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cube-studio/myapp/init-job-template.json
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2022-08-22 13:29:21 +08:00

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{
"自定义镜像":{
"project_name":"基础命令",
"image_name":"ubuntu:18.04",
"gitpath": "",
"image_describe":"开源ubuntu:18.04基础镜像",
"job_template_name":"自定义镜像",
"job_template_describe":"使用用户自定义镜像作为运行镜像",
"job_template_expand":{
"index":1
},
"job_template_args":{
"参数":{
"images":{
"type":"str",
"item_type":"str",
"label":"要调试的镜像",
"require":1,
"choice":[
],
"range":"",
"default":"ccr.ccs.tencentyun.com/cube-studio/ubuntu-gpu:cuda10.1-cudnn7-python3.6",
"placeholder":"",
"describe":"要调试的镜像，<a target='_blank' href='https://github.com/tencentmusic/cube-studio/tree/master/images'>基础镜像参考<a>",
"editable":1,
"condition":"",
"sub_args":{
}
},
"workdir":{
"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":"启动命令",
"require":1,
"choice":[
],
"range":"",
"default":"sh start.sh",
"placeholder":"",
"describe":"启动命令",
"editable":1,
"condition":"",
"sub_args":{
}
}
}
}
},
"datax":{
"project_name":"数据导入导出",
"image_name":"ccr.ccs.tencentyun.com/cube-studio/datax:latest",
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/datax",
"image_describe":"datax异构数据源同步",
"job_template_name":"datax",
"job_template_describe":"datax异构数据源同步",
"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/datax"
},
"job_template_args":{
"参数":{
"-f":{
"type":"str",
"item_type":"str",
"label":"job.json文件地址，<a target='_blank' href='https://github.com/alibaba/DataX'>书写格式参考</a>",
"require":1,
"choice":[
],
"range":"",
"default":"/usr/local/datax/job/job.json",
"placeholder":"",
"describe":"job.json文件地址，<a target='_blank' href='https://github.com/alibaba/DataX'>书写格式参考</a>",
"editable":1,
"condition":"",
"sub_args":{
}
}
}
}
},
"hadoop":{
"project_name":"数据处理",
"image_name":"ccr.ccs.tencentyun.com/cube-studio/hadoop:20221010",
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/hadoop",
"image_describe":"hadoop大数据组件客户端",
"job_template_name":"hadoop",
"job_template_describe":"hadoop大数据组件，hdfs,hbase,sqoop,spark",
"job_template_command":"",
"job_template_volume":"",
"job_template_account":"",
"job_template_expand":{
"index":0,
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/hadoop"
},
"job_template_env":"",
"job_template_args":{
"参数":{
"--command": {
"type": "str",
"item_type": "str",
"label": "执行命令",
"require": 1,
"choice": [],
"range": "",
"default": "spark-submit xx",
"placeholder": "",
"describe": "执行命令",
"editable": 1,
"condition": "",
"sub_args": {}
}
}
}
},
"volcanojob":{
"project_name":"数据处理",
"image_name":"ccr.ccs.tencentyun.com/cube-studio/volcano:20211001",
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/volcano",
"image_describe":"有序分布式任务",
"job_template_name":"volcanojob",
"job_template_describe":"有序分布式任务",
"job_template_command":"",
"job_template_volume":"",
"job_template_account":"kubeflow-pipeline",
"job_template_expand":{
"index":1,
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/volcano"
},
"job_template_env":"NO_RESOURCE_CHECK=true\nTASK_RESOURCE_CPU=2\nTASK_RESOURCE_MEMORY=4G\nTASK_RESOURCE_GPU=0",
"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":"启动命令",
"require":1,
"choice":[
],
"range":"",
"default":"echo aa",
"placeholder":"",
"describe":"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":{
}
}
}
}
},
"ray":{
"project_name":"数据处理",
"image_name":"ccr.ccs.tencentyun.com/cube-studio/ray:gpu-20210601",
"gitpath": "https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/ray",
"image_describe":"ray分布式任务",
"job_template_name":"ray",
"job_template_describe":"python多机分布式任务",
"job_template_command":"",
