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.
GET /v1/{project_id}/job/resource-specs
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
|
None
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. |
The following shows how to query the resource specifications of a training job.
GET https://endpoint/v1/{project_id}/job/resource-specs?job_type=train
{ "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 }
{ "is_success": false, "error_message": "Error string", "error_code": "ModelArts.0105" }
For details about the status code, see Table 1.
See Error Codes.