数据湖计算 DLC 查询 MlFlow Server 关联的训练

1. 接口描述

接口请求域名： dlc.tencentcloudapi.com 。

查询 MlFlow Server 关联的训练实例列表

默认接口请求频率限制：20次/秒。

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2. 输入参数

以下请求参数列表仅列出了接口请求参数和部分公共参数，完整公共参数列表见公共请求参数。

参数名称	必选	类型	描述
Action	是	String	公共参数，本接口取值：ListMlflowServerTrainingInstances。
Version	是	String	公共参数，本接口取值：2021-01-25。
Region	是	String	公共参数，详见产品支持的地域列表，本接口仅支持其中的: ap-beijing, ap-chongqing, ap-guangzhou, ap-shanghai, ap-singapore 。
ServerId	否	String	MlFlowServer的ID 示例值：mlflow-7f72b80b
Filters.N	否	Array of Filter	分页过滤条件
SortFields.N	否	Array of SortField	分页筛选条件
StartTime	否	Integer	分页开始时间范围示例值：1783151859000
EndTime	否	Integer	分页结束时间范围示例值：1785830259000
Page	否	Integer	分页当前页号示例值：1
PageSize	否	Integer	分页每页大小示例值：10

3. 输出参数

参数名称	类型	描述
Items	Array of TrainingJobInstance	返回训练实例列表
Total	Integer	总数示例值：22
Page	Integer	当前页示例值：1
PageSize	Integer	每页大小示例值：200
TotalPages	Integer	总页数示例值：1
RequestId	String	唯一请求 ID，由服务端生成，每次请求都会返回（若请求因其他原因未能抵达服务端，则该次请求不会获得 RequestId）。定位问题时需要提供该次请求的 RequestId。

4. 示例

示例1 返回MlFlow关联的训练实例列表

输入示例

POST / HTTP/1.1
Host: dlc.tencentcloudapi.com
Content-Type: application/json
X-TC-Action: ListMlflowServerTrainingInstances
<公共请求参数>