"job_template_volume":"",
"job_template_account":"kubeflow-pipeline",
"job_template_expand":{
"index":2,
"help_url":"https://github.com/tencentmusic/cube-studio/tree/master/job-template/job/ray"
},
"job_template_args":{
"参数":{
"-n":{
"type":"str",
"item_type":"",
"label":"分布式任务worker的数量",
"require":1,
"choice":[
],
"range":"$min,$max",
"default":"3",
"placeholder":"",
"describe":"分布式任务worker的数量",
"editable":1,
"condition":"",
"sub_args":{
}
},
"-i":{
"type":"str",
"item_type":"str",
"label":"每个worker的初始化脚本文件地址，用来安装环境",
"require":0,
"choice":[
],
"range":"",
"default":"",
"placeholder":"每个worker的初始化脚本文件地址，用来安装环境",
"describe":"每个worker的初始化脚本文件地址，用来安装环境",
"editable":1,
"condition":"",
"sub_args":{
}
},
"-f":{
"type":"str",
"item_type":"str",
"label":"python启动命令，例如 python3 /mnt/xx/xx.py",
"require":1,
"choice":[
],
"range":"",
"default":"python /mnt/admin/demo.py",
"placeholder":"",
"describe":"python启动命令，例如 python3 /mnt/xx/xx.py",
"editable":1,
"condition":"",
"sub_args":{
}
}
}
}
},
"sparkjob":{
"project_name":"数据处理",
"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",
"job_template_describe":"spark serverless分布式任务",
"job_template_command":"",
"job_template_volume":"",
"job_template_account":"kubeflow-pipeline",
"job_template_expand":{
"index":3,
"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":{
"参数":{
"--image": {
"type": "str",
"item_type": "str",
"label": "执行镜像",
"require": 1,
"choice": [],
"range": "",
"default": "ccr.ccs.tencentyun.com/cube-studio/spark-operator:spark-v3.1.1",
"placeholder": "",
"describe": "执行镜像",
"editable": 1,
"condition": "",
"sub_args": {}
},
"--num_worker": {
"type": "str",
"item_type": "str",
"label": "executor 数目",
"require": 1,
"choice": [],
"range": "",
"default": "3",
"placeholder": "",
"describe": "executor 数目",
"editable": 1,
"condition": "",
"sub_args": {}
},
"--code_type": {
"type": "str",
"item_type": "str",
"label": "语言类型",
"require": 1,
"choice": [
"Java",
"Python",
"Scala",
"R"
],
"range": "",
"default": "Python",
"placeholder": "",
"describe": "语言类型",
"editable": 1,
"condition": "",
"sub_args": {}
},
"--code_class": {
"type": "str",
"item_type": "str",
"label": "Java/Scala类名",
"require": 0,
"choice": [],
"range": "",
"default": "",
"placeholder": "",
"describe": "Java/Scala类名，其他语言下不填",
"editable": 1,
"condition": "",
"sub_args": {}
},
"--code_file": {
"type": "str",
"item_type": "str",
"label": "代码文件地址",
"require": 1,
"choice": [],
"range": "",
"default": "local:///opt/spark/examples/src/main/python/pi.py",
"placeholder": "",
"describe": "代码文件地址，支持local://,http://,hdfs://,s3a://,gcs://",
"editable": 1,
"condition": "",
"sub_args": {}
},
"--code_arguments": {
"type": "str",
"item_type": "str",
"label": "代码参数",
"require": 0,
"choice": [],
"range": "",
"default": "",
"placeholder": "",
"describe": "代码参数",
"editable": 1,
"condition": "",
"sub_args": {}
},
"--sparkConf": {
"type": "text",
"item_type": "str",
"label": "spark配置",
"require": 0,
"choice": [],
"range": "",
"default": "",
"placeholder": "",
"describe": "spark配置，每行一个配置，xx=yy",
"editable": 1,
"condition": "",
"sub_args": {}
},
"--hadoopConf": {
"type": "text",
"item_type": "str",
"label": "hadoop配置，每行一个配置，xx=yy",
"require": 0,
"choice": [],
"range": "",
"default": "",
"placeholder": "",
"describe": "hadoop配置",
"editable": 1,
"condition": "",
"sub_args": {}
}
}
}
},
"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":"",
"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,
"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":{
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"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":{
}
}
}
}
}
}
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