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