Sai Cheemalapati | ea3a5e1 | 2016-10-12 14:05:53 -0700 | [diff] [blame] | 1 | <html><body> |
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| 75 | <h1><a href="ml_v1beta1.html">Google Cloud Machine Learning</a> . <a href="ml_v1beta1.projects.html">projects</a> . <a href="ml_v1beta1.projects.jobs.html">jobs</a></h1> |
| 76 | <h2>Instance Methods</h2> |
| 77 | <p class="toc_element"> |
| 78 | <code><a href="#cancel">cancel(name=None, body, x__xgafv=None)</a></code></p> |
| 79 | <p class="firstline">Cancels a running job.</p> |
| 80 | <p class="toc_element"> |
| 81 | <code><a href="#create">create(parent=None, body, x__xgafv=None)</a></code></p> |
| 82 | <p class="firstline">Creates a training or a batch prediction job.</p> |
| 83 | <p class="toc_element"> |
| 84 | <code><a href="#get">get(name=None, x__xgafv=None)</a></code></p> |
| 85 | <p class="firstline">Describes a job.</p> |
| 86 | <p class="toc_element"> |
| 87 | <code><a href="#list">list(parent=None, pageSize=None, filter=None, pageToken=None, x__xgafv=None)</a></code></p> |
| 88 | <p class="firstline">Lists the jobs in the project.</p> |
| 89 | <p class="toc_element"> |
| 90 | <code><a href="#list_next">list_next(previous_request, previous_response)</a></code></p> |
| 91 | <p class="firstline">Retrieves the next page of results.</p> |
| 92 | <h3>Method Details</h3> |
| 93 | <div class="method"> |
| 94 | <code class="details" id="cancel">cancel(name=None, body, x__xgafv=None)</code> |
| 95 | <pre>Cancels a running job. |
| 96 | |
| 97 | Args: |
| 98 | name: string, Required. The name of the job to cancel. |
| 99 | |
| 100 | Authorization: requires `Editor` role on the parent project. (required) |
| 101 | body: object, The request body. (required) |
| 102 | The object takes the form of: |
| 103 | |
| 104 | { # Request message for the CancelJob method. |
| 105 | } |
| 106 | |
| 107 | x__xgafv: string, V1 error format. |
| 108 | Allowed values |
| 109 | 1 - v1 error format |
| 110 | 2 - v2 error format |
| 111 | |
| 112 | Returns: |
| 113 | An object of the form: |
| 114 | |
| 115 | { # A generic empty message that you can re-use to avoid defining duplicated |
| 116 | # empty messages in your APIs. A typical example is to use it as the request |
| 117 | # or the response type of an API method. For instance: |
| 118 | # |
| 119 | # service Foo { |
| 120 | # rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); |
| 121 | # } |
| 122 | # |
| 123 | # The JSON representation for `Empty` is empty JSON object `{}`. |
| 124 | }</pre> |
| 125 | </div> |
| 126 | |
| 127 | <div class="method"> |
| 128 | <code class="details" id="create">create(parent=None, body, x__xgafv=None)</code> |
| 129 | <pre>Creates a training or a batch prediction job. |
| 130 | |
| 131 | Args: |
| 132 | parent: string, Required. The project name. |
| 133 | |
| 134 | Authorization: requires `Editor` role on the specified project. (required) |
| 135 | body: object, The request body. (required) |
| 136 | The object takes the form of: |
| 137 | |
| 138 | { # Represents a training or prediction job. |
| 139 | "trainingOutput": { # Represents results of a training job. # The current training job result. |
| 140 | "completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully. |
| 141 | "trials": [ # Results for individual Hyperparameter trials. |
| 142 | { # Represents the result of a single hyperparameter tuning trial from a |
| 143 | # training job. The TrainingOutput object that is returned on successful |
| 144 | # completion of a training job with hyperparameter tuning includes a list |
| 145 | # of HyperparameterOutput objects, one for each successful trial. |
| 146 | "hyperparameters": { # The hyperparameters given to this trial. |
| 147 | "a_key": "A String", |
| 148 | }, |
| 149 | "trialId": "A String", # The trial id for these results. |
| 150 | "allMetrics": [ # All recorded object metrics for this trial. |
| 151 | { # An observed value of a metric. |
| 152 | "trainingStep": "A String", # The global training step for this metric. |
| 153 | "objectiveValue": 3.14, # The objective value at this training step. |
| 154 | }, |
| 155 | ], |
| 156 | "finalMetric": { # An observed value of a metric. # The final objective metric seen for this trial. |
| 157 | "trainingStep": "A String", # The global training step for this metric. |
| 158 | "objectiveValue": 3.14, # The objective value at this training step. |
| 159 | }, |
| 160 | }, |
| 161 | ], |
| 162 | }, |
| 163 | "startTime": "A String", # Output only. When the job processing was started. |
| 164 | "errorMessage": "A String", # Output only. The details of a failure or a cancellation. |
| 165 | "jobId": "A String", # Required. The user-specified id of the job. |
| 166 | "state": "A String", # Output only. The detailed state of a job. |
| 167 | "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job. |
| 168 | "modelName": "A String", # Use this field if you want to use the default version for the specified |
| 169 | # model. The string must use the following format: |
| 170 | # |
| 171 | # `"project/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"` |
| 172 | "inputPaths": [ # Required. The Google Cloud Storage location of the input data files. |
| 173 | # May contain wildcards. |
| 174 | "A String", |
| 175 | ], |
| 176 | "maxWorkerCount": "A String", # Optional. The maximum amount of workers to be used for parallel processing. |
| 177 | # Defaults to 10. |
| 178 | "outputPath": "A String", # Required. The output Google Cloud Storage location. |
| 179 | "dataFormat": "A String", # Required. The format of the input data files. |
| 180 | "versionName": "A String", # Use this field if you want to specify a version of the model to use. The |
| 181 | # string is formatted the same way as `model_version`, with the addition |
