添加初始化示例

This commit is contained in:
data-infra 2023-12-11 09:59:38 +08:00
parent 899bd41538
commit fdd5afd848
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[
{
"job_type": "Job",
"project": "public",
"name": "test",
"namespace": "automl",
"describe": "nni功能测试",
"parallel_trial_count": 3,
"max_trial_count": 12,
"objective_type": "maximize",
"objective_goal": 0.99,
"objective_metric_name": "accuracy",
"algorithm_name": "Random",
"parameters": {
"batch_size": {"_type":"choice", "_value": [16, 32, 64, 128]},
"momentum":{"_type":"uniform","_value":[0, 1]}
},
"job_json": {
},
"job_worker_image": "ccr.ccs.tencentyun.com/cube-studio/nni:20230601",
"working_dir": "/mnt/admin/pipeline/example/nni/",
"job_worker_command": "python demo.py",
"resource_memory": "1G",
"resource_cpu": "1",
"resource_gpu": "0"
}
]

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name,label,describe,source_type,source,industry,field,usage,research,storage_class,file_type,status,years,url,path,download_url,storage_size,entries_num,duration,price,status,icon,owner
MNIST,手写数字数据集,"包含一组60,000个示例的训练集和一组10,000个示例的测试集。数字已经过尺寸标准化以适合 20x20 像素框,同时保持其纵横比,并在固定尺寸的图像中居中",开源,github,图像处理,视觉,传统机器学习和深度学习入门,svm、分类,压缩,gz,正常,,http://yann.lecun.com/exdb/mnist/,,"http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz
http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz
http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz
http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz",11M," 60,000 个示例的训练集和 10,000 个示例的测试集",,0,正常,/static/assets/images/dataset/mnist.png,admin
Fashion-MNIST,时尚产品数据,"包含60,000个训练图像和10,000个测试图像。类似MNIST的时尚产品数据库。",开源,github,图像处理,视觉,传统机器学习和深度学习入门,图像分类,压缩,gz,正常,,https://github.com/zalandoresearch/fashion-mnist,,"http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz
http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz
http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz
http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz",5M,"60,000个训练图像和10,000个测试图像",,0,正常,/static/assets/images/dataset/fashion-mnist.png,admin
1 name label describe source_type source industry field usage research storage_class file_type status years url path download_url storage_size entries_num duration price status icon owner
2 MNIST 手写数字数据集 包含一组60,000个示例的训练集和一组10,000个示例的测试集。数字已经过尺寸标准化,以适合 20x20 像素框,同时保持其纵横比,并在固定尺寸的图像中居中 开源 github 图像处理 视觉 传统机器学习和深度学习入门 svm、分类 压缩 gz 正常 http://yann.lecun.com/exdb/mnist/ http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz 11M 60,000 个示例的训练集和 10,000 个示例的测试集 0 正常 /static/assets/images/dataset/mnist.png admin
3 Fashion-MNIST 时尚产品数据 包含60,000个训练图像和10,000个测试图像。类似MNIST的时尚产品数据库。 开源 github 图像处理 视觉 传统机器学习和深度学习入门 图像分类 压缩 gz 正常 https://github.com/zalandoresearch/fashion-mnist http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz 5M 60,000个训练图像和10,000个测试图像 0 正常 /static/assets/images/dataset/fashion-mnist.png admin

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[
{
"name": "dau",
"describe": "dau计算",
"config": {
"alert_user": "admin"
},
"workflow": "airflow",
"dag_json": {
"cos导入hdfs-1686184253953": {
