label":"模型文件保存路径",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"模型文件保存路径。为空则不保存模型。",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
},
|
||
"离线推理":{
|
||
"--model_load_path":{
|
||
"type":"str",
|
||
"item_type":"",
|
||
"label":"模型加载路径",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"模型加载路径。为空则不加载。",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--predict_csv_file_path":{
|
||
"type":"str",
|
||
"item_type":"",
|
||
"label":"预测数据集csv路径",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"预测数据集csv路径,格式和训练集一致,顺序保持一致,没有label列。为空则不做predict。",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--predict_result_path":{
|
||
"type":"str",
|
||
"item_type":"",
|
||
"label":"预测结果保存路径",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"预测结果保存路径,为空则不做predict。",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
|
||
"tfjob-runner":{
|
||
"project_name":"tf分布式",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/tf2.3_keras_train:latest",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/tf_keras_train",
|
||
"image_describe":"tf分布式-runner方式",
|
||
"job_template_name":"tfjob-runner",
|
||
"job_template_describe":"tf分布式-runner方式",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"kubeflow-pipeline",
|
||
"job_template_env":"NO_RESOURCE_CHECK=true\nTASK_RESOURCE_CPU=4\nTASK_RESOURCE_MEMORY=4G\nTASK_RESOURCE_GPU=0",
|
||
"job_template_expand":{
|
||
"index":2,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/tf_keras_train"
|
||
},
|
||
"job_template_args":{
|
||
"参数":{
|
||
"--job":{
|
||
"type":"json",
|
||
"item_type":"str",
|
||
"label":"模型训练,json配置",
|
||
"require":1,
|
||
"choice":[
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"模型训练,json配置",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--upstream-output-file":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"上游输出文件",
|
||
"require":0,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"上游输出文件",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"tfjob-plain":{
|
||
"project_name":"tf分布式",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/tf2.3_plain_train:latest",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/tf_plain_train",
|
||
"image_describe":"tf分布式-plain方式",
|
||
"job_template_name":"tfjob-plain",
|
||
"job_template_describe":"tf分布式-plain方式",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"kubeflow-pipeline",
|
||
"job_template_env":"NO_RESOURCE_CHECK=true\nTASK_RESOURCE_CPU=4\nTASK_RESOURCE_MEMORY=4G\nTASK_RESOURCE_GPU=0",
|
||
"job_template_expand":{
|
||
"index":3,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/tf_plain_train"
|
||
},
|
||
"job_template_args":{
|
||
"参数":{
|
||
"--job":{
|
||
"type":"json",
|
||
"item_type":"str",
|
||
"label":"模型训练,json配置",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"模型训练,json配置",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--upstream-output-file":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"上游输出文件",
|
||
"require":0,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"上游输出文件",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"tfjob-train":{
|
||
"project_name":"tf分布式",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/tf_distributed_train:latest",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/tf_distributed_train",
|
||
"image_describe":"tf分布式训练",
|
||
"job_template_name":"tfjob-train",
|
||
"job_template_describe":"tf分布式训练,内部支持plain和runner两种方式",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"kubeflow-pipeline",
|
||
"job_template_env":"NO_RESOURCE_CHECK=true\nTASK_RESOURCE_CPU=4\nTASK_RESOURCE_MEMORY=4G\nTASK_RESOURCE_GPU=0",
|
||
"job_template_expand":{
|
||
"index":4,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/tf_distributed_train"
|
||
},
|
||
"job_template_args":{
|
||
"参数":{
|
||
"--job":{
|
||
"type":"json",
|
||
"item_type":"str",
|
||
"label":"模型训练,json配置",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"模型训练,json配置",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--upstream-output-file":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"上游输出文件",
|
||
"require":0,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"上游输出文件",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"tf-model-evaluation":{
|
||
"project_name":"tf分布式",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/tf2.3_model_evaluation:latest",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/tf_model_evaluation",
|
||
"image_describe":"tensorflow2.3模型评估",
|
||
"job_template_name":"tf-model-evaluation",
|
||
"job_template_describe":"tensorflow2.3模型评估",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"kubeflow-pipeline",
|
||
"job_template_env":"NO_RESOURCE_CHECK=true\nTASK_RESOURCE_CPU=4\nTASK_RESOURCE_MEMORY=4G\nTASK_RESOURCE_GPU=0",