| 182 | # of the version information: |
| 183 | # |
| 184 | # `"project/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"` |
| 185 | "region": "A String", # Required. The Google Compute Engine region to run the prediction job in. |
| 186 | }, |
| 187 | "trainingInput": { # Represents input parameters for a training job. # Input parameters to create a training job. |
| 188 | "workerType": "A String", # Optional. Specifies the type of virtual machine to use for your training |
| 189 | # job's worker nodes. |
| 190 | # |
| 191 | # The supported values are the same as those described in the entry for |
| 192 | # `masterType`. |
| 193 | # |
| 194 | # This value must be present when `scaleTier` is set to `CUSTOM` and |
| 195 | # `workerCount` is greater than zero. |
| 196 | "scaleTier": "A String", # Required. Specifies the machine types, the number of replicas for workers |
| 197 | # and parameter servers. |
| 198 | "masterType": "A String", # Optional. Specifies the type of virtual machine to use for your training |
| 199 | # job's master worker. |
| 200 | # |
| 201 | # The following types are supported: |
| 202 | # |
| 203 | # <dl> |
| 204 | # <dt>standard</dt> |
| 205 | # <dd> |
| 206 | # A basic machine configuration suitable for training simple models with |
| 207 | # small to moderate datasets. |
| 208 | # </dd> |
| 209 | # <dt>large_model</dt> |
| 210 | # <dd> |
| 211 | # A machine with a lot of memory, specially suited for parameter servers |
| 212 | # when your model is large (having many hidden layers or layers with very |
| 213 | # large numbers of nodes). |
| 214 | # </dd> |
| 215 | # <dt>complex_model_s</dt> |
| 216 | # <dd> |
| 217 | # A machine suitable for the master and workers of the cluster when your |
| 218 | # model requires more computation than the standard machine can handle |
| 219 | # satisfactorily. |
| 220 | # </dd> |
| 221 | # <dt>complex_model_m</dt> |
| 222 | # <dd> |
| 223 | # A machine with roughly twice the number of cores and roughly double the |
| 224 | # memory of <code suppresswarning="true">complex_model_s</code>. |
| 225 | # </dd> |
| 226 | # <dt>complex_model_l</dt> |
| 227 | # <dd> |
| 228 | # A machine with roughly twice the number of cores and roughly double the |
| 229 | # memory of <code suppresswarning="true">complex_model_m</code>. |
| 230 | # </dd> |
| 231 | # </dl> |
| 232 | # |
| 233 | # You must set this value when `scaleTier` is set to `CUSTOM`. |
| 234 | "hyperparameters": { # Represents a set of hyperparameters to optimize. # Optional. The set of Hyperparameters to tune. |
| 235 | "maxTrials": 42, # Optional. How many training trials should be attempted to optimize |
| 236 | # the specified hyperparameters. |
| 237 | # |
| 238 | # Defaults to one. |
| 239 | "params": [ # Required. The set of parameters to tune. |
| 240 | { # Represents a single hyperparameter to optimize. |
| 241 | "maxValue": 3.14, # Required if typeis `DOUBLE` or `INTEGER`. This field |
| 242 | # should be unset if type is `CATEGORICAL`. This value should be integers if |
| 243 | # type is `INTEGER`. |
| 244 | "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field |
| 245 | # should be unset if type is `CATEGORICAL`. This value should be integers if |
| 246 | # type is INTEGER. |
| 247 | "discreteValues": [ # Required if type is `DISCRETE`. |
| 248 | # A list of feasible points. |
| 249 | # The list should be in strictly increasing order. For instance, this |
| 250 | # parameter might have possible settings of 1.5, 2.5, and 4.0. This list |
| 251 | # should not contain more than 1,000 values. |
| 252 | 3.14, |
| 253 | ], |
| 254 | "parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in |
| 255 | # a HyperparameterSpec message. E.g., "learning_rate". |
| 256 | "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories. |
| 257 | "A String", |
| 258 | ], |
| 259 | "type": "A String", # Required. The type of the parameter. |
| 260 | "scaleType": "A String", # Optional. How the parameter should be scaled to the hypercube. |
| 261 | # Leave unset for categorical parameters. |
| 262 | # Some kind of scaling is strongly recommended for real or integral |
| 263 | # parameters (e.g., `UNIT_LINEAR_SCALE`). |
| 264 | }, |
| 265 | ], |
| 266 | "maxParallelTrials": 42, # Optional. The number of training trials to run concurrently. |
| 267 | # You can reduce the time it takes to perform hyperparameter tuning by adding |
| 268 | # trials in parallel. However, each trail only benefits from the information |
| 269 | # gained in completed trials. That means that a trial does not get access to |
| 270 | # the results of trials running at the same time, which could reduce the |
| 271 | # quality of the overall optimization. |
| 272 | # |
| 273 | # Each trial will use the same scale tier and machine types. |
| 274 | # |
| 275 | # Defaults to one. |
| 276 | "goal": "A String", # Required. The type of goal to use for tuning. Available types are |
| 277 | # `MAXIMIZE` and `MINIMIZE`. |
| 278 | # |
| 279 | # Defaults to `MAXIMIZE`. |
| 280 | }, |
| 281 | "region": "A String", # Required. The Google Compute Engine region to run the training job in. |
| 282 | "args": [ # Optional. Command line arguments to pass to the program. |
| 283 | "A String", |
| 284 | ], |
| 285 | "pythonModule": "A String", # Required. The Python module name to run after installing the packages. |
| 286 | "packageUris": [ # Required. The Google Cloud Storage location of the packages with |
| 287 | # the training program and any additional dependencies. |
| 288 | "A String", |
| 289 | ], |
| 290 | "workerCount": "A String", # Optional. The number of worker replicas to use for the training job. Each |
| 291 | # replica in the cluster will be of the type specified in `worker_type`. |
| 292 | # |
| 293 | # This value can only be used when `scale_tier` is set to `CUSTOM`. If you |
