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gerrit-public.fairphone.software / platform / external / python / google-api-python-client / 2f245374da9c895dbd8bb0423e98707d51b53414 / . / docs / dyn / ml_v1beta1.projects.jobs.html
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Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]1<html><body>
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Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]75<h1><a href="ml_v1beta1.html">Google Cloud Machine Learning Engine</a> . <a href="ml_v1beta1.projects.html">projects</a> . <a href="ml_v1beta1.projects.jobs.html">jobs</a></h1>
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]76<h2>Instance Methods</h2>
77<p class="toc_element">
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]78 <code><a href="#cancel">cancel(name, body, x__xgafv=None)</a></code></p>
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]79<p class="firstline">Cancels a running job.</p>
80<p class="toc_element">
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]81 <code><a href="#create">create(parent, body, x__xgafv=None)</a></code></p>
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]82<p class="firstline">Creates a training or a batch prediction job.</p>
83<p class="toc_element">
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]84 <code><a href="#get">get(name, x__xgafv=None)</a></code></p>
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]85<p class="firstline">Describes a job.</p>
86<p class="toc_element">
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]87 <code><a href="#list">list(parent, pageSize=None, filter=None, pageToken=None, x__xgafv=None)</a></code></p>
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]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">
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]94 <code class="details" id="cancel">cancel(name, body, x__xgafv=None)</code>
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]95 <pre>Cancels a running job.
96
97Args:
98 name: string, Required. The name of the job to cancel.
99
100Authorization: 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
112Returns:
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">
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]128 <code class="details" id="create">create(parent, body, x__xgafv=None)</code>
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]129 <pre>Creates a training or a batch prediction job.
130
131Args:
132 parent: string, Required. The project name.
133
134Authorization: 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.
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]139 "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]140 "trainingOutput": { # Represents results of a training job. Output only. # The current training job result.
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]141 "completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
142 # Only set for hyperparameter tuning jobs.
143 "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]144 "trials": [ # Results for individual Hyperparameter trials.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]145 # Only set for hyperparameter tuning jobs.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]146 { # Represents the result of a single hyperparameter tuning trial from a
147 # training job. The TrainingOutput object that is returned on successful
148 # completion of a training job with hyperparameter tuning includes a list
149 # of HyperparameterOutput objects, one for each successful trial.
150 "hyperparameters": { # The hyperparameters given to this trial.
151 "a_key": "A String",
152 },
153 "trialId": "A String", # The trial id for these results.
154 "allMetrics": [ # All recorded object metrics for this trial.
155 { # An observed value of a metric.
156 "trainingStep": "A String", # The global training step for this metric.
157 "objectiveValue": 3.14, # The objective value at this training step.
158 },
159 ],
160 "finalMetric": { # An observed value of a metric. # The final objective metric seen for this trial.
161 "trainingStep": "A String", # The global training step for this metric.
162 "objectiveValue": 3.14, # The objective value at this training step.
163 },
164 },
165 ],
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]166 "consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]167 },
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]168 "startTime": "A String", # Output only. When the job processing was started.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]169 "trainingInput": { # Represents input parameters for a training job. # Input parameters to create a training job.
170 "workerType": "A String", # Optional. Specifies the type of virtual machine to use for your training
171 # job's worker nodes.
172 #
173 # The supported values are the same as those described in the entry for
174 # `masterType`.
175 #
176 # This value must be present when `scaleTier` is set to `CUSTOM` and
177 # `workerCount` is greater than zero.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]178 "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for training. If not
179 # set, Google Cloud ML will choose the latest stable version.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]180 "scaleTier": "A String", # Required. Specifies the machine types, the number of replicas for workers
181 # and parameter servers.
182 "masterType": "A String", # Optional. Specifies the type of virtual machine to use for your training
183 # job's master worker.
184 #
185 # The following types are supported:
186 #
187 # <dl>
188 # <dt>standard</dt>
189 # <dd>
190 # A basic machine configuration suitable for training simple models with
191 # small to moderate datasets.
192 # </dd>
193 # <dt>large_model</dt>
194 # <dd>
195 # A machine with a lot of memory, specially suited for parameter servers
196 # when your model is large (having many hidden layers or layers with very
197 # large numbers of nodes).
198 # </dd>
199 # <dt>complex_model_s</dt>
200 # <dd>
201 # A machine suitable for the master and workers of the cluster when your
202 # model requires more computation than the standard machine can handle
203 # satisfactorily.
