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>
14 KiB
Querying All Trials Using Hyperparameter Search
Function
This API is used to query all trails using hyperparameter search.
URI
GET /v2/{project_id}/training-jobs/{training_job_id}/autosearch-trials
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. |
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. |
Parameter |
Mandatory |
Type |
Description |
---|---|---|---|
limit |
No |
Integer |
Number of returned data entries. |
offset |
No |
Integer |
Offset of a data entry. |
Request Parameters
None
Response Parameters
Status code: 200
Parameter |
Type |
Description |
---|---|---|
total |
Integer |
Total number of trials using the hyperparameter search. |
count |
Integer |
Number of hyperparameter search trials displayed on the current page. |
limit |
Integer |
Maximum number of hyperparameter search trials displayed on the current page. |
offset |
Integer |
Current page for all trials searched using hyperparameters. |
group_by |
String |
Type. |
items |
items object |
Hyperparameter search items. |
Example Requests
The following shows how to query all trial information about 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
Example Responses
Status code: 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" ] ] } }
Status Codes
Status Code |
Description |
---|---|
200 |
ok |
Error Codes
See Error Codes.