| 294 | # set this value, you must also set `worker_type`. |
| 295 | "parameterServerType": "A String", # Optional. Specifies the type of virtual machine to use for your training |
| 296 | # job's parameter server. |
| 297 | # |
| 298 | # The supported values are the same as those described in the entry for |
| 299 | # `master_type`. |
| 300 | # |
| 301 | # This value must be present when `scaleTier` is set to `CUSTOM` and |
| 302 | # `parameter_server_count` is greater than zero. |
| 303 | "parameterServerCount": "A String", # Optional. The number of parameter server replicas to use for the training |
| 304 | # job. Each replica in the cluster will be of the type specified in |
| 305 | # `parameter_server_type`. |
| 306 | # |
| 307 | # This value can only be used when `scale_tier` is set to `CUSTOM`.If you |
| 308 | # set this value, you must also set `parameter_server_type`. |
| 309 | }, |
| 310 | "endTime": "A String", # Output only. When the job processing was completed. |
| 311 | "predictionOutput": { # Represents results of a prediction job. # The current prediction job result. |
| 312 | "outputPath": "A String", # The output Google Cloud Storage location provided at the job creation time. |
| 313 | "predictionCount": "A String", # The number of generated predictions. |
| 314 | "errorCount": "A String", # The number of data instances which resulted in errors. |
| 315 | }, |
| 316 | "createTime": "A String", # Output only. When the job was created. |
| 317 | } |
| 318 | |
| 319 | x__xgafv: string, V1 error format. |
| 320 | Allowed values |
| 321 | 1 - v1 error format |
| 322 | 2 - v2 error format |
| 323 | |
| 324 | Returns: |
| 325 | An object of the form: |
| 326 | |
| 327 | { # Represents a training or prediction job. |
| 328 | "trainingOutput": { # Represents results of a training job. # The current training job result. |
| 329 | "completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully. |
| 330 | "trials": [ # Results for individual Hyperparameter trials. |
| 331 | { # Represents the result of a single hyperparameter tuning trial from a |
| 332 | # training job. The TrainingOutput object that is returned on successful |
| 333 | # completion of a training job with hyperparameter tuning includes a list |
| 334 | # of HyperparameterOutput objects, one for each successful trial. |
| 335 | "hyperparameters": { # The hyperparameters given to this trial. |
| 336 | "a_key": "A String", |
| 337 | }, |
| 338 | "trialId": "A String", # The trial id for these results. |
| 339 | "allMetrics": [ # All recorded object metrics for this trial. |
| 340 | { # An observed value of a metric. |
| 341 | "trainingStep": "A String", # The global training step for this metric. |
| 342 | "objectiveValue": 3.14, # The objective value at this training step. |
| 343 | }, |
| 344 | ], |
| 345 | "finalMetric": { # An observed value of a metric. # The final objective metric seen for this trial. |
| 346 | "trainingStep": "A String", # The global training step for this metric. |
| 347 | "objectiveValue": 3.14, # The objective value at this training step. |
| 348 | }, |
| 349 | }, |
| 350 | ], |
| 351 | }, |
| 352 | "startTime": "A String", # Output only. When the job processing was started. |
| 353 | "errorMessage": "A String", # Output only. The details of a failure or a cancellation. |
| 354 | "jobId": "A String", # Required. The user-specified id of the job. |
| 355 | "state": "A String", # Output only. The detailed state of a job. |
| 356 | "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job. |
| 357 | "modelName": "A String", # Use this field if you want to use the default version for the specified |
| 358 | # model. The string must use the following format: |
| 359 | # |
| 360 | # `"project/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"` |
| 361 | "inputPaths": [ # Required. The Google Cloud Storage location of the input data files. |
| 362 | # May contain wildcards. |
| 363 | "A String", |
| 364 | ], |
| 365 | "maxWorkerCount": "A String", # Optional. The maximum amount of workers to be used for parallel processing. |
| 366 | # Defaults to 10. |
| 367 | "outputPath": "A String", # Required. The output Google Cloud Storage location. |
| 368 | "dataFormat": "A String", # Required. The format of the input data files. |
| 369 | "versionName": "A String", # Use this field if you want to specify a version of the model to use. The |
| 370 | # string is formatted the same way as `model_version`, with the addition |
| 371 | # of the version information: |
| 372 | # |
| 373 | # `"project/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"` |
| 374 | "region": "A String", # Required. The Google Compute Engine region to run the prediction job in. |
| 375 | }, |
| 376 | "trainingInput": { # Represents input parameters for a training job. # Input parameters to create a training job. |
| 377 | "workerType": "A String", # Optional. Specifies the type of virtual machine to use for your training |
| 378 | # job's worker nodes. |
| 379 | # |
| 380 | # The supported values are the same as those described in the entry for |
| 381 | # `masterType`. |
| 382 | # |
| 383 | # This value must be present when `scaleTier` is set to `CUSTOM` and |
| 384 | # `workerCount` is greater than zero. |
| 385 | "scaleTier": "A String", # Required. Specifies the machine types, the number of replicas for workers |
| 386 | # and parameter servers. |
| 387 | "masterType": "A String", # Optional. Specifies the type of virtual machine to use for your training |
| 388 | # job's master worker. |
| 389 | # |
| 390 | # The following types are supported: |
| 391 | # |
| 392 | # <dl> |
| 393 | # <dt>standard</dt> |
| 394 | # <dd> |
| 395 | # A basic machine configuration suitable for training simple models with |