204 # </dd>
205 # <dt>complex_model_m</dt>
206 # <dd>
207 # A machine with roughly twice the number of cores and roughly double the
208 # memory of <code suppresswarning="true">complex_model_s</code>.
209 # </dd>
210 # <dt>complex_model_l</dt>
211 # <dd>
212 # A machine with roughly twice the number of cores and roughly double the
213 # memory of <code suppresswarning="true">complex_model_m</code>.
214 # </dd>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]215 # <dt>standard_gpu</dt>
216 # <dd>
217 # A machine equivalent to <code suppresswarning="true">standard</code> that
218 # also includes a
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]219 # <a href="/ml-engine/docs/how-tos/using-gpus">
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]220 # GPU that you can use in your trainer</a>.
221 # </dd>
222 # <dt>complex_model_m_gpu</dt>
223 # <dd>
224 # A machine equivalent to
225 # <code suppresswarning="true">coplex_model_m</code> that also includes
226 # four GPUs.
227 # </dd>
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]228 # </dl>
229 #
230 # You must set this value when `scaleTier` is set to `CUSTOM`.
231 "hyperparameters": { # Represents a set of hyperparameters to optimize. # Optional. The set of Hyperparameters to tune.
232 "maxTrials": 42, # Optional. How many training trials should be attempted to optimize
233 # the specified hyperparameters.
234 #
235 # Defaults to one.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]236 "hyperparameterMetricTag": "A String", # Optional. The Tensorflow summary tag name to use for optimizing trials. For
237 # current versions of Tensorflow, this tag name should exactly match what is
238 # shown in Tensorboard, including all scopes. For versions of Tensorflow
239 # prior to 0.12, this should be only the tag passed to tf.Summary.
240 # By default, "training/hptuning/metric" will be used.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]241 "params": [ # Required. The set of parameters to tune.
242 { # Represents a single hyperparameter to optimize.
243 "maxValue": 3.14, # Required if typeis `DOUBLE` or `INTEGER`. This field
244 # should be unset if type is `CATEGORICAL`. This value should be integers if
245 # type is `INTEGER`.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]246 "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field
247 # should be unset if type is `CATEGORICAL`. This value should be integers if
248 # type is INTEGER.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]249 "discreteValues": [ # Required if type is `DISCRETE`.
250 # A list of feasible points.
251 # The list should be in strictly increasing order. For instance, this
252 # parameter might have possible settings of 1.5, 2.5, and 4.0. This list
253 # should not contain more than 1,000 values.
254 3.14,
255 ],
256 "parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in
257 # a HyperparameterSpec message. E.g., "learning_rate".
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]258 "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories.
259 "A String",
260 ],
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]261 "type": "A String", # Required. The type of the parameter.
262 "scaleType": "A String", # Optional. How the parameter should be scaled to the hypercube.
263 # Leave unset for categorical parameters.
264 # Some kind of scaling is strongly recommended for real or integral
265 # parameters (e.g., `UNIT_LINEAR_SCALE`).
266 },
267 ],
268 "maxParallelTrials": 42, # Optional. The number of training trials to run concurrently.
269 # You can reduce the time it takes to perform hyperparameter tuning by adding
270 # trials in parallel. However, each trail only benefits from the information
271 # gained in completed trials. That means that a trial does not get access to
272 # the results of trials running at the same time, which could reduce the
273 # quality of the overall optimization.
274 #
275 # Each trial will use the same scale tier and machine types.
276 #
277 # Defaults to one.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]278 "goal": "A String", # Required. The type of goal to use for tuning. Available types are
279 # `MAXIMIZE` and `MINIMIZE`.
280 #
281 # Defaults to `MAXIMIZE`.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]282 },
283 "region": "A String", # Required. The Google Compute Engine region to run the training job in.
284 "args": [ # Optional. Command line arguments to pass to the program.
285 "A String",
286 ],
287 "pythonModule": "A String", # Required. The Python module name to run after installing the packages.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]288 "jobDir": "A String", # Optional. A Google Cloud Storage path in which to store training outputs
289 # and other data needed for training. This path is passed to your TensorFlow
290 # program as the 'job_dir' command-line argument. The benefit of specifying
291 # this field is that Cloud ML validates the path for use in training.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]292 "packageUris": [ # Required. The Google Cloud Storage location of the packages with
293 # the training program and any additional dependencies.
