Help Center/ ModelArts/ API Reference/ Historical APIs/ Training Management (Old Version)/ Training Jobs/ Obtaining Training Job Versions

Updated on 2024-06-13 GMT+08:00

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Obtaining Training Job Versions

Function

This API is used to obtain the version of a specified training job based on the job ID.

URI

GET /v1/{project_id}/training-jobs/{job_id}/versions

Table 1 describes the required parameters.

**Table 1** URI parameters
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

**Table 2** Query parameters
Parameter	Mandatory	Type	Description
per_page	No	Integer	Number of job parameters displayed on each page. The value range is [1, 1000]. Default value: 10
page	No	Integer	Index of the page to be queried If paging is required, set page to 1. The default value of page is 0, indicating that paging is not supported.

Request Body

None

Response Body

Table 3 describes the response parameters.

**Table 3** Parameters
Parameter	Type	Description
is_success	Boolean	Whether the request is successful
error_message	String	Error message of a failed API call. This parameter is not included when the API call succeeds.
error_code	String	Error code of a failed API call. For details, see Error Codes. This parameter is not included when the API call succeeds.
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_count	Long	Number of versions of a training job
versions	JSON Array	Version parameters of a training job. For details, see the sample response. For details about the attributes, see Table 4.

**Table 4** **versions** parameters
Parameter	Type	Description
version_id	Long	Version ID of a training job
version_name	String	Version name of a training job
pre_version_id	Long	ID of the previous version of a training job
engine_type	Long	Engine type of a training job
engine_name	String	Name of the engine selected for a training job
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	Int	Status of a training job
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	JSON Array	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 5.
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	Boolean	Whether to use GPUs
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/log/
dataset_version_id	String	Dataset version ID of a training job
dataset_id	String	Dataset ID of a training job
data_source	JSON Array	Dataset of a training job. For details, see Table 6.
model_id	Long	Model ID of a training job
model_metric_list	String	Model metrics of a training job. For details, see Table 7.
system_metric_list	String	System monitoring metrics of a training job. For details, see Table 8.
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
start_time	Long	Training start time
volumes	JSON Array	Storage volume that can be used by a training job. For details, see Table 13.
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

**Table 5** **parameter** parameters
Parameter	Type	Description
label	String	Parameter name
value	String	Parameter value

**Table 6** **data_source** parameters
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 obs: Data from OBS is used. dataset: Data from a specified dataset is used.
data_url	String	OBS bucket path

**Table 7** **model_metric_list** parameters
Parameter	Type	Description
metric	JSON Array	Validation metrics of a classification of a training job.
total_metric	JSON	Overall validation parameters of a training job. For details, see Table 11.

**Table 8** **system_metric_list** parameters
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

**Table 9** **metric** parameters
Parameter	Type	Description
metric_values	JSON	Validation metrics of a classification of a training job. For details, see Table 10.
reserved_data	JSON	Reserved parameter
metric_meta	JSON	Classification of a training job, including the classification ID and name

**Table 10** **metric_values** parameters
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

**Table 11** **total_metric** parameters
Parameter	Type	Description
total_metric_meta	JSON Array	Reserved parameter
total_reserved_data	JSON Array	Reserved parameter
total_metric_values	JSON Array	Overall validation metrics of a training job. For details, see Table 12.

**Table 12** **total_metric_values** parameters
Parameter	Type	Description
f1_score	Float	F1 score of a training job. This parameter is used only by some preset algorithms and is automatically generated. It is for reference only.
recall	Float	Total recall of a training job
precision	Float	Total precision of a training job
accuracy	Float	Total accuracy of a training job

**Table 13** **volumes** parameters
Parameter	Type	Description
nfs	object	Storage volume of the shared file system type. Only the training jobs running in a resource pool with the shared file system network connected support such storage volumes. For details, see Table 14.
host_path	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 15.

**Table 14** **nfs** parameters
Parameter	Type	Description
id	String	ID of an SFS Turbo file system
src_path	String	Address of an SFS Turbo file system
dest_path	String	Local path to a training job
read_only	Boolean	Whether dest_path is read-only. The default value is false. true: read-only permission false: read/write permission. This is the default value.

**Table 15** **host_path** parameters
Parameter	Type	Description
src_path	String	Local path to a host
dest_path	String	Local path to a training job
read_only	Boolean	Whether dest_path is read-only. The default value is false. true: read-only permission false: read/write permission. This is the default value.

Sample Request

The following shows how to obtain the job version details on the first page when job_id is set to 10 and five records are displayed on each page.

GET    https://endpoint/v1/{project_id}/training-jobs/10/versions?per_page=5&page=1

Sample Response

Successful response

{
    "is_success": true,
    "job_id": 10,
    "job_name": "testModelArtsJob",
    "job_desc": "testModelArtsJob desc",
    "version_count": 2,
    "versions": [
        {
            "version_id": 10,
            "version_name": "V0004",
            "pre_version_id": 5,
            "engine_type": 1,
            "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": true,
            "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\"],\"gpuMemUsage\":[\"0\",\"0.65\",\"6.01\",\"0\",\"0\",\"0\",\"0\"],\"diskReadRate\":[\"0\",\"91811.07\",\"38846.63\",\"0\",\"0\",\"0\",\"0\"],\"diskWriteRate\":[\"0\",\"2.23\",\"0.94\",\"0\",\"0\",\"0\",\"0\"],\"recvBytesRate\":[\"0\",\"5770405.50\",\"2980077.75\",\"0\",\"0\",\"0\",\"0\"],\"sendBytesRate\":[\"0\",\"12607.17\",\"10487410.00\",\"0\",\"0\",\"0\",\"0\"],\"interval\":1}",
            "dataset_name": "dataset-test",
            "dataset_version_name": "dataset-version-test",

            "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.

Parent topic: Training Jobs

Previous topic: Deleting a Version of a Training Job

Next topic: Creating a Version of a Training Job

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