| 396 | # small to moderate datasets. |
| 397 | # </dd> |
| 398 | # <dt>large_model</dt> |
| 399 | # <dd> |
| 400 | # A machine with a lot of memory, specially suited for parameter servers |
| 401 | # when your model is large (having many hidden layers or layers with very |
| 402 | # large numbers of nodes). |
| 403 | # </dd> |
| 404 | # <dt>complex_model_s</dt> |
| 405 | # <dd> |
| 406 | # A machine suitable for the master and workers of the cluster when your |
| 407 | # model requires more computation than the standard machine can handle |
| 408 | # satisfactorily. |
| 409 | # </dd> |
| 410 | # <dt>complex_model_m</dt> |
| 411 | # <dd> |
| 412 | # A machine with roughly twice the number of cores and roughly double the |
| 413 | # memory of <code suppresswarning="true">complex_model_s</code>. |
| 414 | # </dd> |
| 415 | # <dt>complex_model_l</dt> |
| 416 | # <dd> |
| 417 | # A machine with roughly twice the number of cores and roughly double the |
| 418 | # memory of <code suppresswarning="true">complex_model_m</code>. |
| 419 | # </dd> |
| 420 | # </dl> |
| 421 | # |
| 422 | # You must set this value when `scaleTier` is set to `CUSTOM`. |
| 423 | "hyperparameters": { # Represents a set of hyperparameters to optimize. # Optional. The set of Hyperparameters to tune. |
| 424 | "maxTrials": 42, # Optional. How many training trials should be attempted to optimize |
| 425 | # the specified hyperparameters. |
| 426 | # |
| 427 | # Defaults to one. |
| 428 | "params": [ # Required. The set of parameters to tune. |
| 429 | { # Represents a single hyperparameter to optimize. |
| 430 | "maxValue": 3.14, # Required if typeis `DOUBLE` or `INTEGER`. This field |
| 431 | # should be unset if type is `CATEGORICAL`. This value should be integers if |
| 432 | # type is `INTEGER`. |
| 433 | "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field |
| 434 | # should be unset if type is `CATEGORICAL`. This value should be integers if |
| 435 | # type is INTEGER. |
| 436 | "discreteValues": [ # Required if type is `DISCRETE`. |
| 437 | # A list of feasible points. |
| 438 | # The list should be in strictly increasing order. For instance, this |
| 439 | # parameter might have possible settings of 1.5, 2.5, and 4.0. This list |
| 440 | # should not contain more than 1,000 values. |
| 441 | 3.14, |
| 442 | ], |
| 443 | "parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in |
| 444 | # a HyperparameterSpec message. E.g., "learning_rate". |
| 445 | "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories. |
| 446 | "A String", |
| 447 | ], |
| 448 | "type": "A String", # Required. The type of the parameter. |
| 449 | "scaleType": "A String", # Optional. How the parameter should be scaled to the hypercube. |
| 450 | # Leave unset for categorical parameters. |
| 451 | # Some kind of scaling is strongly recommended for real or integral |
| 452 | # parameters (e.g., `UNIT_LINEAR_SCALE`). |
| 453 | }, |
| 454 | ], |
| 455 | "maxParallelTrials": 42, # Optional. The number of training trials to run concurrently. |
| 456 | # You can reduce the time it takes to perform hyperparameter tuning by adding |
| 457 | # trials in parallel. However, each trail only benefits from the information |
| 458 | # gained in completed trials. That means that a trial does not get access to |
| 459 | # the results of trials running at the same time, which could reduce the |
| 460 | # quality of the overall optimization. |
| 461 | # |
| 462 | # Each trial will use the same scale tier and machine types. |
| 463 | # |
| 464 | # Defaults to one. |
| 465 | "goal": "A String", # Required. The type of goal to use for tuning. Available types are |
| 466 | # `MAXIMIZE` and `MINIMIZE`. |
| 467 | # |
| 468 | # Defaults to `MAXIMIZE`. |
| 469 | }, |
| 470 | "region": "A String", # Required. The Google Compute Engine region to run the training job in. |
| 471 | "args": [ # Optional. Command line arguments to pass to the program. |
| 472 | "A String", |
| 473 | ], |
| 474 | "pythonModule": "A String", # Required. The Python module name to run after installing the packages. |
| 475 | "packageUris": [ # Required. The Google Cloud Storage location of the packages with |
| 476 | # the training program and any additional dependencies. |
| 477 | "A String", |
| 478 | ], |
| 479 | "workerCount": "A String", # Optional. The number of worker replicas to use for the training job. Each |
| 480 | # replica in the cluster will be of the type specified in `worker_type`. |
| 481 | # |
| 482 | # This value can only be used when `scale_tier` is set to `CUSTOM`. If you |
| 483 | # set this value, you must also set `worker_type`. |
| 484 | "parameterServerType": "A String", # Optional. Specifies the type of virtual machine to use for your training |
| 485 | # job's parameter server. |
| 486 | # |
| 487 | # The supported values are the same as those described in the entry for |
| 488 | # `master_type`. |
| 489 | # |
| 490 | # This value must be present when `scaleTier` is set to `CUSTOM` and |
| 491 | # `parameter_server_count` is greater than zero. |
| 492 | "parameterServerCount": "A String", # Optional. The number of parameter server replicas to use for the training |
| 493 | # job. Each replica in the cluster will be of the type specified in |
| 494 | # `parameter_server_type`. |
| 495 | # |
| 496 | # This value can only be used when `scale_tier` is set to `CUSTOM`.If you |
| 497 | # set this value, you must also set `parameter_server_type`. |
| 498 | }, |
| 499 | "endTime": "A String", # Output only. When the job processing was completed. |
| 500 | "predictionOutput": { # Represents results of a prediction job. # The current prediction job result. |
| 501 | "outputPath": "A String", # The output Google Cloud Storage location provided at the job creation time. |