|
||
"job_template_expand":{
|
||
"index":5,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/tf_model_evaluation"
|
||
},
|
||
"job_template_args":{
|
||
"参数":{
|
||
"--job":{
|
||
"type":"json",
|
||
"item_type":"str",
|
||
"label":"模型对比评估,json配置",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"模型对比评估,json配置",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--upstream-output-file":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"上游输出文件",
|
||
"require":0,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"上游输出文件",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"tf-distribute-model-evaluation":{
|
||
"project_name":"tf分布式",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/tf_distributed_eval:latest",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/tf_distributed_evaluation",
|
||
"image_describe":"tensorflow2.3分布式模型评估",
|
||
"job_template_name":"tf-distribute-model-evaluation",
|
||
"job_template_describe":"tensorflow2.3分布式模型评估",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"kubeflow-pipeline",
|
||
"job_template_env":"NO_RESOURCE_CHECK=true\nTASK_RESOURCE_CPU=4\nTASK_RESOURCE_MEMORY=4G\nTASK_RESOURCE_GPU=0",
|
||
"job_template_expand":{
|
||
"index":6,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/tf_distributed_evaluation"
|
||
},
|
||
"job_template_args":{
|
||
"参数":{
|
||
"--job":{
|
||
"type":"json",
|
||
"item_type":"str",
|
||
"label":"模型评估,json配置",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"模型评估,json配置",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--upstream-output-file":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"上游输出文件",
|
||
"require":0,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"上游输出文件",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"tf-model-offline-predict":{
|
||
"project_name":"tf分布式",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/tf_model_offline_predict:latest",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/tf_model_offline_predict",
|
||
"image_describe":"tf模型离线推理",
|
||
"job_template_name":"tf-model-offline-predict",
|
||
"job_template_describe":"tf模型离线推理",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"",
|
||
"job_template_env":"",
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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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||
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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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||
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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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||
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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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||
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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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|
||
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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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|
||
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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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||
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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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||
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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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||
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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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||
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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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||
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|
||
"image_describe":"mxnet分布式训练",
|
||
"job_template_name":"mxnet",
|
||
"job_template_describe":"mxnet 分布式训练",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"kubeflow-pipeline",
|
||
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|
||
"job_template_expand":{
|
||
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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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|
||
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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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||
