Querying the Details About a Training Job Version
Function
This API is used to obtain the details about a specified training job based on the job ID.
URI
GET /v1/{project_id}/training-jobs/{job_id}/versions/{version_id}
| Parameter | Mandatory | Type | Description |
|---|---|---|---|
| project_id | Yes | String | Project ID. For details about how to obtain a project ID, see Obtaining a Project ID and Name. |
| job_id | Yes | Long | ID of a training job |
| version_id | Yes | Long | Version ID of a training job |
Request Body
None
Response Body
| Parameter | Type | Description |
|---|---|---|
| is_success | Boolean | Whether the request is successful |
| job_id | Long | ID of a training job |
| job_name | String | Name of a training job |
| job_desc | String | Description of a training job |
| version_id | Long | Version ID of a training job |
| version_name | String | Version name of a training job |
| pre_version_id | Long | Name of the previous version of a training job |
| engine_type | Integer | Engine type of a training job. The mapping between engine_type and engine_name is as follows: engine_type: 13, engine_name: Ascend-Powered-Engine |
| engine_name | String | Name of the engine selected for a training job. Currently, the following engines are supported:
|
| engine_id | Long | ID of the engine selected for a training job |
| engine_version | String | Version of the engine selected for a training job |
| status | Integer | Status of a training job. For details about the job statuses, see Job Statuses. |
| app_url | String | Code directory of a training job |
| boot_file_url | String | Boot file of a training job |
| create_time | Long | Time when a training job is created |
| parameter | Array<Object> | Running parameters of a training job. This parameter is a container environment variable when a training job uses a custom image. For details, see Table 3. |
| duration | Long | Training job running duration, in milliseconds |
| spec_id | Long | ID of the resource specifications selected for a training job |
| core | String | Number of cores of the resource specifications |
| cpu | String | CPU memory of the resource specifications |
| gpu_num | Integer | Number of GPUs of the resource specifications |
| gpu_type | String | GPU type of the resource specifications |
| worker_server_num | Integer | Number of workers in a training job |
| data_url | String | Dataset of a training job |
| train_url | String | OBS path of the training job output file |
| log_url | String | OBS URL of the logs of a training job. By default, this parameter is left blank. Example value: /usr/train/ |
| dataset_version_id | String | Dataset version ID of a training job |
| dataset_id | String | Dataset ID of a training job |
| data_source | Array<Object> | Dataset of a training job. For details, see Table 4. |
| model_id | Long | Model ID of a training job |
| model_metric_list | String | Model metrics of a training job. For details, see Table 5. |
| system_metric_list | Object | System monitoring metrics of a training job. For details, see Table 6. |
| user_image_url | String | SWR URL of a custom image used by a training job |
| user_command | String | Boot command used to start the container of a custom image of a training job |
| resource_id | String | Charged resource ID of a training job |
| dataset_name | String | Dataset of a training job |
| spec_code | String | Resource specifications selected for a training job |
| start_time | Long | Training start time |
| volumes | Array<Object> | Storage volume that can be used by a training job. For details, see Table 11. |
| dataset_version_name | String | Dataset of a training job |
| pool_name | String | Name of a resource pool |
| pool_id | String | ID of a resource pool |
| nas_mount_path | String | Local mount path of SFS Turbo (NAS). Example value: /home/work/nas |
| nas_share_addr | String | Shared path of SFS Turbo (NAS). Example value: 192.168.8.150:/ |
| nas_type | String | Only NFS is supported. Example value: nfs |
| Parameter | Type | Description |
|---|---|---|
| label | String | Parameter name |
| value | String | Parameter value |
| Parameter | Type | Description |
|---|---|---|
| dataset_id | String | Dataset ID of a training job |
| dataset_version | String | Dataset version ID of a training job |
| type | String | Dataset type
|
| data_url | String | OBS bucket path |
| Parameter | Type | Description |
|---|---|---|
| metric | JSON Array | Validation metrics of a classification of a training job. For details, see Table 7. |
| total_metric | JSON | Overall validation parameters of a training job. For details, see Table 9. |
| Parameter | Type | Description |
|---|---|---|
| cpuUsage | Array | CPU usage of a training job |
| memUsage | Array | Memory usage of a training job |
| gpuUtil | Array | GPU usage of a training job |
| Parameter | Type | Description |
|---|---|---|
| metric_values | JSON | Validation metrics of a classification of a training job. For details, see Table 8. |
| reserved_data | JSON | Reserved parameter |
| metric_meta | JSON | Classification of a training job, including the classification ID and name |
| Parameter | Type | Description |
|---|---|---|
| recall | Float | Recall of a classification of a training job |
| precision | Float | Precision of a classification of a training job |
| accuracy | Float | Accuracy of a classification of a training job |
| Parameter | Type | Description |
|---|---|---|
| total_metric_meta | JSON | Reserved parameter |
| total_reserved_data | JSON | Reserved parameter |
| total_metric_values | JSON | Overall validation metrics of a training job. For details, see Table 10. |
| Parameter | Mandatory | Type | Description |
|---|---|---|---|
| nfs | No | Object | Storage volume of the shared file system type. Only the training jobs running in the resource pool with a shared file system network connected support such storage volumes. For details, see Table 6. |
| host_path | No | Object | Storage volume of the host file system type. Only training jobs running in a dedicated resource pool support such storage volumes. For details, see Table 7. |
| Parameter | Mandatory | Type | Description |
|---|---|---|---|
| id | Yes | String | ID of an SFS Turbo file system |
| src_path | Yes | String | Path to an SFS Turbo file system |
| dest_path | Yes | String | Local path to a training job |
| read_only | No | Boolean | Whether dest_path is read-only. The default value is false.