| 502 | "predictionCount": "A String", # The number of generated predictions. |
| 503 | "errorCount": "A String", # The number of data instances which resulted in errors. |
| 504 | }, |
| 505 | "createTime": "A String", # Output only. When the job was created. |
| 506 | }</pre> |
| 507 | </div> |
| 508 | |
| 509 | <div class="method"> |
| 510 | <code class="details" id="get">get(name=None, x__xgafv=None)</code> |
| 511 | <pre>Describes a job. |
| 512 | |
| 513 | Args: |
| 514 | name: string, Required. The name of the job to get the description of. |
| 515 | |
| 516 | Authorization: requires `Viewer` role on the parent project. (required) |
| 517 | x__xgafv: string, V1 error format. |
| 518 | Allowed values |
| 519 | 1 - v1 error format |
| 520 | 2 - v2 error format |
| 521 | |
| 522 | Returns: |
| 523 | An object of the form: |
| 524 | |
| 525 | { # Represents a training or prediction job. |
| 526 | "trainingOutput": { # Represents results of a training job. # The current training job result. |
| 527 | "completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully. |
| 528 | "trials": [ # Results for individual Hyperparameter trials. |
| 529 | { # Represents the result of a single hyperparameter tuning trial from a |
| 530 | # training job. The TrainingOutput object that is returned on successful |
| 531 | # completion of a training job with hyperparameter tuning includes a list |
| 532 | # of HyperparameterOutput objects, one for each successful trial. |
| 533 | "hyperparameters": { # The hyperparameters given to this trial. |
| 534 | "a_key": "A String", |
| 535 | }, |
| 536 | "trialId": "A String", # The trial id for these results. |
| 537 | "allMetrics": [ # All recorded object metrics for this trial. |
| 538 | { # An observed value of a metric. |
| 539 | "trainingStep": "A String", # The global training step for this metric. |
| 540 | "objectiveValue": 3.14, # The objective value at this training step. |
| 541 | }, |
| 542 | ], |
| 543 | "finalMetric": { # An observed value of a metric. # The final objective metric seen for this trial. |
| 544 | "trainingStep": "A String", # The global training step for this metric. |
| 545 | "objectiveValue": 3.14, # The objective value at this training step. |
| 546 | }, |
| 547 | }, |
| 548 | ], |
| 549 | }, |
| 550 | "startTime": "A String", # Output only. When the job processing was started. |
| 551 | "errorMessage": "A String", # Output only. The details of a failure or a cancellation. |
| 552 | "jobId": "A String", # Required. The user-specified id of the job. |
| 553 | "state": "A String", # Output only. The detailed state of a job. |
| 554 | "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job. |
| 555 | "modelName": "A String", # Use this field if you want to use the default version for the specified |
| 556 | # model. The string must use the following format: |
| 557 | # |
| 558 | # `"project/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"` |
| 559 | "inputPaths": [ # Required. The Google Cloud Storage location of the input data files. |
| 560 | # May contain wildcards. |
| 561 | "A String", |
| 562 | ], |
| 563 | "maxWorkerCount": "A String", # Optional. The maximum amount of workers to be used for parallel processing. |
| 564 | # Defaults to 10. |
| 565 | "outputPath": "A String", # Required. The output Google Cloud Storage location. |
| 566 | "dataFormat": "A String", # Required. The format of the input data files. |
| 567 | "versionName": "A String", # Use this field if you want to specify a version of the model to use. The |
| 568 | # string is formatted the same way as `model_version`, with the addition |
| 569 | # of the version information: |
| 570 | # |
| 571 | # `"project/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"` |
| 572 | "region": "A String", # Required. The Google Compute Engine region to run the prediction job in. |
| 573 | }, |
| 574 | "trainingInput": { # Represents input parameters for a training job. # Input parameters to create a training job. |
| 575 | "workerType": "A String", # Optional. Specifies the type of virtual machine to use for your training |
| 576 | # job's worker nodes. |
| 577 | # |
| 578 | # The supported values are the same as those described in the entry for |
| 579 | # `masterType`. |
| 580 | # |
| 581 | # This value must be present when `scaleTier` is set to `CUSTOM` and |
| 582 | # `workerCount` is greater than zero. |
| 583 | "scaleTier": "A String", # Required. Specifies the machine types, the number of replicas for workers |
| 584 | # and parameter servers. |
| 585 | "masterType": "A String", # Optional. Specifies the type of virtual machine to use for your training |
| 586 | # job's master worker. |
| 587 | # |
| 588 | # The following types are supported: |
| 589 | # |
| 590 | # <dl> |
| 591 | # <dt>standard</dt> |
| 592 | # <dd> |
| 593 | # A basic machine configuration suitable for training simple models with |
| 594 | # small to moderate datasets. |
| 595 | # </dd> |
| 596 | # <dt>large_model</dt> |
| 597 | # <dd> |
| 598 | # A machine with a lot of memory, specially suited for parameter servers |
| 599 | # when your model is large (having many hidden layers or layers with very |
| 600 | # large numbers of nodes). |
| 601 | # </dd> |
| 602 | # <dt>complex_model_s</dt> |
| 603 | # <dd> |
| 604 | # A machine suitable for the master and workers of the cluster when your |
| 605 | # model requires more computation than the standard machine can handle |
| 606 | # satisfactorily. |
| 607 | # </dd> |
| 608 | # <dt>complex_model_m</dt> |
| 609 | # <dd> |
| 610 | # A machine with roughly twice the number of cores and roughly double the |
| 611 | # memory of <code suppresswarning="true">complex_model_s</code>. |
| 612 | # </dd> |
| 613 | # <dt>complex_model_l</dt> |
| 614 | # <dd> |
| 615 | # A machine with roughly twice the number of cores and roughly double the |