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|
||
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|
||
"--working_dir": {
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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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||
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|
||
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|
||
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||
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||
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|
||
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|
||
"--command": {
|
||
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|
||
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|
||
"label": "启动命令,例如 python3 xxx.py",
|
||
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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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||
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|
||
},
|
||
"--num_worker": {
|
||
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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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|
||
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|
||
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|
||
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|
||
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|
||
},
|
||
"--num_ps": {
|
||
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|
||
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|
||
"label": "分布式训练ps的数目",
|
||
"require": 1,
|
||
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|
||
"range": "",
|
||
"default": "0",
|
||
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|
||
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|
||
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|
||
"condition": "",
|
||
"sub_args": {}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"kaldi":{
|
||
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|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/kaldi_distributed_on_volcano:v2",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/kaldi_distributed_on_volcanojob",
|
||
"image_describe":"kaldi音频分布式",
|
||
"job_template_name":"kaldi",
|
||
"job_template_old_names": ["kaldi-distributed-on-volcanojob"],
|
||
"job_template_describe":"kaldi音频分布式训练",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"kubeflow-pipeline",
|
||
"job_template_env":"NO_RESOURCE_CHECK=true\nTASK_RESOURCE_CPU=4\nTASK_RESOURCE_MEMORY=4G\nTASK_RESOURCE_GPU=0",
|
||
"job_template_expand":{
|
||
"index":6,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/kaldi_distributed_on_volcanojob"
|
||
},
|
||
"job_template_args":{
|
||
"参数":{
|
||
"--working_dir":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"/mnt/xx",
|
||
"placeholder":"启动目录",
|
||
"describe":"启动目录",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--user_cmd":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"./run.sh",
|
||
"placeholder":"启动命令",
|
||
"describe":"启动命令",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--num_worker":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"2",
|
||
"placeholder":"worker数量",
|
||
"describe":"worker数量",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--image":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"ccr.ccs.tencentyun.com/cube-studio/kaldi_distributed_worker:v1",
|
||
"placeholder":"",
|
||
"describe":"worker镜像,直接运行你代码的环境镜像 <a target='_blank' href='https://github.com/tencentmusic/cube-studio/tree/master/images'>基础镜像</a>",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"media-download":{
|
||
"project_name":"多媒体类模板",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/video-audio:20210601",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/video-audio",
|
||
"image_describe":"分布式媒体文件处理",
|
||
"job_template_name":"media-download",
|
||
"job_template_describe":"分布式下载媒体文件",
|
||
"job_template_command":"python start_download.py",
|
||
"job_template_volume":"2G(memory):/dev/shm",
|
||
"job_template_account":"kubeflow-pipeline",
|
||
"job_template_expand":{
|
||
"index":1,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/video-audio"
|
||
},
|
||
"job_template_args":{
|
||
"参数":{
|
||
"--num_worker":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"分布式任务的worker数目",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"3",
|
||
"placeholder":"分布式任务的worker数目",
|
||
"describe":"分布式任务的worker数目",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--download_type":{
|
||
"type":"enum",
|
||
"item_type":"str",
|
||
"label":"下载类型",
|
||
"require":1,
|
||
"choice":[
|
||
