更新时间:2022-05-25 GMT+08:00
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查询超参搜索所有trial的结果

功能介绍

查询超参搜索所有trial的结果。

调试

您可以在API Explorer中调试该接口。

URI

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

表1 路径参数

参数

是否必选

参数类型

描述

project_id

String

用户项目ID。获取方法请参见获取项目ID

training_job_id

String

训练作业ID。

表2 Query参数

参数

是否必选

参数类型

描述

limit

Integer

指定每一页返回的最大条目数,取值范围[1,50],默认为50。

最小值:1

最大值:50

缺省值:50

offset

Integer

分页列表的起始页,默认为0。

最小值:0

缺省值:0

请求参数

响应参数

状态码: 200

表3 响应Body参数

参数

参数类型

描述

total

Integer

超参搜索所有trial结果的个数。

count

Integer

超参搜索所有trial结果的当前页展示个数。

limit

Integer

超参搜索所有trial结果的当前页展示个数最大值。

offset

Integer

超参搜索所有trial结果的当前页数。

items

items object

超参搜索列表。

表4 items

参数

参数类型

描述

header

Array of strings

超参搜索所有trial结果的字段信息。

data

Array<Array<String>>

超参搜索所有trial结果的每条数据列表。

请求示例

如以下查询training_job_id为5b60a667-1438-4eb5-9705-85b860e623dc的作业的所有trial的信息。

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

响应示例

状态码: 200

ok

{
  "total" : 8,
  "count" : 8,
  "limit" : 50,
  "offset" : 0,
  "group_by" : "",
  "items" : {
    "header" : [ "", "done", "pid", "config", "trial_id", "training_iteration", "time_total_s", "worker_index", "reward_attr", "status", "acc", "loss", "best_reward" ],
    "data" : [ [ "0", "True", "314", "{'batch_size': 32, 'learning_rate': 0.05512301741232006, 'trial_index': 0, 'param/batch_size': 32, 'param/learning_rate': 0.05512301741232006}", "ae544174", "2", "19.477163314819336", "", "0.0625", "TERMINATED", "0.0625", "tensor(0.0754, device='cuda:0', requires_grad=True)", "0.0625" ], [ "1", "True", "315", "{'batch_size': 32, 'learning_rate': 0.0785570955603036, 'trial_index': 1, 'param/batch_size': 32, 'param/learning_rate': 0.0785570955603036}", "ae548666", "2", "3.601897954940796", "", "0.0", "TERMINATED", "0.0", "tensor(0.0760, device='cuda:0', requires_grad=True)", "0.0" ], [ "2", "True", "312", "{'batch_size': 16, 'learning_rate': 0.04015387428829642, 'trial_index': 2, 'param/batch_size': 16, 'param/learning_rate': 0.04015387428829642}", "ae54c0ea", "2", "3.5978384017944336", "", "0.1875", "TERMINATED", "0.1875", "tensor(0.1469, device='cuda:0', requires_grad=True)", "0.1875" ], [ "3", "True", "313", "{'batch_size': 32, 'learning_rate': 0.0340820322164706, 'trial_index': 3, 'param/batch_size': 32, 'param/learning_rate': 0.0340820322164706}", "ae5503c0", "2", "3.641200304031372", "", "0.25", "TERMINATED", "0.25", "tensor(0.0716, device='cuda:0', requires_grad=True)", "0.25" ], [ "4", "True", "470", "{'batch_size': 32, 'learning_rate': 0.03656488928171769, 'trial_index': 4, 'param/batch_size': 32, 'param/learning_rate': 0.03656488928171769}", "bef46590", "2", "3.6120550632476807", "", "0.09375", "TERMINATED", "0.09375", "tensor(0.0740, device='cuda:0', requires_grad=True)", "0.09375" ], [ "5", "True", "499", "{'batch_size': 32, 'learning_rate': 0.008413169003970163, 'trial_index': 5, 'param/batch_size': 32, 'param/learning_rate': 0.008413169003970163}", "bef578f4", "2", "3.6379287242889404", "", "0.1875", "TERMINATED", "0.1875", "tensor(0.0723, device='cuda:0', requires_grad=True)", "0.1875" ], [ "6", "True", "528", "{'batch_size': 64, 'learning_rate': 0.06297447200613912, 'trial_index': 6, 'param/batch_size': 64, 'param/learning_rate': 0.06297447200613912}", "bef5c584", "2", "3.711118221282959", "", "0.046875", "TERMINATED", "0.046875", "tensor(0.0381, device='cuda:0', requires_grad=True)", "0.046875" ], [ "7", "True", "557", "{'batch_size': 32, 'learning_rate': 0.04426479392014276, 'trial_index': 7, 'param/batch_size': 32, 'param/learning_rate': 0.04426479392014276}", "bef60684", "2", "3.6971280574798584", "", "0.0625", "TERMINATED", "0.0625", "tensor(0.0778, device='cuda:0', requires_grad=True)", "0.0625" ] ]
  }
}

状态码

状态码

描述

200

ok

错误码

请参见错误码

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