294 "A String",
295 ],
296 "workerCount": "A String", # Optional. The number of worker replicas to use for the training job. Each
297 # replica in the cluster will be of the type specified in `worker_type`.
298 #
299 # This value can only be used when `scale_tier` is set to `CUSTOM`. If you
300 # set this value, you must also set `worker_type`.
301 "parameterServerType": "A String", # Optional. Specifies the type of virtual machine to use for your training
302 # job's parameter server.
303 #
304 # The supported values are the same as those described in the entry for
305 # `master_type`.
306 #
307 # This value must be present when `scaleTier` is set to `CUSTOM` and
308 # `parameter_server_count` is greater than zero.
309 "parameterServerCount": "A String", # Optional. The number of parameter server replicas to use for the training
310 # job. Each replica in the cluster will be of the type specified in
311 # `parameter_server_type`.
312 #
313 # This value can only be used when `scale_tier` is set to `CUSTOM`.If you
314 # set this value, you must also set `parameter_server_type`.
315 },
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]316 "jobId": "A String", # Required. The user-specified id of the job.
317 "state": "A String", # Output only. The detailed state of a job.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]318 "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
319 "modelName": "A String", # Use this field if you want to use the default version for the specified
320 # model. The string must use the following format:
321 #
322 # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
323 "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this batch
324 # prediction. If not set, Google Cloud ML will pick the runtime version used
325 # during the CreateVersion request for this model version, or choose the
326 # latest stable version when model version information is not available
327 # such as when the model is specified by uri.
328 "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
329 # May contain wildcards.
330 "A String",
331 ],
332 "maxWorkerCount": "A String", # Optional. The maximum number of workers to be used for parallel processing.
333 # Defaults to 10 if not specified.
334 "uri": "A String", # Use this field if you want to specify a Google Cloud Storage path for
335 # the model to use.
336 "outputPath": "A String", # Required. The output Google Cloud Storage location.
337 "dataFormat": "A String", # Required. The format of the input data files.
338 "versionName": "A String", # Use this field if you want to specify a version of the model to use. The
339 # string is formatted the same way as `model_version`, with the addition
340 # of the version information:
341 #
342 # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"`
343 "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
344 },
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]345 "endTime": "A String", # Output only. When the job processing was completed.
346 "predictionOutput": { # Represents results of a prediction job. # The current prediction job result.
347 "outputPath": "A String", # The output Google Cloud Storage location provided at the job creation time.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]348 "nodeHours": 3.14, # Node hours used by the batch prediction job.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]349 "predictionCount": "A String", # The number of generated predictions.
350 "errorCount": "A String", # The number of data instances which resulted in errors.
351 },
352 "createTime": "A String", # Output only. When the job was created.
353 }
354
355 x__xgafv: string, V1 error format.
356 Allowed values
357 1 - v1 error format
358 2 - v2 error format
359
360Returns:
361 An object of the form:
362
363 { # Represents a training or prediction job.
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]364 "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]365 "trainingOutput": { # Represents results of a training job. Output only. # The current training job result.
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]366 "completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
367 # Only set for hyperparameter tuning jobs.
368 "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]369 "trials": [ # Results for individual Hyperparameter trials.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]370 # Only set for hyperparameter tuning jobs.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]371 { # Represents the result of a single hyperparameter tuning trial from a
372 # training job. The TrainingOutput object that is returned on successful
373 # completion of a training job with hyperparameter tuning includes a list
374 # of HyperparameterOutput objects, one for each successful trial.
375 "hyperparameters": { # The hyperparameters given to this trial.
376 "a_key": "A String",
377 },
378 "trialId": "A String", # The trial id for these results.
379 "allMetrics": [ # All recorded object metrics for this trial.
380 { # An observed value of a metric.
381 "trainingStep": "A String", # The global training step for this metric.
382 "objectiveValue": 3.14, # The objective value at this training step.
383 },
384 ],
385 "finalMetric": { # An observed value of a metric. # The final objective metric seen for this trial.
386 "trainingStep": "A String", # The global training step for this metric.
387 "objectiveValue": 3.14, # The objective value at this training step.