"url"
|
||
],
|
||
"range":"",
|
||
"default":"url",
|
||
"placeholder":"",
|
||
"describe":"下载类型",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--input_file":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"下载信息文件地址",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"下载信息文件地址<br>url类型,每行格式:$url $local_path",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"video-img":{
|
||
"project_name":"多媒体类模板",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/video-audio:20210601",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/video-audio",
|
||
"image_describe":"分布式媒体文件处理",
|
||
"job_template_name":"video-img",
|
||
"job_template_describe":"视频提取图片(分布式版)",
|
||
"job_template_command":"python start_video_img.py",
|
||
"job_template_volume":"2G(memory):/dev/shm",
|
||
"job_template_account":"kubeflow-pipeline",
|
||
"job_template_expand":{
|
||
"index":2,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/video-audio"
|
||
},
|
||
"job_template_args":{
|
||
"参数":{
|
||
"--num_workers":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"3",
|
||
"placeholder":"",
|
||
"describe":"worker数量",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--input_file":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"配置文件地址,每行格式:<br>$local_video_path $des_img_dir $frame_rate",
|
||
"describe":"配置文件地址,每行格式:<br>$local_video_path $des_img_dir $frame_rate",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"video-audio":{
|
||
"project_name":"多媒体类模板",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/video-audio:20210601",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/video-audio",
|
||
"image_describe":"分布式媒体文件处理",
|
||
"job_template_name":"video-audio",
|
||
"job_template_describe":"视频提取音频(分布式版)",
|
||
"job_template_command":"python start_video_audio.py",
|
||
"job_template_volume":"2G(memory):/dev/shm",
|
||
"job_template_account":"kubeflow-pipeline",
|
||
"job_template_expand":{
|
||
"index":3,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/video-audio"
|
||
},
|
||
"job_template_args":{
|
||
"参数":{
|
||
"--num_workers":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"worker数量",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"3",
|
||
"placeholder":"",
|
||
"describe":"worker数量",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--input_file":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"配置文件地址,每行格式:<br>$local_video_path $des_audio_path",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"object-detection-on-darknet":{
|
||
"project_name":"多媒体类模板",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/object_detection_on_darknet:v1",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/object_detection_on_darknet",
|
||
"image_describe":"yolo目标识别",
|
||
"job_template_name":"object-detection-on-darknet",
|
||
"job_template_describe":"yolo目标识别",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"",
|
||
"job_template_env":"",
|
||
"job_template_expand":{
|
||
"index":4,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/object_detection_on_darknet"
|
||
},
|
||
"job_template_args":{
|
||
"参数": {
|
||
"--train_cfg": {
|
||
"type": "text",
|
||
"item_type": "str",
|
||
"label": "模型参数配置、训练配置",
|
||
"require": 1,
|
||
"choice": [],
|
||
"range": "",
|
||
"default": "[net]\n# Testing\n# batch=1\n# subdivisions=1\n# Training\nbatch=64\nsubdivisions=16\nwidth=608\nheight=608\nchannels=3\nmomentum=0.9\ndecay=0.0005\nangle=0\nsaturation = 1.5\nexposure = 1.5\nhue=.1\n\nlearning_rate=0.001\nburn_in=1000\nmax_batches = 50150\npolicy=steps\nsteps=400000,450000\nscales=.1,.1\n\n[convolutional]\nbatch_normalize=1\nfilters=32\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n# Downsample\n\n[convolutional]\nbatch_normalize=1\nfilters=64\nsize=3\nstride=2\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=32\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=64\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n# Downsample\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=3\nstride=2\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=64\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n[convolutional]\nbatch_normalize=1\nfilters=64\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n# Downsample\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=3\nstride=2\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n# Downsample\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=3\nstride=2\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n# Downsample\n\n[convolutional]\nbatch_normalize=1\nfilters=1024\nsize=3\nstride=2\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=1024\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=1024\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=1024\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=1024\nsize=3\nstride=1\npad=1\nactivation=leaky\n\n[shortcut]\nfrom=-3\nactivation=linear\n\n######################\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nsize=3\nstride=1\npad=1\nfilters=1024\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nsize=3\nstride=1\npad=1\nfilters=1024\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=512\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nsize=3\nstride=1\npad=1\nfilters=1024\nactivation=leaky\n\n[convolutional]\nsize=1\nstride=1\npad=1\nfilters=255\nactivation=linear\n\n\n[yolo]\nmask = 6,7,8\nanchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326\nclasses=80\nnum=9\njitter=.3\nignore_thresh = .7\ntruth_thresh = 1\nrandom=1\n\n\n[route]\nlayers = -4\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[upsample]\nstride=2\n\n[route]\nlayers = -1, 61\n\n\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nsize=3\nstride=1\npad=1\nfilters=512\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nsize=3\nstride=1\npad=1\nfilters=512\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=256\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nsize=3\nstride=1\npad=1\nfilters=512\nactivation=leaky\n\n[convolutional]\nsize=1\nstride=1\npad=1\nfilters=255\nactivation=linear\n\n\n[yolo]\nmask = 3,4,5\nanchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326\nclasses=80\nnum=9\njitter=.3\nignore_thresh = .7\ntruth_thresh = 1\nrandom=1\n\n\n\n[route]\nlayers = -4\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[upsample]\nstride=2\n\n[route]\nlayers = -1, 36\n\n\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nsize=3\nstride=1\npad=1\nfilters=256\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nsize=3\nstride=1\npad=1\nfilters=256\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nfilters=128\nsize=1\nstride=1\npad=1\nactivation=leaky\n\n[convolutional]\nbatch_normalize=1\nsize=3\nstride=1\npad=1\nfilters=256\nactivation=leaky\n\n[convolutional]\nsize=1\nstride=1\npad=1\nfilters=255\nactivation=linear\n\n\n[yolo]\nmask = 0,1,2\nanchors = 10,13, 16,30, 33,23, 30,61, 62,45, 59,119, 116,90, 156,198, 373,326\nclasses=80\nnum=9\njitter=.3\nignore_thresh = .7\ntruth_thresh = 1\nrandom=1\n\n",
|
||
"placeholder": "",
|
||
"describe": "模型参数配置、训练配置",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
},
|
||
"--data_cfg": {
|
||
"type": "text",
|
||
"item_type": "str",
|
||
"label": "训练数据配置",
|
||
"require": 1,
|
||
"choice": [],
|
||
"range": "",
|
||
"default": "classes= 80\ntrain = /root/darknet/coco_data/coco/trainvalno5k.txt\n#valid = coco_testdev\nvalid = /root/darknet/coco_data/coco/5k.txt\nnames = /root/darknet/data/coco.names\nbackup = /root/darknet/backup\neval=coco\n\n",
|
||
"placeholder": "",
|
||
"describe": "训练数据配置",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
},
|
||
"--weights": {
|
||
"type": "str",
|
||
"item_type": "str",
|
||
"label": "预训练模型权重文件",
|
||
"require": 1,
|
||
"choice": [],
|
||
"range": "",
|
||
"default": "",
|
||
"placeholder": "",
|
||
"describe": "预训练模型权重文件",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"ner":{
|
||
"project_name":"多媒体类模板",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/ner:20220812",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/ner",
|
||
"image_describe":"ner命名实体识别",
|
||
"job_template_name":"ner",
|
||
"job_template_describe":"ner命名实体识别",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"",
|
||
"job_template_env":"",
|
||
"job_template_expand":{
|
||
"index":5,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/ner"
|
||
},
|
||
"job_template_args":{
|
||
"参数": {
|
||
"--model": {
|
||
"type": "str",
|
||
"item_type": "str",
|
||
"label": "训练的基础模型名称,这里固定为: BiLSTM_CRF",
|
||
"require": 1,
|
||
"choice": [],
|
||
"range": "",
|
||
"default": "BiLSTM_CRF",
|
||
"placeholder": "",
|
||
"describe": "训练的基础模型名称,这里固定为: BiLSTM_CRF",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
},
|
||
"--path": {
|
||
"type": "str",
|
||
"item_type": "str",
|
||
"label": "训练数据存放目录",
|
||
"require": 1,
|
||
"choice": [],
|
||
"range": "",
|
||
"default": "/mnt/admin/NER/zdata/",
|
||
"placeholder": "",
|
||
"describe": "训练数据存放目录",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
},
|
||
"--filename": {
|
||
"type": "str",
|
||
"item_type": "str",
|
||
"label": "数据集的名字",
|
||
"require": 1,
|
||
"choice": [
|
||
"resume_BIO.txt",
|
||
"people_daily_BIO.txt"
|
||
],
|
||
"range": "",
|
||
"default": "resume_BIO.txt",
|
||
"placeholder": "",
|
||
"describe": " 数据集的名字",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
},
|
||
"--epochs": {
|
||
"type": "str",
|
||
