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Querying Job Resource Specifications

Function

This API is used to query 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 Parameter description

Parameter

Mandatory

Type

Description

project_id

Yes

String

Project ID. For details about how to obtain the project ID, see Obtaining a Project ID.
Table 2 Parameter description

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 Parameter description

Parameter

Type

Description

is_success

Boolean

Whether the request is successful

error_msg

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 Code.

This parameter is not included when the API call succeeds.

spec_total_count

Integer

Total number of job resource specifications

specs

JSON Array

List of resource specifications attributes
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.

Samples

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

  • Sample request 
    GET    https://endpoint/v1/{project_id}/job/resource-specs?job_type=train
  • Successful sample 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": "nvidia-p100",
            "spec_code":"modelarts.vm.gpu.p100",
            "unit_num": 1,
            "max_num": 4,
            "storage": "",
            "interface_type": 1,
            "no_resource": false
        }
    ],
    "is_success": true,
    "spec_total_count": 2
}
  • Failed sample response 
    {
    "is_success": false,
    "error_msg": "Error string",
    "error_code": "ModelArts.0105"
}

Status Code

For details about the status code, see Table 1.