388 },
389 },
390 ],
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]391 "consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]392 },
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]393 "startTime": "A String", # Output only. When the job processing was started.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]394 "trainingInput": { # Represents input parameters for a training job. # Input parameters to create a training job.
395 "workerType": "A String", # Optional. Specifies the type of virtual machine to use for your training
396 # job's worker nodes.
397 #
398 # The supported values are the same as those described in the entry for
399 # `masterType`.
400 #
401 # This value must be present when `scaleTier` is set to `CUSTOM` and
402 # `workerCount` is greater than zero.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]403 "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for training. If not
404 # set, Google Cloud ML will choose the latest stable version.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]405 "scaleTier": "A String", # Required. Specifies the machine types, the number of replicas for workers
406 # and parameter servers.
407 "masterType": "A String", # Optional. Specifies the type of virtual machine to use for your training
408 # job's master worker.
409 #
410 # The following types are supported:
411 #
412 # <dl>
413 # <dt>standard</dt>
414 # <dd>
415 # A basic machine configuration suitable for training simple models with
416 # small to moderate datasets.
417 # </dd>
418 # <dt>large_model</dt>
419 # <dd>
420 # A machine with a lot of memory, specially suited for parameter servers
421 # when your model is large (having many hidden layers or layers with very
422 # large numbers of nodes).
423 # </dd>
424 # <dt>complex_model_s</dt>
425 # <dd>
426 # A machine suitable for the master and workers of the cluster when your
427 # model requires more computation than the standard machine can handle
428 # satisfactorily.
429 # </dd>
430 # <dt>complex_model_m</dt>
431 # <dd>
432 # A machine with roughly twice the number of cores and roughly double the
433 # memory of <code suppresswarning="true">complex_model_s</code>.
434 # </dd>
435 # <dt>complex_model_l</dt>
436 # <dd>
437 # A machine with roughly twice the number of cores and roughly double the
438 # memory of <code suppresswarning="true">complex_model_m</code>.
439 # </dd>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]440 # <dt>standard_gpu</dt>
441 # <dd>
442 # A machine equivalent to <code suppresswarning="true">standard</code> that
443 # also includes a
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]444 # <a href="/ml-engine/docs/how-tos/using-gpus">
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]445 # GPU that you can use in your trainer</a>.
446 # </dd>
447 # <dt>complex_model_m_gpu</dt>
448 # <dd>
449 # A machine equivalent to
450 # <code suppresswarning="true">coplex_model_m</code> that also includes
451 # four GPUs.
452 # </dd>
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]453 # </dl>
454 #
455 # You must set this value when `scaleTier` is set to `CUSTOM`.
456 "hyperparameters": { # Represents a set of hyperparameters to optimize. # Optional. The set of Hyperparameters to tune.
457 "maxTrials": 42, # Optional. How many training trials should be attempted to optimize
458 # the specified hyperparameters.
459 #
460 # Defaults to one.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]461 "hyperparameterMetricTag": "A String", # Optional. The Tensorflow summary tag name to use for optimizing trials. For
462 # current versions of Tensorflow, this tag name should exactly match what is
463 # shown in Tensorboard, including all scopes. For versions of Tensorflow
464 # prior to 0.12, this should be only the tag passed to tf.Summary.
465 # By default, "training/hptuning/metric" will be used.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]466 "params": [ # Required. The set of parameters to tune.
467 { # Represents a single hyperparameter to optimize.
468 "maxValue": 3.14, # Required if typeis `DOUBLE` or `INTEGER`. This field
469 # should be unset if type is `CATEGORICAL`. This value should be integers if
470 # type is `INTEGER`.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]471 "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field
472 # should be unset if type is `CATEGORICAL`. This value should be integers if
473 # type is INTEGER.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]474 "discreteValues": [ # Required if type is `DISCRETE`.
475 # A list of feasible points.
476 # The list should be in strictly increasing order. For instance, this
477 # parameter might have possible settings of 1.5, 2.5, and 4.0. This list
478 # should not contain more than 1,000 values.
479 3.14,
480 ],
481 "parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in
482 # a HyperparameterSpec message. E.g., "learning_rate".
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]483 "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories.
484 "A String",
485 ],
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]486 "type": "A String", # Required. The type of the parameter.
487 "scaleType": "A String", # Optional. How the parameter should be scaled to the hypercube.
488 # Leave unset for categorical parameters.
