1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
|
<html><body>
<style>
body, h1, h2, h3, div, span, p, pre, a {
margin: 0;
padding: 0;
border: 0;
font-weight: inherit;
font-style: inherit;
font-size: 100%;
font-family: inherit;
vertical-align: baseline;
}
body {
font-size: 13px;
padding: 1em;
}
h1 {
font-size: 26px;
margin-bottom: 1em;
}
h2 {
font-size: 24px;
margin-bottom: 1em;
}
h3 {
font-size: 20px;
margin-bottom: 1em;
margin-top: 1em;
}
pre, code {
line-height: 1.5;
font-family: Monaco, 'DejaVu Sans Mono', 'Bitstream Vera Sans Mono', 'Lucida Console', monospace;
}
pre {
margin-top: 0.5em;
}
h1, h2, h3, p {
font-family: Arial, sans serif;
}
h1, h2, h3 {
border-bottom: solid #CCC 1px;
}
.toc_element {
margin-top: 0.5em;
}
.firstline {
margin-left: 2 em;
}
.method {
margin-top: 1em;
border: solid 1px #CCC;
padding: 1em;
background: #EEE;
}
.details {
font-weight: bold;
font-size: 14px;
}
</style>
<h1><a href="ml_v1.html">AI Platform Training & Prediction API</a> . <a href="ml_v1.projects.html">projects</a> . <a href="ml_v1.projects.locations.html">locations</a> . <a href="ml_v1.projects.locations.studies.html">studies</a> . <a href="ml_v1.projects.locations.studies.trials.html">trials</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
<code><a href="#addMeasurement">addMeasurement(name, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Adds a measurement of the objective metrics to a trial. This measurement is assumed to have been taken before the trial is complete.</p>
<p class="toc_element">
<code><a href="#checkEarlyStoppingState">checkEarlyStoppingState(name, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Checks whether a trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.</p>
<p class="toc_element">
<code><a href="#close">close()</a></code></p>
<p class="firstline">Close httplib2 connections.</p>
<p class="toc_element">
<code><a href="#complete">complete(name, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Marks a trial as complete.</p>
<p class="toc_element">
<code><a href="#create">create(parent, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Adds a user provided trial to a study.</p>
<p class="toc_element">
<code><a href="#delete">delete(name, x__xgafv=None)</a></code></p>
<p class="firstline">Deletes a trial.</p>
<p class="toc_element">
<code><a href="#get">get(name, x__xgafv=None)</a></code></p>
<p class="firstline">Gets a trial.</p>
<p class="toc_element">
<code><a href="#list">list(parent, x__xgafv=None)</a></code></p>
<p class="firstline">Lists the trials associated with a study.</p>
<p class="toc_element">
<code><a href="#listOptimalTrials">listOptimalTrials(parent, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Lists the pareto-optimal trials for multi-objective study or the optimal trials for single-objective study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency</p>
<p class="toc_element">
<code><a href="#stop">stop(name, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Stops a trial.</p>
<p class="toc_element">
<code><a href="#suggest">suggest(parent, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Adds one or more trials to a study, with parameter values suggested by AI Platform Vizier. Returns a long-running operation associated with the generation of trial suggestions. When this long-running operation succeeds, it will contain a SuggestTrialsResponse.</p>
<h3>Method Details</h3>
<div class="method">
<code class="details" id="addMeasurement">addMeasurement(name, body=None, x__xgafv=None)</code>
<pre>Adds a measurement of the objective metrics to a trial. This measurement is assumed to have been taken before the trial is complete.
Args:
name: string, Required. The trial name. (required)
body: object, The request body.
The object takes the form of:
{ # The request message for the AddTrialMeasurement service method.
"measurement": { # A message representing a measurement. # Required. The measurement to be added to a trial.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # A message representing a trial.
"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
{ # A message representing a measurement.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
],
"name": "A String", # Output only. Name of the trial assigned by the service.
