Updated on 2023-12-14 GMT+08:00

Querying Job Resource Specifications

Function

This API is used to obtain the resource specifications of a specified job.

You must specify the resource specifications when creating a training job or an inference job.

URI

GET /v1/{project_id}/job/resource-specs

Table 1 describes the required parameters.
Table 1 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.

Table 2 Parameters

Parameter

Mandatory

Type

Description

job_type

No

String

Job type. The value can be train or inference. This parameter is not required for querying the specifications of ExeML resources.

engine_id

No

Long

Engine ID of a job. Default value: 0 This parameter is not required for querying the specifications of ExeML resources.

project_type

No

Integer

Project type. Default value: 0

  • 0: non-ExeML project
  • 1: ExeML job for image classification
  • 2: ExeML job for object detection
  • 3: ExeML job for predictive analytics

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.

spec_total_count

Integer

Total number of job resource specifications

specs

specs array

List of resource specifications attributes. For details, see Table 4.

Table 4 specs parameters

Parameter

Type

Description

spec_id

Long

ID of the resource specifications

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

spec_code

String

Type of the resource specifications

max_num

Integer

Maximum number of nodes that can be selected

unit_num

Integer

Number of pricing units

storage

String

SSD size of a resource flavor

interface_type

Integer

Interface type

no_resource

Boolean

Whether the resources of the selected specifications are sufficient. True indicates that no resource is available.

Sample Request

The following shows how to obtain the resource specifications of a training job.

GET    https://endpoint/v1/{project_id}/job/resource-specs?job_type=train

Sample Response

  • Successful response
    {
        "specs": [
    
            {
                "spec_id": 2,
                "core": "2",
                "cpu": "8",
                "gpu_num": 0,
                "gpu_type": "",
                "spec_code": "modelarts.vm.cpu.2u",
                "unit_num": 1,
                "max_num": 2,
                "storage": "",
                "interface_type": 1,
                "no_resource": false
            },
            {
                "spec_id": 4,
                "core": "8",
                "cpu": "64",
                "gpu_num": 1,
                "gpu_type": "v100",
                "spec_code":"modelarts.vm.gpu.v100",
                "unit_num": 1,
                "max_num": 4,
                "storage": "",
                "interface_type": 1,
                "no_resource": false
            }
        ],
        "is_success": true,
        "spec_total_count": 2
    }
  • Failed response
    {
        "is_success": false,
        "error_message": "Error string",
        "error_code": "ModelArts.0105"
    }

Status Code

For details about the status code, see Table 1.