"label": "数据导入",
"location": [
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],
"color": {
"color": "rgba(0,170,200,1)",
"bg": "rgba(0,170,200,0.02)"
},
"template": "cos导入hdfs",
"template-group": "出库入库",
"task-config": {
"crontab": "1 1 * * *",
"selfDepend": "单实例运行",
"ResourceGroup": "default",
"alert_user": "admin,",
"timeout": "0",
"retry": "0",
"hdfsPath": "hdfs://xx/xxx",
"cosPath": "/xx/${YYYYMMDD}.tar.gz",
"ifNeedZip": "1",
"label": "数据导入"
},
"upstream": [],
"task_id": 1
},
"hdfs入库至hive-1686184263002": {
"label": "数据入库",
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"color": {
"color": "rgba(0,170,200,1)",
"bg": "rgba(0,170,200,0.02)"
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"template": "hdfs入库至hive",
"template-group": "出库入库",
"task-config": {
"crontab": "1 1 * * *",
"selfDepend": "单实例运行",
"ResourceGroup": "default",
"alert_user": "admin,",
"timeout": "0",
"retry": "0",
"charSet": "UTF-8",
"databaseName": "",
"tableName": "",
"delimiter": "9",
"failedOnZeroWrited": "1",
"partitionType": "P_${YYYYMMDDHH}",
"sourceFilePath": "",
"sourceFileNames": "*",
"sourceColumnNames": "",
"targetColumnNames": "",
"loadMode": "TRUNCATE",
"label": "数据入库"
},
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],
"task_id": 2
},
"SQL-1686184276800": {
"label": "局部特征计算",
"location": [
-16,
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],
"color": {
"color": "rgba(0,200,153,1)",
"bg": "rgba(0,200,153,0.02)"
},
"template": "SQL",
"template-group": "数据计算",
"task-config": {
"crontab": "1 1 * * *",
"selfDepend": "单实例运行",
"ResourceGroup": "default",
"alert_user": "admin,",
"timeout": "0",
"retry": "0",
"filterSQL": "\n --库名替换下面的demo_database\n use demo_database;\n\n --建表语句替换下面的demo_table修改字段。一定要加“if not exists”这样使只在第一次运行时建表\n CREATE TABLE if not exists demo_table(\n qimei36 STRING COMMENT '唯一设备ID',\n userid_id STRING COMMENT '用户id各app的用户id',\n device_id STRING COMMENT '设备id各app的device_id',\n ftime INT COMMENT '数据分区时间 格式yyyymmdd'\n )\n PARTITION BY LIST( ftime ) --定义分区字段替换掉ftime。\n (\n PARTITION p_20220323 VALUES IN ( 20220323 ), --初始分区分区名替换p_20220323分区值替换20220323\n PARTITION default\n )\n STORED AS ORCFILE COMPRESS;\n\n -- 分区,根据时间参数新建分区。\n alter table demo_table drop partition (p_${YYYYMMDD});\n alter table demo_table add partition p_${YYYYMMDD} values in (${YYYYMMDD});\n\n -- 写入用你的sql逻辑替换。\n insert table demo_table\n select * from other_db::other_table partition(p_${YYYYMMDD}) t;\n ",
"special_para": "set hive.exec.parallel = true;set hive.execute.engine=spark;set hive.multi.join.use.hive=false;set hive.spark.failed.retry=false;",
"label": "局部特征计算"
},
"upstream": [
"hdfs入库至hive-1686184263002"
],
"task_id": 3
},
"SparkScala-1686184279367": {
"label": "局部特征计算",
"location": [
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],
"color": {
"color": "rgba(0,200,153,1)",
"bg": "rgba(0,200,153,0.02)"
},
"template": "SparkScala",
"template-group": "数据计算",
"task-config": {
"crontab": "1 1 * * *",
"selfDepend": "单实例运行",
"ResourceGroup": "default",
"alert_user": "admin,",
"timeout": "0",
"retry": "0",
