Help Center> ModelArts> API Reference> Training Management> Obtaining the Preset AI Frameworks Supported by a Training Job
Updated on 2024-05-30 GMT+08:00

Obtaining the Preset AI Frameworks Supported by a Training Job

Function

This API is used to obtain the preset AI frameworks 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-engines

Table 1 Path Parameters

Parameter

Mandatory

Type

Description

project_id

Yes

String

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

Request Parameters

None

Response Parameters

Status code: 200

Table 2 Response body parameters

Parameter

Type

Description

total

Integer

Total number of training job engines.

items

Array of items objects

List of engine specifications.

Table 3 items

Parameter

Type

Description

engine_id

String

Engine ID, for example, caffe-1.0.0-python2.7.

engine_name

String

Engine name, for example, Caffe.

engine_version

String

Engine version. Engines with the same name have multiple versions, for example, Caffe-1.0.0-python2.7 of Python 2.7.

v1_compatible

Boolean

Whether the v1 compatibility mode is used.

run_user

String

User UID started by default by the engine.

image_info

image_info object

Engine information.

Table 4 image_info

Parameter

Type

Description

cpu_image_url

String

Image with the matched CPU specifications.

gpu_image_url

String

Image with the matched GPU or Ascend flavors

image_version

String

Image version.

Example Requests

The following shows how to query all public engine specifications of a training job in CN North-Beijing4 (only part of the specifications are displayed because there are too many engines).

GET https://endpoint/v2/{project_id}/training-job-engines

Example Responses

Status code: 200

ok

{
  "total" : 20,
  "items" : [ {
    "engine_id" : "caffe-1.0.0-python2.7",
    "engine_name" : "Caffe",
    "engine_version" : "caffe-1.0.0-python2.7",
    "v1_compatible" : true,
    "run_user" : "",
    "image_info" : {
      "cpu_image_url" : "modelarts-job-dev-image/caffe1-cpu-cp27:1.0.0",
      "gpu_image_url" : "modelarts-job-dev-image/caffe1-gpu-cuda8-cp27:1.0.0",
      "image_version" : "3.1.0"
    }
  }, {
    "engine_id" : "horovod-cp36-tf-1.16.2",
    "engine_name" : "Horovod",
    "engine_version" : "0.16.2-TF-1.13.1-python3.6",
    "v1_compatible" : true,
    "run_user" : "",
    "image_info" : {
      "cpu_image_url" : "modelarts-job-dev-image/tensorflow-gpu-cuda10-cp36-horovod0162:1.13.1",
      "gpu_image_url" : "modelarts-job-dev-image/tensorflow-gpu-cuda10-cp36-horovod0162:1.13.1",
      "image_version" : "3.2.1"
    }
  }, {
    "engine_id" : "horovod_0.20.0-tensorflow_2.1.0-cuda_10.1-py_3.7-ubuntu_18.04-x86_64",
    "engine_name" : "Horovod",
    "engine_version" : "horovod_0.20.0-tensorflow_2.1.0-cuda_10.1-py_3.7-ubuntu_18.04-x86_64",
    "v1_compatible" : false,
    "run_user" : "1102",
    "image_info" : {
      "cpu_image_url" : "aip/horovod_tensorflow:train",
      "gpu_image_url" : "aip/horovod_tensorflow:train",
      "image_version" : "horovod_0.20.0-tensorflow_2.1.0-cuda_10.1-py_3.7-ubuntu_18.04-x86_64-20210912152543-1e0838d"
    }
  }, "......", {
    "engine_id" : "tensorflow_2.1.0-cuda_10.1-py_3.7-ubuntu_18.04-x86_64",
    "engine_name" : "TensorFlow",
    "engine_version" : "tensorflow_2.1.0-cuda_10.1-py_3.7-ubuntu_18.04-x86_64",
    "v1_compatible" : false,
    "run_user" : "1102",
    "image_info" : {
      "cpu_image_url" : "aip/tensorflow_2_1:train",
      "gpu_image_url" : "aip/tensorflow_2_1:train",
      "image_version" : "tensorflow_2.1.0-cuda_10.1-py_3.7-ubuntu_18.04-x86_64-20210912152543-1e0838d"
    }
  }, {
    "engine_id" : "xgboost-sklearn-python3.6",
    "engine_name" : "XGBoost-Sklearn",
    "engine_version" : "XGBoost-0.80-Sklearn-0.18.1-python3.6",
    "v1_compatible" : true,
    "run_user" : "",
    "image_info" : {
      "cpu_image_url" : "modelarts-job-dev-image/python-train-py36:secure",
      "gpu_image_url" : "",
      "image_version" : "2.0.10-20211101113705"
    }
  } ]
}

Status Codes

Status Code

Description

200

ok

Error Codes

See Error Codes.