"item_type": "str",
|
||
"label": "训练的次数,次数越大效果越好,建议 5 以上",
|
||
"require": 1,
|
||
"choice": [],
|
||
"range": "",
|
||
"default": "5",
|
||
"placeholder": "",
|
||
"describe": "训练的次数,次数越大效果越好,建议 5 以上",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
},
|
||
|
||
"-pp": {
|
||
"type": "str",
|
||
"item_type": "str",
|
||
"label": "模型保存地址",
|
||
"require": 1,
|
||
"choice": [],
|
||
"range": "",
|
||
"default": "/mnt/admin/model.pkl",
|
||
"placeholder": "",
|
||
"describe": "模型保存地址",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"model-register":{
|
||
"project_name":"模型服务化",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/model:20221001",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/model_register",
|
||
"image_describe":"注册模型",
|
||
"job_template_name":"model-register",
|
||
"job_template_describe":"注册模型",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"",
|
||
"job_template_env":"",
|
||
"job_template_expand":{
|
||
"index":1,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/model_register"
|
||
},
|
||
"job_template_args":{
|
||
"参数": {
|
||
"--project_name": {
|
||
"type": "str",
|
||
"item_type": "str",
|
||
"label": "部署项目名",
|
||
"require": 1,
|
||
"choice": [],
|
||
"range": "",
|
||
"default": "public",
|
||
"placeholder": "",
|
||
"describe": "部署项目名",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
},
|
||
"--model_name": {
|
||
"type": "str",
|
||
"item_type": "str",
|
||
"label": "模型名",
|
||
"require": 1,
|
||
"choice": [],
|
||
"range": "",
|
||
"default": "",
|
||
"placeholder": "",
|
||
"describe": "模型名",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
},
|
||
"--model_version": {
|
||
"type": "str",
|
||
"item_type": "str",
|
||
"label": "模型版本号",
|
||
"require": 1,
|
||
"choice": [],
|
||
"range": "",
|
||
"default": "{{ datetime.datetime.now().strftime(\"v%Y.%m.%d.2\") }}",
|
||
"placeholder": "",
|
||
"describe": "模型版本号",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
},
|
||
"--model_path": {
|
||
"type": "str",
|
||
"item_type": "str",
|
||
"label": "模型地址",
|
||
"require": 1,
|
||
"choice": [],
|
||
"range": "",
|
||
"default": "",
|
||
"placeholder": "",
|
||
"describe": "模型地址",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
},
|
||
"--describe": {
|
||
"type": "str",
|
||
"item_type": "str",
|
||
"label": "模型描述",
|
||
"require": 1,
|
||
"choice": [],
|
||
"range": "",
|
||
"default": "",
|
||
"placeholder": "",
|
||
"describe": "模型描述",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
},
|
||
"--framework": {
|
||
"type": "str",
|
||
"item_type": "str",
|
||
"label": "模型框架",
|
||
"require": 1,
|
||
"choice": [
|
||
"xgb",
|
||
"tf",
|
||
"pytorch",
|
||
"onnx",
|
||
"tensorrt"
|
||
],
|
||
"range": "",
|
||
"default": "tf",
|
||
"placeholder": "",
|
||
"describe": "模型框架",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
},
|
||
"--inference_framework": {
|
||
"type": "str",
|
||
"item_type": "str",
|
||
"label": "推理框架",
|
||
"require": 1,
|
||
"choice": [
|
||
"tfserving",
|
||
"torch-server",
|
||
"onnxruntime",
|
||
"triton-server"
|
||
],
|
||
"range": "",
|
||
"default": "tfserving",
|
||
"placeholder": "",
|
||
"describe": "推理框架",
|
||
"editable": 1,
|
||
"condition": "",
|
||
"sub_args": {}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"model-offline-predict":{
|
||
"project_name":"模型服务化",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/volcano:offline-predict-20220101",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/model_offline_predict",
|
||
"image_describe":"分布式离线推理",
|
||
"job_template_name":"model-offline-predict",
|
||
"job_template_describe":"分布式离线推理",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"kubeflow-pipeline",
|
||
"job_template_env":"NO_RESOURCE_CHECK=true\nTASK_RESOURCE_CPU=4\nTASK_RESOURCE_MEMORY=4G\nTASK_RESOURCE_GPU=0",
|
||
"job_template_expand":{
|
||
"index":2,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/model_offline_predict"
|
||
},
|
||
"job_template_args":{
|
||
"参数":{
|
||
"--image":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"ccr.ccs.tencentyun.com/cube-studio/ubuntu-gpu:cuda10.1-cudnn7-python3.6",
|
||
"placeholder":"",
|
||
"describe":"worker镜像,直接运行你代码的环境镜像<a target='_blank' href='https://github.com/tencentmusic/cube-studio/tree/master/images'>基础镜像</a>",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--working_dir":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"启动目录",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"/mnt/xx",
|
||
"placeholder":"",
|
||
"describe":"启动目录",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--command":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"环境安装和任务启动命令",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"/mnt/xx/../start.sh",