"jar_path": "",
"className": "",
"files": "",
"programSpecificParams": "",
"options": "",
"dynamicAllocation": "1",
"driver_memory": "2g",
"num_executors": "4",
"executor_memory": "2g",
"executor_cores": "2",
"task.main.timeout": "480",
"task.check.timeout": "5",
"label": "局部特征计算"
},
"upstream": [
"hdfs入库至hive-1686184263002"
],
"task_id": 4
},
"pyspark-1686184281148": {
"label": "局部特征计算",
"location": [
608,
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],
"color": {
"color": "rgba(0,200,153,1)",
"bg": "rgba(0,200,153,0.02)"
},
"template": "pyspark",
"template-group": "数据计算",
"task-config": {
"crontab": "1 1 * * *",
"selfDepend": "单实例运行",
"ResourceGroup": "default",
"alert_user": "admin,",
"timeout": "0",
"retry": "0",
"py_script_path": "",
"files": "",
"pyFiles": "",
"programSpecificParams": "",
"options": "",
"dynamicAllocation": 1,
"driver_memory": "2g",
"num_executors": 4,
"executor_memory": "2g",
"executor_cores": 2,
"task.main.timeout": 480,
"task.check.timeout": "5",
"label": "局部特征计算"
},
"upstream": [
"hdfs入库至hive-1686184263002"
],
"task_id": 5
},
"hive出库至hdfs-1686184293917": {
"label": "结果计算",
"location": [
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],
"color": {
"color": "rgba(0,170,200,1)",
"bg": "rgba(0,170,200,0.02)"
},
"template": "hive出库至hdfs",
"template-group": "出库入库",
"task-config": {
"crontab": "1 1 * * *",
"selfDepend": "单实例运行",
"ResourceGroup": "default",
"alert_user": "admin,",
"timeout": "0",
"retry": "0",
"databaseName": "",
"destCheckFileName": "",
"destCheckFilePath": "",
"destFileDelimiter": "9",
"destFilePath": "",
"filterSQL": "select t1,t2,t3 from your_table where imp_date=${YYYYMMDD}",
"label": "结果计算"
},
"upstream": [
"SQL-1686184276800",
"pyspark-1686184281148",
"SparkScala-1686184279367"
],
"task_id": 6
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"hdfs导入cos-1686184296749": {
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304,
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],
"color": {
"color": "rgba(0,170,200,1)",
"bg": "rgba(0,170,200,0.02)"
},
"template": "hdfs导入cos",
"template-group": "出库入库",
"task-config": {
"crontab": "1 1 * * *",
"selfDepend": "单实例运行",
"ResourceGroup": "default",
"alert_user": "admin,",
"timeout": "0",
"retry": "0",
"hdfsPath": "hdfs://xx/xxx",
"cosPath": "/xx/xx/${YYYYMMDD}.tar.gz",
"ifNeedZip": "1",
"label": "数据导出"
},
"upstream": [
"hive出库至hdfs-1686184293917"
],
"task_id": 7
}
}
}
]

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[
{
"group_name": "基础命令",
"name": "ccr.ccs.tencentyun.com/cube-studio/python:strong",
"repository": "hubsecret",
"gitpath": "",
"describe": "丰富版本python镜像",
"dockerfile":"FROM python:3.9\n\nENV TZ=Asia/Shanghai\nENV DEBIAN_FRONTEND=noninteractive\n\nRUN pip config set global.index-url https://mirrors.aliyun.com/pypi/simple\n\nRUN pip install numpy \n\nWORKDIR /app\n\nEXPOSE 80"
}
]

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{
"tf-mnist": {
"project_name": "public",
"service_name": "mnist-202208011",
"model_name": "mnist",
"service_describe": "tf 图像分类",
