Help Center/ ModelArts/ API Reference/ Training Management/ Obtaining the General Specifications Supported by a Training Job
Updated on 2024-05-30 GMT+08:00

Obtaining the General Specifications Supported by a Training Job

Function

This API is used to obtain the public flavors supported by a training job.

Debugging

You can debug this API through automatic authentication in API Explorer or use the SDK sample code generated by API Explorer.

URI

GET /v2/{project_id}/training-job-flavors

Table 1 Path Parameters

Parameter

Mandatory

Type

Description

project_id

Yes

String

Project ID. For details, see Obtaining a Project ID and Name.

Table 2 Query Parameters

Parameter

Mandatory

Type

Description

flavor_type

No

String

This API is used to obtain training job flavors. If this parameter is not specified, all flavors will be obtained. Options:

  • CPU

  • GPU

  • Ascend

Request Parameters

None

Response Parameters

Status code: 200

Table 3 Response body parameters

Parameter

Type

Description

total_count

Integer

Total number of resource flavors of a training job.

flavors

Array of FlavorResponse objects

List of resource flavors of a training job.

Table 4 FlavorResponse

Parameter

Type

Description

flavor_id

String

ID of the resource flavor.

flavor_name

String

Name of the resource flavor.

max_num

Integer

Maximum number of nodes in a resource flavor.

flavor_type

String

Resource flavor type. Options:

  • CPU

  • GPU

  • Ascend

billing

billing object

Billing information of a resource flavor.

flavor_info

flavor_info object

Resource flavor details.

attributes

Map<String,String>

Other specification attributes.

Table 5 billing

Parameter

Type

Description

code

String

Billing code.

unit_num

Integer

Number of billing units.

Table 6 flavor_info

Parameter

Type

Description

max_num

Integer

Maximum number of nodes that can be selected. The value 1 indicates that the distributed mode is not supported.

cpu

cpu object

CPU specifications.

gpu

gpu object

GPU specifications.

npu

npu object

Ascend specifications

memory

memory object

Memory information.

disk

disk object

Disk information.

Table 7 cpu

Parameter

Type

Description

arch

String

CPU architecture.

core_num

Integer

Number of cores.

Table 8 gpu

Parameter

Type

Description

unit_num

Integer

Number of GPUs.

product_name

String

Product name.

memory

String

Memory.

Table 9 npu

Parameter

Type

Description

unit_num

String

Number of NPUs.

product_name

String

Product name.

memory

String

Memory.

Table 10 memory

Parameter

Type

Description

size

Integer

Memory size.

unit

String

Memory size

Table 11 disk

Parameter

Type

Description

size

Integer

Disk size.

unit

String

Unit of the disk size.

Example Requests

The following shows how to query the public CPU resource flavors of training jobs in CN North-Beijing4.

GET https://endpoint/v2/{project_id}/training-job-flavors?flavor_type=CPU

Example Responses

Status code: 200

ok

{
  "total_count" : 2,
  "flavors" : [ {
    "flavor_id" : "modelarts.vm.cpu.2u",
    "flavor_name" : "Computing CPU(2U) instance",
    "flavor_type" : "CPU",
    "billing" : {
      "code" : "modelarts.vm.cpu.2u",
      "unit_num" : 1
    },
    "flavor_info" : {
      "max_num" : 1,
      "cpu" : {
        "arch" : "x86",
        "core_num" : 2
      },
      "memory" : {
        "size" : 8,
        "unit" : "GB"
      },
      "disk" : {
        "size" : 50,
        "unit" : "GB"
      }
    }
  }, {
    "flavor_id" : "modelarts.vm.cpu.8u",
    "flavor_name" : "Computing CPU(8U) instance",
    "flavor_type" : "CPU",
    "billing" : {
      "code" : "modelarts.vm.cpu.8u",
      "unit_num" : 1
    },
    "flavor_info" : {
      "max_num" : 16,
      "cpu" : {
        "arch" : "x86",
        "core_num" : 8
      },
      "memory" : {
        "size" : 32,
        "unit" : "GB"
      },
      "disk" : {
        "size" : 50,
        "unit" : "GB"
      }
    }
  } ]
}

Status Codes

Status Code

Description

200

ok

Error Codes

See Error Codes.