|
| Parameter | Mandatory | Type | Description |
|---|---|---|---|
| src_path | Yes | String | Local path to a host |
| dest_path | Yes | String | Local path to a training job |
| read_only | No | Boolean | Whether dest_path is read-only. The default value is false.
|
Sample Request
The following shows how to obtain the details about the job whose job_id is 10 and version_id is 10.
GET https://endpoint/v1/{project_id}/training-jobs/10/versions/10 Sample Response
- Successful response
{ "is_success": true, "job_id": 10, "job_name": "TestModelArtsJob", "job_desc": "TestModelArtsJob desc", "version_id": 10, "version_name": "jobVersion", "pre_version_id": 5, "engine_type": , "engine_name": "TensorFlow", "engine_id": 1, "engine_version": "TF-1.4.0-python2.7", "status": 10, "app_url": "/usr/app/", "boot_file_url": "/usr/app/boot.py", "create_time": 1524189990635, "parameter": [ { "label": "learning_rate", "value": 0.01 } ], "duration": 532003, "spec_id": 1, "core": 2, "cpu": 8, "gpu_num": 2, "gpu_type": "Pnt1", "worker_server_num": 1, "data_url": "/usr/data/", "train_url": "/usr/train/", "log_url": "/usr/log/", "dataset_version_id": "2ff0d6ba-c480-45ae-be41-09a8369bfc90", "dataset_id": "38277e62-9e59-48f4-8d89-c8cf41622c24", "data_source": [ { "type": "obs", "data_url": "/qianjiajun-test/minst/data/" } ], "user_image_url": "100.125.5.235:20202/jobmng/custom-cpu-base:1.0", "user_command": "bash -x /home/work/run_train.sh python /home/work/user-job-dir/app/mnist/mnist_softmax.py --data_url /home/work/user-job-dir/app/mnist_data", "model_id": 1, "model_metric_list": "{\"metric\":[{\"metric_values\":{\"recall\":0.005833,\"precision\":0.000178,\"accuracy\":0.000937},\"reserved_data\":{},\"metric_meta\":{\"class_name\":0,\"class_id\":0}}],\"total_metric\":{\"total_metric_meta\":{},\"total_reserved_data\":{},\"total_metric_values\":{\"recall\":0.005833,\"id\":0,\"precision\":0.000178,\"accuracy\":0.000937}}}", "system_metric_list": { "cpuUsage": [ "0", "3.10", "5.76", "0", "0", "0", "0" ], "memUsage": [ "0", "0.77", "2.09", "0", "0", "0", "0" ], "gpuUtil": [ "0", "0.25", "0.88", "0", "0", "0", "0" ] }, "dataset_name": "dataset-test", "dataset_version_name": "dataset-version-test", "spec_code": "xxxxxxxx", "start_time": 1563172362000, "volumes": [ { "nfs": { "id": "43b37236-9afa-4855-8174-32254b9562e7", "src_path": "192.168.8.150:/", "dest_path": "/home/work/nas", "read_only": false } }, { "host_path": { "src_path": "/root/work", "dest_path": "/home/mind", "read_only": false } } ], "pool_id": "pool9928813f", "pool_name": "pnt1", "nas_mount_path": "/home/work/nas", "nas_share_addr": "192.168.8.150:/", "nas_type": "nfs" } - Failed response
{ "is_success": false, "error_message": "Error string", "error_code": "ModelArts.0105" }
Status Code
For details about the status code, see Status Code.