"image_name": "ccr.ccs.tencentyun.com/cube-studio/tfserving:2.3.4",
"model_version": "v2022.08.01.1",
"model_path": "https://docker-76009.sz.gfp.tencent-cloud.com/github/cube-studio/inference/tf-mnist.tar.gz",
"service_type": "tfserving",
"env": "TF_CPP_VMODULE=http_server=1\nTZ=Asia/Shanghai",
"host": "/v1/models/mnist/metadata",
"ports": "8501",
"metrics": "8501:/metrics",
"command": "wget https://docker-76009.sz.gfp.tencent-cloud.com/github/cube-studio/inference/tf-mnist.tar.gz && tar -zxvf tf-mnist.tar.gz && mkdir -p /models/mnist/202207281/ && cp -r tf-mnist/* /models/mnist/202207281/ && /usr/bin/tf_serving_entrypoint.sh --model_config_file=/config/models.config --monitoring_config_file=/config/monitoring.config --platform_config_file=/config/platform.config",
"health": "8501:/v1/models/mnist/versions/202207281/metadata",
"volume_mount": "kubeflow-user-workspace(pvc):/mnt,kubeflow-archives(pvc):/archives",
"resource_memory": "2G",
"resource_cpu": "2",
"expand": {
"help_url": "https://github.com/tencentmusic/cube-studio/tree/master/images/serving/tfserving/example"
}
},
"pytorch-resnet50": {
"project_name": "public",
"service_name": "resnet50-202208012",
"model_name": "resnet50",
"service_describe": "pytorch 图像分类",
"image_name": "ccr.ccs.tencentyun.com/cube-studio/torchserve:0.5.3-cpu",
"model_version": "v2022.08.01.2",
"model_path": "https://docker-76009.sz.gfp.tencent-cloud.com/github/cube-studio/inference/resnet50.mar",
"service_type": "torch-server",
"env": "",
"host": "/models",
"ports": "8080,8081",
"metrics": "8082:/metrics",
"workdir": "/models",
"command": "wget https://docker-76009.sz.gfp.tencent-cloud.com/github/cube-studio/inference/resnet50.mar && mkdir -p /models && cp /config/* /models/ && cp resnet50.mar /models/ && torchserve --start --model-store /models --models resnet50=resnet50.mar --foreground --ts-config=/config/config.properties",
"health": "8080:/ping",
"volume_mount": "kubeflow-user-workspace(pvc):/mnt,kubeflow-archives(pvc):/archives",
"resource_memory": "5G",
"resource_cpu": "5",
"expand": {
"help_url": "https://github.com/tencentmusic/cube-studio/tree/master/images/serving/torchserver/example"
}
},
"torchscript-resnet50": {
"project_name": "public",
"service_name": "resnet50-202208013",
"model_name": "resnet50",
"service_describe": "torchscript 图像分类",
"image_name": "ccr.ccs.tencentyun.com/cube-studio/tritonserver:22.07-py3",
"model_version": "v2022.08.01.3",
"model_path": "https://docker-76009.sz.gfp.tencent-cloud.com/github/cube-studio/inference/resnet50-torchscript.pt",
"service_type": "triton-server",
"env": "",
"host": "/v2/models/resnet50",
"ports": "8000,8002",
"metrics": "",
"workdir": "",
"command": "wget https://docker-76009.sz.gfp.tencent-cloud.com/github/cube-studio/inference/resnet50-torchscript.pt && mkdir -p /models/resnet50/202208013/ && cp /config/* /models/resnet50/ && cp -r resnet50-torchscript.pt /models/resnet50/202208013/model.pt && tritonserver --model-repository=/models --strict-model-config=true --log-verbose=1",
"health": "8000:/v2/health/ready",
"volume_mount": "kubeflow-user-workspace(pvc):/mnt,kubeflow-archives(pvc):/archives",