| 616 | # memory of <code suppresswarning="true">complex_model_m</code>. |
| 617 | # </dd> |
| 618 | # </dl> |
| 619 | # |
| 620 | # You must set this value when `scaleTier` is set to `CUSTOM`. |
| 621 | "hyperparameters": { # Represents a set of hyperparameters to optimize. # Optional. The set of Hyperparameters to tune. |
| 622 | "maxTrials": 42, # Optional. How many training trials should be attempted to optimize |
| 623 | # the specified hyperparameters. |
| 624 | # |
| 625 | # Defaults to one. |
| 626 | "params": [ # Required. The set of parameters to tune. |
| 627 | { # Represents a single hyperparameter to optimize. |
| 628 | "maxValue": 3.14, # Required if typeis `DOUBLE` or `INTEGER`. This field |
| 629 | # should be unset if type is `CATEGORICAL`. This value should be integers if |
| 630 | # type is `INTEGER`. |
| 631 | "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field |
| 632 | # should be unset if type is `CATEGORICAL`. This value should be integers if |
| 633 | # type is INTEGER. |
| 634 | "discreteValues": [ # Required if type is `DISCRETE`. |
| 635 | # A list of feasible points. |
| 636 | # The list should be in strictly increasing order. For instance, this |
| 637 | # parameter might have possible settings of 1.5, 2.5, and 4.0. This list |
| 638 | # should not contain more than 1,000 values. |
| 639 | 3.14, |
| 640 | ], |
| 641 | "parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in |
| 642 | # a HyperparameterSpec message. E.g., "learning_rate". |
| 643 | "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories. |
| 644 | "A String", |
| 645 | ], |
| 646 | "type": "A String", # Required. The type of the parameter. |
| 647 | "scaleType": "A String", # Optional. How the parameter should be scaled to the hypercube. |
| 648 | # Leave unset for categorical parameters. |
| 649 | # Some kind of scaling is strongly recommended for real or integral |
| 650 | # parameters (e.g., `UNIT_LINEAR_SCALE`). |
| 651 | }, |
| 652 | ], |
| 653 | "maxParallelTrials": 42, # Optional. The number of training trials to run concurrently. |
| 654 | # You can reduce the time it takes to perform hyperparameter tuning by adding |
| 655 | # trials in parallel. However, each trail only benefits from the information |
| 656 | # gained in completed trials. That means that a trial does not get access to |
| 657 | # the results of trials running at the same time, which could reduce the |
| 658 | # quality of the overall optimization. |
| 659 | # |
| 660 | # Each trial will use the same scale tier and machine types. |
| 661 | # |
| 662 | # Defaults to one. |
| 663 | "goal": "A String", # Required. The type of goal to use for tuning. Available types are |
| 664 | # `MAXIMIZE` and `MINIMIZE`. |
| 665 | # |
| 666 | # Defaults to `MAXIMIZE`. |
| 667 | }, |
| 668 | "region": "A String", # Required. The Google Compute Engine region to run the training job in. |
| 669 | "args": [ # Optional. Command line arguments to pass to the program. |
| 670 | "A String", |
| 671 | ], |
| 672 | "pythonModule": "A String", # Required. The Python module name to run after installing the packages. |
| 673 | "packageUris": [ # Required. The Google Cloud Storage location of the packages with |
| 674 | # the training program and any additional dependencies. |
| 675 | "A String", |
| 676 | ], |
| 677 | "workerCount": "A String", # Optional. The number of worker replicas to use for the training job. Each |
| 678 | # replica in the cluster will be of the type specified in `worker_type`. |
| 679 | # |
| 680 | # This value can only be used when `scale_tier` is set to `CUSTOM`. If you |
| 681 | # set this value, you must also set `worker_type`. |
| 682 | "parameterServerType": "A String", # Optional. Specifies the type of virtual machine to use for your training |
| 683 | # job's parameter server. |
| 684 | # |
| 685 | # The supported values are the same as those described in the entry for |
| 686 | # `master_type`. |
| 687 | # |
| 688 | # This value must be present when `scaleTier` is set to `CUSTOM` and |
| 689 | # `parameter_server_count` is greater than zero. |
| 690 | "parameterServerCount": "A String", # Optional. The number of parameter server replicas to use for the training |
| 691 | # job. Each replica in the cluster will be of the type specified in |
| 692 | # `parameter_server_type`. |
| 693 | # |
| 694 | # This value can only be used when `scale_tier` is set to `CUSTOM`.If you |
| 695 | # set this value, you must also set `parameter_server_type`. |
| 696 | }, |
| 697 | "endTime": "A String", # Output only. When the job processing was completed. |
| 698 | "predictionOutput": { # Represents results of a prediction job. # The current prediction job result. |
| 699 | "outputPath": "A String", # The output Google Cloud Storage location provided at the job creation time. |
| 700 | "predictionCount": "A String", # The number of generated predictions. |
| 701 | "errorCount": "A String", # The number of data instances which resulted in errors. |
| 702 | }, |
| 703 | "createTime": "A String", # Output only. When the job was created. |
| 704 | }</pre> |
| 705 | </div> |
| 706 | |
| 707 | <div class="method"> |
| 708 | <code class="details" id="list">list(parent=None, pageSize=None, filter=None, pageToken=None, x__xgafv=None)</code> |
| 709 | <pre>Lists the jobs in the project. |
| 710 | |
| 711 | Args: |
| 712 | parent: string, Required. The name of the project for which to list jobs. |
| 713 | |
| 714 | Authorization: requires `Viewer` role on the specified project. (required) |
| 715 | pageSize: integer, Optional. The number of jobs to retrieve per "page" of results. If there |
| 716 | are more remaining results than this number, the response message will |
| 717 | contain a valid value in the `next_page_token` field. |