"parameters": [ # The parameters of the trial.
{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
"intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
"startTime": "A String", # Output only. Time at which the trial was started.
"state": "A String", # The detailed state of a trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
}</pre>
</div>
<div class="method">
<code class="details" id="checkEarlyStoppingState">checkEarlyStoppingState(name, body=None, x__xgafv=None)</code>
<pre>Checks whether a trial should stop or not. Returns a long-running operation. When the operation is successful, it will contain a CheckTrialEarlyStoppingStateResponse.
Args:
name: string, Required. The trial name. (required)
body: object, The request body.
The object takes the form of:
{ # The request message for the CheckTrialEarlyStoppingState service method.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}</pre>
</div>
<div class="method">
<code class="details" id="close">close()</code>
<pre>Close httplib2 connections.</pre>
</div>
<div class="method">
<code class="details" id="complete">complete(name, body=None, x__xgafv=None)</code>
<pre>Marks a trial as complete.
Args:
name: string, Required. The trial name.metat (required)
body: object, The request body.
The object takes the form of:
{ # The request message for the CompleteTrial service method.
"finalMeasurement": { # A message representing a measurement. # Optional. If provided, it will be used as the completed trial's final_measurement; Otherwise, the service will auto-select a previously reported measurement as the final-measurement
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
"infeasibleReason": "A String", # Optional. A human readable reason why the trial was infeasible. This should only be provided if `trial_infeasible` is true.
"trialInfeasible": True or False, # Optional. True if the trial cannot be run with the given Parameter, and final_measurement will be ignored.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # A message representing a trial.
"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
{ # A message representing a measurement.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
],
"name": "A String", # Output only. Name of the trial assigned by the service.
"parameters": [ # The parameters of the trial.
{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
"intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
"startTime": "A String", # Output only. Time at which the trial was started.
"state": "A String", # The detailed state of a trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
}</pre>
</div>
<div class="method">
<code class="details" id="create">create(parent, body=None, x__xgafv=None)</code>
<pre>Adds a user provided trial to a study.
Args:
parent: string, Required. The name of the study that the trial belongs to. (required)
body: object, The request body.
The object takes the form of:
{ # A message representing a trial.
"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
{ # A message representing a measurement.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
],
"name": "A String", # Output only. Name of the trial assigned by the service.
"parameters": [ # The parameters of the trial.
{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
"intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
"startTime": "A String", # Output only. Time at which the trial was started.
"state": "A String", # The detailed state of a trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # A message representing a trial.
"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
{ # A message representing a measurement.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
],
"name": "A String", # Output only. Name of the trial assigned by the service.
"parameters": [ # The parameters of the trial.
{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
"intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
"startTime": "A String", # Output only. Time at which the trial was started.
"state": "A String", # The detailed state of a trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
}</pre>
</div>
<div class="method">
<code class="details" id="delete">delete(name, x__xgafv=None)</code>
<pre>Deletes a trial.
Args:
name: string, Required. The trial name. (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
}</pre>
</div>
<div class="method">
<code class="details" id="get">get(name, x__xgafv=None)</code>
<pre>Gets a trial.
Args:
name: string, Required. The trial name. (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # A message representing a trial.
"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
{ # A message representing a measurement.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
],
"name": "A String", # Output only. Name of the trial assigned by the service.
"parameters": [ # The parameters of the trial.
{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
"intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
"startTime": "A String", # Output only. Time at which the trial was started.
"state": "A String", # The detailed state of a trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
}</pre>
</div>
<div class="method">
<code class="details" id="list">list(parent, x__xgafv=None)</code>
<pre>Lists the trials associated with a study.
Args:
parent: string, Required. The name of the study that the trial belongs to. (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # The response message for the ListTrials method.
"trials": [ # The trials associated with the study.
{ # A message representing a trial.
"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
{ # A message representing a measurement.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
],
"name": "A String", # Output only. Name of the trial assigned by the service.