"resource_memory": "5G",
"resource_cpu": "5",
"inference_config": "\n---config.pbtxt\n\nname: \"resnet50\"\nplatform: \"pytorch_libtorch\"\nmax_batch_size: 0\ninput \n[\n {\n name: \"INPUT__0\"\n data_type: TYPE_FP32\n format: FORMAT_NCHW\n dims: [ 3, 224, 224 ]\n reshape: {\n shape: [ 1, 3, 224, 224 ]\n }\n }\n]\n \noutput \n[\n {\n name: \"OUTPUT__0\"\n data_type: TYPE_FP32\n dims: [ 1000 ]\n reshape: {\n shape: [ 1, 1000 ]\n }\n }\n]\n \n\nparameters: { key: \"DISABLE_OPTIMIZED_EXECUTION\" value: { string_value:\"true\" } }\nparameters: { key: \"INFERENCE_MODE\" value: { string_value: \"false\" } }\n",
"expand": {
"help_url": "https://github.com/tencentmusic/cube-studio/tree/master/images/serving/triton-server/example"
}
},
"onnx-resnet50": {
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"service_name": "resnet50-202208014",
"model_name": "resnet50",
"service_describe": "onnx 图像分类",
"image_name": "ccr.ccs.tencentyun.com/cube-studio/tritonserver:22.07-py3",
"model_version": "v2022.08.01.4",
"model_path": "https://docker-76009.sz.gfp.tencent-cloud.com/github/cube-studio/inference/resnet50.onnx",
"service_type": "triton-server",
"env": "",
"host": "/v2/models/resnet50",
"ports": "8000,8002",
"metrics": "",
"workdir": "",
"command": "wget https://docker-76009.sz.gfp.tencent-cloud.com/github/cube-studio/inference/resnet50.onnx && mkdir -p /models/resnet50/202208014/ && cp /config/* /models/resnet50/ && cp -r resnet50.onnx /models/resnet50/202208014/model.onnx && tritonserver --model-repository=/models --strict-model-config=true --log-verbose=1",
"health": "8000:/v2/health/ready",
"volume_mount": "kubeflow-user-workspace(pvc):/mnt,kubeflow-archives(pvc):/archives",
"resource_memory": "5G",
"resource_cpu": "5",
"inference_config": "---config.pbtxt\n\nname: \"resnet50\"\nplatform: \"onnxruntime_onnx\"\nbackend: \"onnxruntime\"\nmax_batch_size : 0\n\ninput [\n {\n name: \"input_name\"\n data_type: TYPE_FP32\n format: FORMAT_NCHW\n dims: [ 3, 224, 224 ]\n reshape { shape: [ 1, 3, 224, 224 ] }\n }\n]\noutput [\n {\n name: \"output_name\"\n data_type: TYPE_FP32\n dims: [ 1000 ]\n reshape { shape: [ 1, 1000 ] }\n }\n]\n\nparameters { key: \"intra_op_thread_count\" value: { string_value: \"10\" } }\nparameters { key: \"execution_mode\" value: { string_value: \"1\" } }\nparameters { key: \"inter_op_thread_count\" value: { string_value: \"10\" } }\n",
"expand": {
"help_url": "https://github.com/tencentmusic/cube-studio/tree/master/images/serving/triton-server/example"
}
}
}

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[
{
"type": "org",
"name": "推荐中心",
"describe": "推荐项目组",
"expand": {}
},
{
"type": "org",
"name": "搜索中心",
"describe": "搜索项目组",
"expand": {}
},
{
"type": "org",
"name": "广告中心",
"describe": "广告项目组",
"expand": {}
}, {
"type": "org",
"name": "安全中心",
"describe": "安全项目组",
"expand": {}
}, {
"type": "org",
"name": "多媒体中心",
"describe": "多媒体项目组",
"expand": {}
}, {
"type": "job-template",
"name": "基础命令",
"describe": "python/bash等直接在服务器命令行中执行命令的模板",
"expand": {"index": 1}