| 718 | |
| 719 | The default value is 20, and the maximum page size is 100. |
| 720 | filter: string, Optional. Specifies the subset of jobs to retrieve. |
| 721 | pageToken: string, Optional. A page token to request the next page of results. |
| 722 | |
| 723 | You get the token from the `next_page_token` field of the response from |
| 724 | the previous call. |
| 725 | x__xgafv: string, V1 error format. |
| 726 | Allowed values |
| 727 | 1 - v1 error format |
| 728 | 2 - v2 error format |
| 729 | |
| 730 | Returns: |
| 731 | An object of the form: |
| 732 | |
| 733 | { # Response message for the ListJobs method. |
| 734 | "nextPageToken": "A String", # Optional. Pass this token as the `page_token` field of the request for a |
| 735 | # subsequent call. |
| 736 | "jobs": [ # The list of jobs. |
| 737 | { # Represents a training or prediction job. |
| 738 | "trainingOutput": { # Represents results of a training job. # The current training job result. |
| 739 | "completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully. |
| 740 | "trials": [ # Results for individual Hyperparameter trials. |
| 741 | { # Represents the result of a single hyperparameter tuning trial from a |
| 742 | # training job. The TrainingOutput object that is returned on successful |
| 743 | # completion of a training job with hyperparameter tuning includes a list |
| 744 | # of HyperparameterOutput objects, one for each successful trial. |
| 745 | "hyperparameters": { # The hyperparameters given to this trial. |
| 746 | "a_key": "A String", |
| 747 | }, |
| 748 | "trialId": "A String", # The trial id for these results. |
| 749 | "allMetrics": [ # All recorded object metrics for this trial. |
| 750 | { # An observed value of a metric. |
| 751 | "trainingStep": "A String", # The global training step for this metric. |
| 752 | "objectiveValue": 3.14, # The objective value at this training step. |
| 753 | }, |
| 754 | ], |
| 755 | "finalMetric": { # An observed value of a metric. # The final objective metric seen for this trial. |
| 756 | "trainingStep": "A String", # The global training step for this metric. |
| 757 | "objectiveValue": 3.14, # The objective value at this training step. |
| 758 | }, |
| 759 | }, |
| 760 | ], |
| 761 | }, |
| 762 | "startTime": "A String", # Output only. When the job processing was started. |
| 763 | "errorMessage": "A String", # Output only. The details of a failure or a cancellation. |
| 764 | "jobId": "A String", # Required. The user-specified id of the job. |
| 765 | "state": "A String", # Output only. The detailed state of a job. |
| 766 | "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job. |
| 767 | "modelName": "A String", # Use this field if you want to use the default version for the specified |
| 768 | # model. The string must use the following format: |
| 769 | # |
| 770 | # `"project/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"` |
| 771 | "inputPaths": [ # Required. The Google Cloud Storage location of the input data files. |
| 772 | # May contain wildcards. |
| 773 | "A String", |
| 774 | ], |
| 775 | "maxWorkerCount": "A String", # Optional. The maximum amount of workers to be used for parallel processing. |
| 776 | # Defaults to 10. |
| 777 | "outputPath": "A String", # Required. The output Google Cloud Storage location. |
| 778 | "dataFormat": "A String", # Required. The format of the input data files. |
| 779 | "versionName": "A String", # Use this field if you want to specify a version of the model to use. The |
| 780 | # string is formatted the same way as `model_version`, with the addition |
| 781 | # of the version information: |
| 782 | # |
| 783 | # `"project/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"` |
| 784 | "region": "A String", # Required. The Google Compute Engine region to run the prediction job in. |
| 785 | }, |
| 786 | "trainingInput": { # Represents input parameters for a training job. # Input parameters to create a training job. |
| 787 | "workerType": "A String", # Optional. Specifies the type of virtual machine to use for your training |
| 788 | # job's worker nodes. |
| 789 | # |
| 790 | # The supported values are the same as those described in the entry for |
| 791 | # `masterType`. |
| 792 | # |
| 793 | # This value must be present when `scaleTier` is set to `CUSTOM` and |
| 794 | # `workerCount` is greater than zero. |
| 795 | "scaleTier": "A String", # Required. Specifies the machine types, the number of replicas for workers |
| 796 | # and parameter servers. |
| 797 | "masterType": "A String", # Optional. Specifies the type of virtual machine to use for your training |
| 798 | # job's master worker. |
| 799 | # |
| 800 | # The following types are supported: |
| 801 | # |
| 802 | # <dl> |
| 803 | # <dt>standard</dt> |
| 804 | # <dd> |
| 805 | # A basic machine configuration suitable for training simple models with |
| 806 | # small to moderate datasets. |
| 807 | # </dd> |
| 808 | # <dt>large_model</dt> |
| 809 | # <dd> |
| 810 | # A machine with a lot of memory, specially suited for parameter servers |
| 811 | # when your model is large (having many hidden layers or layers with very |
| 812 | # large numbers of nodes). |
| 813 | # </dd> |
| 814 | # <dt>complex_model_s</dt> |
| 815 | # <dd> |
| 816 | # A machine suitable for the master and workers of the cluster when your |
| 817 | # model requires more computation than the standard machine can handle |
| 818 | # satisfactorily. |
| 819 | # </dd> |
| 820 | # <dt>complex_model_m</dt> |
| 821 | # <dd> |
| 822 | # A machine with roughly twice the number of cores and roughly double the |
| 823 | # memory of <code suppresswarning="true">complex_model_s</code>. |
| 824 | # </dd> |
| 825 | # <dt>complex_model_l</dt> |
| 826 | # <dd> |
| 827 | # A machine with roughly twice the number of cores and roughly double the |
