doc-exports/docs/modelarts/api-ref/ShowAutoSearchPerTrial.html
Wuwan, Qi f81ead2467 ModelArts API 24.3.0 20241128 version
Reviewed-by: Pruthi, Vineet <vineet.pruthi@t-systems.com>
Co-authored-by: Wuwan, Qi <wuwanqi1@noreply.gitea.eco.tsi-dev.otc-service.com>
Co-committed-by: Wuwan, Qi <wuwanqi1@noreply.gitea.eco.tsi-dev.otc-service.com>
2024-11-29 09:04:54 +00:00

6.5 KiB

Querying Information About a Trial Using Hyperparameter Search

Function

This API is used to query information about a trial using hyperparameter search based on the trial_id.

URI

GET /v2/{project_id}/training-jobs/{training_job_id}/autosearch-trials/{trial_id}

Table 1 Path Parameters

Parameter

Mandatory

Type

Description

project_id

Yes

String

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

training_job_id

Yes

String

ID of a training job.

trial_id

Yes

String

trial_id for hyperparameter search.

Request Parameters

None

Response Parameters

Status code: 200

Table 2 Response body parameters

Parameter

Type

Description

header

Array of strings

Field of a trial searched using hyperparameters.

data

Array<Array<String>>

Each data list of a trial searched using hyperparameters.

Example Requests

The following shows how to query information about trial ae544174 of the job whose training_job_id is 5b60a667-1438-4eb5-9705-85b860e623dc.

GET https://endpoint//v2/{project_id}/training-jobs/5b60a667-1438-4eb5-9705-85b860e623dc/autosearch-trials/ae544174

Example Responses

Status code: 200

ok

{
  "header" : [ "done", "pid", "best_reward", "time_total_s", "config", "acc", "loss", "trial_id", "training_iteration", "reward_attr" ],
  "data" : [ [ "False", "314", "0.0625", "19.477163314819336", {
    "batch_size" : 32,
    "learning_rate" : 0.05512301741232006,
    "trial_index" : 0,
    "param/batch_size" : 32,
    "param/learning_rate" : 0.05512301741232006
  }, "0.0625", "tensor(0.0754, device='cuda:0', requires_grad=True)", "ae544174", "2", "0.0625" ], [ "True", "314", "0.0625", "19.477163314819336", {
    "batch_size" : 32,
    "learning_rate" : 0.05512301741232006,
    "trial_index" : 0,
    "param/batch_size" : 32,
    "param/learning_rate" : 0.05512301741232006
  }, "0.0625", "tensor(0.0754, device='cuda:0', requires_grad=True)", "ae544174", "2", "0.0625" ] ]
}

Status Codes

Status Code

Description

200

ok

Error Codes

See Error Codes.