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.
Parameter | Mandatory | Type | Description |
---|---|---|---|
project_id | Yes | String | Project ID. For details about how to obtain the project ID, see Obtaining a Project ID. |
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
|
Request Body¶
None
Response Body¶
Table 3 describes the response 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. |
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": "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 sample response
{ "is_success": false, "error_message": "Error string", "error_code": "ModelArts.0105" }
Status Code¶
For details about the status code, see Table 1.
Error Codes¶
See Error Codes.