{
    "ServerId": "mlflow-7f72b80b"
}

输出示例

{
    "Response": {
        "Items": [
            {
                "BaseModelUid": "m-qwen35-zerodot8b-6a705b58-dc17",
                "Catalog": "{\"CFSVolumes\":null,\"CFSTurboVolumes\":null,\"COSVolumes\":[{\"Region\":\"ap-guangzhou\",\"Bucket\":\"common-job-packages-251233710\",\"VolumeSubPath\":\"/models/m-qwen35-zerodot8b-6a705b58-dc17/v1/\",\"SubPathMode\":null,\"SubPath\":null,\"MountPath\":\"/models/m-qwen35-zerodot8b-6a705b58-dc17/v1\",\"PersistVolumeName\":\"rayjob-20260804152823-ptbk-cos-34c3f2811e7c39a470e20081757ac1fd\",\"VolumeMountMode\":\"ReadOnly\",\"Source\":null,\"Origin\":null},{\"Region\":\"ap-guangzhou\",\"Bucket\":\"qzzhu-260200065\",\"VolumeSubPath\":\"/datasets/sft/train80\",\"SubPathMode\":null,\"SubPath\":null,\"MountPath\":\"/datasets/sft/train80\",\"PersistVolumeName\":\"rayjob-20260804152823-ptbk-cos-b2e28c1aee9d748a30406f7227b4f91d\",\"VolumeMountMode\":null,\"Source\":\"dataset\",\"Origin\":\"cos_reference\"},{\"Region\":\"ap-guangzhou\",\"Bucket\":\"qzzhu-260200065\",\"VolumeSubPath\":\"/checkpoints/sft/train80-v3\",\"SubPathMode\":null,\"SubPath\":null,\"MountPath\":\"/checkpoints/sft/train80\",\"PersistVolumeName\":\"rayjob-20260804152823-ptbk-cos-c078294231fc46b0d4b59bf5c6f0cf45\",\"VolumeMountMode\":\"ReadWrite\",\"Source\":\"checkpoint\",\"Origin\":null}],\"GooseFSVolumes\":null}",
                "CreateTime": 1785828503572,
                "Creator": "700002655693",
                "Entrypoint": "python /workspace/ray_post_training_entry.py --num-workers 1 --gpus-per-worker 1 --cpus-per-worker 20",
                "HistoryUrl": "https://test-tcray-historyserver-guangzhou.cloud.tencent.com/history/dlc-p-axzbtgug/rayjob-20260804152823-ptbk/jobs/rayjob-20260804152823-ptbk/",
                "Image": "ccr.ccs.tencentyun.com/emr-image/tcray:2.55.1-py311-cu125-torch2.10.0-tfm5.6",
                "InstanceId": "rayjob-20260804152823-ptbk",
                "JobCreateTime": 1785828511904,
                "JobRunningTime": 1045972,
                "Kind": "POST_TRAINING",
                "Mode": "sft",
                "Priority": 5,
                "Queue": "default",
                "ResourceConfig": "{\"Head\":{\"Name\":\"Head\",\"PodCpu\":1,\"PodMem\":4,\"GpuType\":\"\",\"GpuNum\":0,\"Envs\":[],\"Labels\":[],\"ResourcesLabels\":[],\"Tolerations\":null,\"ResourceType\":\"CPU\",\"InstanceType\":\"\",\"Spec\":1,\"BillingItem\":\"sv_dlc_standard_cu_standard_cu\",\"VideoMemory\":null,\"PodNum\":1,\"HighAvailability\":false,\"LabCu\":null},\"Worker\":[{\"Name\":\"WorkerGroup01\",\"PodCpu\":20,\"PodMem\":80,\"GpuType\":\"T4\",\"GpuNum\":1,\"Envs\":[],\"Labels\":[],\"ResourcesLabels\":[],\"Tolerations\":null,\"ResourceType\":\"GPU\",\"InstanceType\":\"GN7\",\"Spec\":1,\"BillingItem\":\"sv_dlc_gn7_gn75xlarge80\",\"VideoMemory\":null,\"MinPodNum\":1,\"MaxPodNum\":1,\"EnableAutoScaling\":false}]}",
                "ResourcePartitionId": "dlc-p-axzbtgug",
                "ResourcePartitionName": "gpu-t4",
                "RuntimeEnv": "{\"env_vars\":{\"TRAIN_CONFIG_YAML_B64\":\"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\",\"DEEPSPEED_CONFIG_B64\":\"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\",\"NUM_WORKERS\":\"1\",\"GPUS_PER_WORKER\":\"1\",\"CPUS_PER_WORKER\":\"20\",\"NCCL_DEBUG\":\"WARN\",\"HF_HOME\":\"/workspace/cache/hf\",\"WANDB_DISABLED\":\"true\",\"MLFLOW_TRACKING_URI\":\"http://mlflow-7f72b80b-mlflow-svc.dlc-p-axzbtgug.svc.cluster.local:5000\",\"MLFLOW_EXPERIMENT_NAME\":\"sft-train80-qzzhu_checkpoints_v2_Clone\",\"MLFLOW_TAGS\":\"{\\\"job_id\\\":\\\"sft-train80-qzzhu_checkpoints_v2_Clone\\\",\\\"experiment_name\\\":\\\"sft-train80-qzzhu_checkpoints_v2_Clone\\\",\\\"mode\\\":\\\"sft\\\",\\\"finetune_type\\\":\\\"lora\\\",\\\"model\\\":\\\"v1\\\",\\\"source\\\":\\\"ray-nexus\\\"}\",\"HF_MLFLOW_LOG_ARTIFACTS\":\"false\",\"RAY_OVERRIDE_JOB_RUNTIME_ENV\":\"1\"}}",
                "SpecId": "raytrain-spec-tj8i36-q65j",
                "SpecName": "sft-train80-qzzhu_checkpoints_v2_Clone",
                "Status": "SUCCEEDED"
            }
        ],
        "Page": 1,
        "PageSize": 200,
        "Total": 22,
        "TotalPages": 1,
        "RequestId": "bb137fa3-26ee-4dd2-bab9-b9b627f814a1"
    }
}

5. 开发者资源

腾讯云 API 平台

腾讯云 API 平台是综合 API 文档、错误码、API Explorer 及 SDK 等资源的统一查询平台，方便您从同一入口查询及使用腾讯云提供的所有 API 服务。

API Inspector

用户可通过 API Inspector 查看控制台每一步操作关联的 API 调用情况，并自动生成各语言版本的 API 代码，也可前往 API Explorer 进行在线调试。

SDK

云 API 3.0 提供了配套的开发工具集（SDK），支持多种编程语言，能更方便的调用 API。

Tencent Cloud SDK 3.0 for Python: CNB, GitHub, Gitee
Tencent Cloud SDK 3.0 for Java: CNB, GitHub, Gitee
Tencent Cloud SDK 3.0 for PHP: CNB, GitHub, Gitee
Tencent Cloud SDK 3.0 for Go: CNB, GitHub, Gitee
Tencent Cloud SDK 3.0 for Node.js: CNB, GitHub, Gitee
Tencent Cloud SDK 3.0 for .NET: CNB, GitHub, Gitee
Tencent Cloud SDK 3.0 for C++: CNB, GitHub, Gitee
Tencent Cloud SDK 3.0 for Ruby: CNB, GitHub, Gitee

命令行工具

Tencent Cloud CLI 3.0

6. 错误码

该接口暂无业务逻辑相关的错误码，其他错误码详见公共错误码。