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

Updated on 2025-11-19 GMT+08:00

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Obtaining the Preset AI Frameworks Supported by a Training Job

Function

This API is used to query the list of preset AI frameworks supported by the current system.

This API is used when you need to know the preset AI frameworks supported by the system. Before using this API, ensure that you have the required permissions. After the query, you will obtain the details of all preset AI frameworks supported by the system. If you do not have the required permission or the query fails, the API will return an error message.

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	Definition: Project ID. For details, see Obtaining a Project ID and Name. Constraints: The value can contain 1 to 64 characters. Letters, digits, and hyphens (-) are allowed. Range: N/A Default Value: N/A

Request Parameters

None

Response Parameters

Status code: 200

**Table 2** Response body parameters
Parameter	Type	Description
total	Integer	Definition: Total number of training job engine flavors. Range: N/A
items	Array of items objects	Definition: Engine flavor parameter list.

**Table 3** items
Parameter	Type	Description
engine_id	String	Definition: Engine flavor ID, for example, caffe-1.0.0-python2.7. Range: N/A
engine_name	String	Definition: Engine flavor name, for example, Caffe. Range: N/A
engine_version	String	Definition: Engine flavor version. Engines with the same name have multiple versions, for example, Caffe-1.0.0-python2.7 of Python 2.7. Range: N/A
v1_compatible	Boolean	Definition: Specifies whether the v1 compatibility mode is used. Range true: v1 compatibility false: v1 incompatibility
run_user	String	Definition: Default UID for the engine startup. Range: N/A
image_info	image_info object	Definition: Engine information.

**Table 4** image_info
Parameter	Type	Description
cpu_image_url	String	Definition: Image of the CPU flavor. Range: N/A
gpu_image_url	String	Definition: Image with the matched GPU or Ascend flavor. Range: N/A
image_version	String	Definition: Image version. Range: N/A

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"
    }
  } ]
}