Help Center/ ModelArts/ API Reference/ Training Management/ Obtaining the Preset AI Frameworks Supported by a Training Job

Updated on 2025-05-30 GMT+08:00

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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.

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

{
  "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"
    }
  } ]
}