| 828 | # memory of <code suppresswarning="true">complex_model_m</code>. |
| 829 | # </dd> |
| 830 | # </dl> |
| 831 | # |
| 832 | # You must set this value when `scaleTier` is set to `CUSTOM`. |
| 833 | "hyperparameters": { # Represents a set of hyperparameters to optimize. # Optional. The set of Hyperparameters to tune. |
| 834 | "maxTrials": 42, # Optional. How many training trials should be attempted to optimize |
| 835 | # the specified hyperparameters. |
| 836 | # |
| 837 | # Defaults to one. |
| 838 | "params": [ # Required. The set of parameters to tune. |
| 839 | { # Represents a single hyperparameter to optimize. |
| 840 | "maxValue": 3.14, # Required if typeis `DOUBLE` or `INTEGER`. This field |
| 841 | # should be unset if type is `CATEGORICAL`. This value should be integers if |
| 842 | # type is `INTEGER`. |
| 843 | "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field |
| 844 | # should be unset if type is `CATEGORICAL`. This value should be integers if |
| 845 | # type is INTEGER. |
| 846 | "discreteValues": [ # Required if type is `DISCRETE`. |
| 847 | # A list of feasible points. |
| 848 | # The list should be in strictly increasing order. For instance, this |
| 849 | # parameter might have possible settings of 1.5, 2.5, and 4.0. This list |
| 850 | # should not contain more than 1,000 values. |
| 851 | 3.14, |
| 852 | ], |
| 853 | "parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in |
| 854 | # a HyperparameterSpec message. E.g., "learning_rate". |
| 855 | "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories. |
| 856 | "A String", |
| 857 | ], |
| 858 | "type": "A String", # Required. The type of the parameter. |
| 859 | "scaleType": "A String", # Optional. How the parameter should be scaled to the hypercube. |
| 860 | # Leave unset for categorical parameters. |
| 861 | # Some kind of scaling is strongly recommended for real or integral |
| 862 | # parameters (e.g., `UNIT_LINEAR_SCALE`). |
| 863 | }, |
| 864 | ], |
| 865 | "maxParallelTrials": 42, # Optional. The number of training trials to run concurrently. |
| 866 | # You can reduce the time it takes to perform hyperparameter tuning by adding |
| 867 | # trials in parallel. However, each trail only benefits from the information |
| 868 | # gained in completed trials. That means that a trial does not get access to |
| 869 | # the results of trials running at the same time, which could reduce the |
| 870 | # quality of the overall optimization. |
| 871 | # |
| 872 | # Each trial will use the same scale tier and machine types. |
| 873 | # |
| 874 | # Defaults to one. |
| 875 | "goal": "A String", # Required. The type of goal to use for tuning. Available types are |
| 876 | # `MAXIMIZE` and `MINIMIZE`. |
| 877 | # |
| 878 | # Defaults to `MAXIMIZE`. |
| 879 | }, |
| 880 | "region": "A String", # Required. The Google Compute Engine region to run the training job in. |
| 881 | "args": [ # Optional. Command line arguments to pass to the program. |
| 882 | "A String", |
| 883 | ], |
| 884 | "pythonModule": "A String", # Required. The Python module name to run after installing the packages. |
| 885 | "packageUris": [ # Required. The Google Cloud Storage location of the packages with |
| 886 | # the training program and any additional dependencies. |
| 887 | "A String", |
| 888 | ], |
| 889 | "workerCount": "A String", # Optional. The number of worker replicas to use for the training job. Each |
| 890 | # replica in the cluster will be of the type specified in `worker_type`. |
| 891 | # |
| 892 | # This value can only be used when `scale_tier` is set to `CUSTOM`. If you |
| 893 | # set this value, you must also set `worker_type`. |
| 894 | "parameterServerType": "A String", # Optional. Specifies the type of virtual machine to use for your training |
| 895 | # job's parameter server. |
| 896 | # |
| 897 | # The supported values are the same as those described in the entry for |
| 898 | # `master_type`. |
| 899 | # |
| 900 | # This value must be present when `scaleTier` is set to `CUSTOM` and |
| 901 | # `parameter_server_count` is greater than zero. |
| 902 | "parameterServerCount": "A String", # Optional. The number of parameter server replicas to use for the training |
| 903 | # job. Each replica in the cluster will be of the type specified in |
| 904 | # `parameter_server_type`. |
| 905 | # |
| 906 | # This value can only be used when `scale_tier` is set to `CUSTOM`.If you |
| 907 | # set this value, you must also set `parameter_server_type`. |
| 908 | }, |
| 909 | "endTime": "A String", # Output only. When the job processing was completed. |
| 910 | "predictionOutput": { # Represents results of a prediction job. # The current prediction job result. |
| 911 | "outputPath": "A String", # The output Google Cloud Storage location provided at the job creation time. |
| 912 | "predictionCount": "A String", # The number of generated predictions. |
| 913 | "errorCount": "A String", # The number of data instances which resulted in errors. |
| 914 | }, |
| 915 | "createTime": "A String", # Output only. When the job was created. |
| 916 | }, |
| 917 | ], |
| 918 | }</pre> |
| 919 | </div> |
| 920 | |
| 921 | <div class="method"> |
| 922 | <code class="details" id="list_next">list_next(previous_request, previous_response)</code> |
| 923 | <pre>Retrieves the next page of results. |
| 924 | |
| 925 | Args: |
| 926 | previous_request: The request for the previous page. (required) |
| 927 | previous_response: The response from the request for the previous page. (required) |
| 928 | |
| 929 | Returns: |
| 930 | A request object that you can call 'execute()' on to request the next |
| 931 | page. Returns None if there are no more items in the collection. |
| 932 | </pre> |
| 933 | </div> |
| 934 | |
| 935 | </body></html> |