"parameters": [ # The parameters of the trial.
{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
"intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
"startTime": "A String", # Output only. Time at which the trial was started.
"state": "A String", # The detailed state of a trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
},
],
}</pre>
</div>
<div class="method">
<code class="details" id="listOptimalTrials">listOptimalTrials(parent, body=None, x__xgafv=None)</code>
<pre>Lists the pareto-optimal trials for multi-objective study or the optimal trials for single-objective study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency
Args:
parent: string, Required. The name of the study that the pareto-optimal trial belongs to. (required)
body: object, The request body.
The object takes the form of:
{ # The request message for the ListTrials service method.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # The response message for the ListOptimalTrials method.
"trials": [ # The pareto-optimal trials for multiple objective study or the optimal trial for single objective study. The definition of pareto-optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency
{ # A message representing a trial.
"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
{ # A message representing a measurement.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
],
"name": "A String", # Output only. Name of the trial assigned by the service.
"parameters": [ # The parameters of the trial.
{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
"intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
"startTime": "A String", # Output only. Time at which the trial was started.
"state": "A String", # The detailed state of a trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
},
],
}</pre>
</div>
<div class="method">
<code class="details" id="stop">stop(name, body=None, x__xgafv=None)</code>
<pre>Stops a trial.
Args:
name: string, Required. The trial name. (required)
body: object, The request body.
The object takes the form of:
{
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # A message representing a trial.
"clientId": "A String", # Output only. The identifier of the client that originally requested this trial.
"endTime": "A String", # Output only. Time at which the trial's status changed to COMPLETED.
"finalMeasurement": { # A message representing a measurement. # The final measurement containing the objective value.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
"infeasibleReason": "A String", # Output only. A human readable string describing why the trial is infeasible. This should only be set if trial_infeasible is true.
"measurements": [ # A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_time). These are used for early stopping computations.
{ # A message representing a measurement.
"elapsedTime": "A String", # Output only. Time that the trial has been running at the point of this measurement.
"metrics": [ # Provides a list of metrics that act as inputs into the objective function.
{ # A message representing a metric in the measurement.
"metric": "A String", # Required. Metric name.
"value": 3.14, # Required. The value for this metric.
},
],
"stepCount": "A String", # The number of steps a machine learning model has been trained for. Must be non-negative.
},
],
"name": "A String", # Output only. Name of the trial assigned by the service.
"parameters": [ # The parameters of the trial.
{ # A message representing a parameter to be tuned. Contains the name of the parameter and the suggested value to use for this trial.
"floatValue": 3.14, # Must be set if ParameterType is DOUBLE or DISCRETE.
"intValue": "A String", # Must be set if ParameterType is INTEGER
"parameter": "A String", # The name of the parameter.
"stringValue": "A String", # Must be set if ParameterTypeis CATEGORICAL
},
],
"startTime": "A String", # Output only. Time at which the trial was started.
"state": "A String", # The detailed state of a trial.
"trialInfeasible": True or False, # Output only. If true, the parameters in this trial are not attempted again.
}</pre>
</div>
<div class="method">
<code class="details" id="suggest">suggest(parent, body=None, x__xgafv=None)</code>
<pre>Adds one or more trials to a study, with parameter values suggested by AI Platform Vizier. Returns a long-running operation associated with the generation of trial suggestions. When this long-running operation succeeds, it will contain a SuggestTrialsResponse.
Args:
parent: string, Required. The name of the study that the trial belongs to. (required)
body: object, The request body.
The object takes the form of:
{ # The request message for the SuggestTrial service method.
"clientId": "A String", # Required. The identifier of the client that is requesting the suggestion. If multiple SuggestTrialsRequests have the same `client_id`, the service will return the identical suggested trial if the trial is pending, and provide a new trial if the last suggested trial was completed.
"suggestionCount": 42, # Required. The number of suggestions requested.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}</pre>
</div>
</body></html>
|