}, {
"type": "job-template",
"name": "数据导入导出",
"describe": "集群与用户机器或其他集群之间的数据迁移",
"expand": {"index": 1}
}, {
"type": "job-template",
"name": "数据预处理",
"describe": "结构化话数据特征处理",
"expand": {"index": 1}
}, {
"type": "job-template",
"name": "数据处理工具",
"describe": "数据的单机或分布式处理任务,ray/spark/hadoop/volcanojob",
"expand": {"index": 1}
}, {
"type": "job-template",
"name": "基础命令",
"describe": "python/bash等直接在服务器命令行中执行命令的模板",
"expand": {"index": 1}
}, {
"type": "job-template",
"name": "特征处理",
"describe": "特征处理相关",
"expand": {"index": 1}
}, {
"type": "job-template",
"name": "机器学习框架",
"describe": "传统机器学习框架sklearn",
"expand": {"index": 1}
}, {
"type": "job-template",
"name": "机器学习算法",
"describe": "传统机器学习lr/决策树/gbdt/xgb/fm等",
"expand": {"index": 1}
}, {
"type": "job-template",
"name": "深度学习",
"describe": "深度框架训练tf/pytorch/mxnet/mpi/horovod/kaldi等",
"expand": {"index": 1}
}, {
"type": "job-template",
"name": "分布式加速",
"describe": "tf相关的训练模型校验离线预测等功能",
"expand": {"index": 1}
}, {
"type": "job-template",
"name": "tf分布式",
"describe": "tf相关的训练模型校验离线预测等功能",
"expand": {"index": 1}
}
]

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@ -0,0 +1,111 @@
{
"mysql-ui": {
"project_name": "public",
"service_name": "mysql-ui",
"service_describe": "可视化编辑mysql数据库",
"image_name": "ccr.ccs.tencentyun.com/cube-studio/phpmyadmin",
"command": "",
"env": "PMA_HOST=mysql-service.infra\nPMA_PORT=3306\nPMA_USER=root\nPMA_PASSWORD=admin",
"ports": "80",
"expand": {
"help_url": "https://github.com/tencentmusic/cube-studio/blob/master/docs/example/service.md"
}
},
"redis-ui": {
"project_name": "public",
"service_name": "redis-ui",
"service_describe": "可视化编辑redis数据库",
"image_name": "ccr.ccs.tencentyun.com/cube-studio/patrikx3:latest",
"command": "",
"env": "REDIS_NAME=default\nREDIS_HOST=redis-master.infra\nREDIS_PORT=6379\nREDIS_PASSWORD=admin",
"ports": "7843",
"expand": {
"help_url": "https://github.com/tencentmusic/cube-studio/blob/master/docs/example/service.md"
}
},
"mongo-express": {
"project_name": "public",
"service_name": "mongo-express",
"service_describe": "可视化编辑mongo数据库",
"image_name": "mongo-express:0.54.0",
"command": "",
"env": "ME_CONFIG_MONGODB_SERVER=xx.xx.xx.xx\nME_CONFIG_MONGODB_PORT=xx\nME_CONFIG_MONGODB_ENABLE_ADMIN=true\nME_CONFIG_MONGODB_ADMINUSERNAME=xx\nME_CONFIG_MONGODB_ADMINPASSWORD=xx\nME_CONFIG_MONGODB_AUTH_DATABASE=xx\nME_CONFIG_MONGODB_AUTH_USERNAME=xx\nME_CONFIG_MONGODB_AUTH_PASSWORD=xx\nVCAP_APP_HOST=0.0.0.0\nVCAP_APP_PORT=8081\nME_CONFIG_OPTIONS_EDITORTHEME=ambiance",
"ports": "8081",
"expand": {
"help_url": "https://github.com/tencentmusic/cube-studio/blob/master/docs/example/service.md"
}
},
"neo4j": {
"project_name": "public",
"service_name": "neo4j",
"service_describe": "可视化编辑图数据库neo4j",
"image_name": "ccr.ccs.tencentyun.com/cube-studio/neo4j:4.4",
"command": "",
"env": "NEO4J_AUTH=neo4j/admin",
"ports": "7474,7687",
"volume_mount": "kubeflow-user-workspace(pvc):/mnt,/data/k8s/kubeflow/pipeline/workspace/admin/neo4j(hostpath):/var/lib/neo4j/data",
"expand": {
"help_url": "https://github.com/tencentmusic/cube-studio/blob/master/docs/example/service.md"