|
||
"placeholder":"",
|
||
"describe":"环境安装和任务启动命令",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--num_worker":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"占用机器个数",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"3",
|
||
"placeholder":"",
|
||
"describe":"占用机器个数",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
}
|
||
}
|
||
},
|
||
"deploy-service":{
|
||
"project_name":"模型服务化",
|
||
"image_name":"ccr.ccs.tencentyun.com/cube-studio/deploy-service:20211001",
|
||
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/deploy-service",
|
||
"image_describe":"模型部署推理服务",
|
||
"job_template_name":"deploy-service",
|
||
"job_template_describe":"模型部署推理服务",
|
||
"job_template_command":"",
|
||
"job_template_volume":"",
|
||
"job_template_account":"kubeflow-pipeline",
|
||
"job_template_env":"",
|
||
"job_template_expand":{
|
||
"index":3,
|
||
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/deploy-service"
|
||
},
|
||
"job_template_args":{
|
||
"模型信息":{
|
||
"--label":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"中文描述描述",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"demo推理服务",
|
||
"placeholder":"",
|
||
"describe":"推理服务描述",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--model_name":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"模型名",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"模型名",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--model_version":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"模型版本号",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"v2022.10.01.1",
|
||
"placeholder":"",
|
||
"describe":"模型版本号",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--model_path":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"模型地址",
|
||
"require":0,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"模型地址",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
},
|
||
"部署信息":{
|
||
"--service_type":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"推理服务类型",
|
||
"require":1,
|
||
"choice":[
|
||
"serving",
|
||
"tfserving",
|
||
"torch-server",
|
||
"onnxruntime",
|
||
"triton-server"
|
||
],
|
||
"range":"",
|
||
"default":"service",
|
||
"placeholder":"",
|
||
"describe":"推理服务类型",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--images":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"推理服务镜像",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"推理服务镜像",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--working_dir":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"推理容器工作目录",
|
||
"require":0,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"推理容器工作目录,个人工作目录/mnt/$username",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--command":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"推理容器启动命令",
|
||
"require":0,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"推理容器启动命令",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--args":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"推理容器启动参数",
|
||
"require":0,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"推理容器启动参数",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--env":{
|
||
"type":"text",
|
||
"item_type":"str",
|
||
"label":"推理容器环境变量",
|
||
"require":0,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"",
|
||
"placeholder":"",
|
||
"describe":"推理容器环境变量",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--ports":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"推理容器暴露端口",
|
||
"require":0,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"80",
|
||
"placeholder":"",
|
||
"describe":"推理容器暴露端口",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--replicas":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"pod副本数",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"1",
|
||
"placeholder":"",
|
||
"describe":"pod副本数",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--resource_memory":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"每个pod占用内存",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"2G",
|
||
"placeholder":"",
|
||
"describe":"每个pod占用内存",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--resource_cpu":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"每个pod占用cpu",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"2",
|
||
"placeholder":"",
|
||
"describe":"每个pod占用cpu",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
},
|
||
"--resource_gpu":{
|
||
"type":"str",
|
||
"item_type":"str",
|
||
"label":"每个pod占用gpu",
|
||
"require":1,
|
||
"choice":[
|
||
|
||
],
|
||
"range":"",
|
||
"default":"0",
|
||
"placeholder":"",
|
||
"describe":"每个pod占用gpu",
|
||
"editable":1,
|
||
"condition":"",
|
||
"sub_args":{
|
||
|
||
}
|
||
}
|
||
}
|
||
}
|
||
}
|
||
}
|