}
},
"jaeger": {
"project_name": "public",
"service_name": "jaeger",
"service_describe": "jaeger链路追踪",
"image_name": "jaegertracing/all-in-one:1.29",
"command": "",
"env": "",
"ports": "16686,5775",
"expand": {
"help_url": "https://github.com/tencentmusic/cube-studio/blob/master/docs/example/service.md"
}
},
"postgresql-ui": {
"project_name": "public",
"service_name": "postgresql-ui",
"service_describe": "可视化编辑postgresql数据库",
"image_name": "dpage/pgadmin4",
"command": "",
"env": "PGADMIN_DEFAULT_EMAIL=admin@tencent.com\nPGADMIN_DEFAULT_PASSWORD=admin",
"ports": "80",
"expand": {
"help_url": "https://github.com/tencentmusic/cube-studio/blob/master/docs/example/service.md"
}
},
"rstudio": {
"project_name": "public",
"service_name": "rstudio",
"service_describe": "rstudio的notebook",
"image_name": "ccr.ccs.tencentyun.com/cube-studio/notebook-enterprise:rstudio-ubuntu-bigdata",
"command": "/init.sh && mkdir -p /home/rstudio/.local && chmod -R 777 /home/rstudio/.local/ && /init",
"env": "DISABLE_AUTH=true\nROOT=true",
"ports": "8787",
"expand": {
"help_url": "https://github.com/tencentmusic/cube-studio/wiki"
}
},
"es": {
"project_name": "public",
"service_name": "es",
"service_describe": "elasticsearch",
"image_name": "elasticsearch:7.12.1",
"command": "",
"env": "discovery.type=single-node\ncluster.name=es-docker-cluster\nTAKE_FILE_OWNERSHIP=111",
"ports": "8080,9200",
"expand": {
"help_url": "https://github.com/tencentmusic/cube-studio/wiki"
}
},
"chrome": {
"project_name": "public",
"service_name": "chrome",
"service_describe": "无头浏览器",
"image_name": "selenium/standalone-chrome",
"command": "",
"env": "shm-size=2g\nSE_NODE_OVERRIDE_MAX_SESSIONS=true\nSE_NODE_MAX_SESSIONS=20",
"ports": "4444",
"expand": {
"help_url": "https://github.com/tencentmusic/cube-studio/wiki"
}
}
}

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{
"tf-mnist": {
"project_name": "public",
"name": "mnist",
"version": "v2022.08.01.1",
"describe": "tf mnist 图像分类 tfserving推理",
"path": "https://docker-76009.sz.gfp.tencent-cloud.com/github/cube-studio/inference/tf-mnist.tar.gz",
"framework": "tf",
"api_type": "tfserving"
},
"pytorch-resnet50": {
"project_name": "public",
"name": "resnet50",
"version": "v2022.08.01.2",
"describe": "pytorch resnet50 图像分类 torch-server推理",
"path": "https://docker-76009.sz.gfp.tencent-cloud.com/github/cube-studio/inference/resnet50.mar",
"framework": "pytorch",
"api_type": "torch-server"
},
"torchscript-resnet50": {
"project_name": "public",
"name": "resnet50",
"version": "v2022.08.01.3",
"describe": "torchscript resnet50 图像分类 triton推理",
"path": "https://docker-76009.sz.gfp.tencent-cloud.com/github/cube-studio/inference/resnet50-torchscript.pt",
"framework": "pytorch",
"api_type": "triton-server"
},
"onnx-resnet50": {
"project_name": "public",
"name": "resnet50",
"version": "v2022.08.01.4",
"describe": "onnx resnet50 图像分类 triton推理",
"path": "https://docker-76009.sz.gfp.tencent-cloud.com/github/cube-studio/inference/resnet50.onnx",
"framework": "onnx",
"api_type": "triton-server"
}
}