489 # Some kind of scaling is strongly recommended for real or integral
490 # parameters (e.g., `UNIT_LINEAR_SCALE`).
491 },
492 ],
493 "maxParallelTrials": 42, # Optional. The number of training trials to run concurrently.
494 # You can reduce the time it takes to perform hyperparameter tuning by adding
495 # trials in parallel. However, each trail only benefits from the information
496 # gained in completed trials. That means that a trial does not get access to
497 # the results of trials running at the same time, which could reduce the
498 # quality of the overall optimization.
499 #
500 # Each trial will use the same scale tier and machine types.
501 #
502 # Defaults to one.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]503 "goal": "A String", # Required. The type of goal to use for tuning. Available types are
504 # `MAXIMIZE` and `MINIMIZE`.
505 #
506 # Defaults to `MAXIMIZE`.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]507 },
508 "region": "A String", # Required. The Google Compute Engine region to run the training job in.
509 "args": [ # Optional. Command line arguments to pass to the program.
510 "A String",
511 ],
512 "pythonModule": "A String", # Required. The Python module name to run after installing the packages.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]513 "jobDir": "A String", # Optional. A Google Cloud Storage path in which to store training outputs
514 # and other data needed for training. This path is passed to your TensorFlow
515 # program as the 'job_dir' command-line argument. The benefit of specifying
516 # this field is that Cloud ML validates the path for use in training.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]517 "packageUris": [ # Required. The Google Cloud Storage location of the packages with
518 # the training program and any additional dependencies.
519 "A String",
520 ],
521 "workerCount": "A String", # Optional. The number of worker replicas to use for the training job. Each
522 # replica in the cluster will be of the type specified in `worker_type`.
523 #
524 # This value can only be used when `scale_tier` is set to `CUSTOM`. If you
525 # set this value, you must also set `worker_type`.
526 "parameterServerType": "A String", # Optional. Specifies the type of virtual machine to use for your training
527 # job's parameter server.
528 #
529 # The supported values are the same as those described in the entry for
530 # `master_type`.
531 #
532 # This value must be present when `scaleTier` is set to `CUSTOM` and
533 # `parameter_server_count` is greater than zero.
534 "parameterServerCount": "A String", # Optional. The number of parameter server replicas to use for the training
535 # job. Each replica in the cluster will be of the type specified in
536 # `parameter_server_type`.
537 #
538 # This value can only be used when `scale_tier` is set to `CUSTOM`.If you
539 # set this value, you must also set `parameter_server_type`.
540 },
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]541 "jobId": "A String", # Required. The user-specified id of the job.
542 "state": "A String", # Output only. The detailed state of a job.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]543 "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
544 "modelName": "A String", # Use this field if you want to use the default version for the specified
545 # model. The string must use the following format:
546 #
547 # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
548 "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this batch
549 # prediction. If not set, Google Cloud ML will pick the runtime version used
550 # during the CreateVersion request for this model version, or choose the
551 # latest stable version when model version information is not available
552 # such as when the model is specified by uri.
553 "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
554 # May contain wildcards.
555 "A String",
556 ],
557 "maxWorkerCount": "A String", # Optional. The maximum number of workers to be used for parallel processing.
558 # Defaults to 10 if not specified.
559 "uri": "A String", # Use this field if you want to specify a Google Cloud Storage path for
560 # the model to use.
561 "outputPath": "A String", # Required. The output Google Cloud Storage location.
562 "dataFormat": "A String", # Required. The format of the input data files.
563 "versionName": "A String", # Use this field if you want to specify a version of the model to use. The
564 # string is formatted the same way as `model_version`, with the addition
565 # of the version information:
566 #
567 # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"`
568 "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
569 },
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]570 "endTime": "A String", # Output only. When the job processing was completed.
571 "predictionOutput": { # Represents results of a prediction job. # The current prediction job result.
572 "outputPath": "A String", # The output Google Cloud Storage location provided at the job creation time.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]573 "nodeHours": 3.14, # Node hours used by the batch prediction job.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]574 "predictionCount": "A String", # The number of generated predictions.
575 "errorCount": "A String", # The number of data instances which resulted in errors.
576 },
577 "createTime": "A String", # Output only. When the job was created.
578 }</pre>
579</div>
580
581<div class="method">
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]582 <code class="details" id="get">get(name, x__xgafv=None)</code>
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]583 <pre>Describes a job.
584
585Args:
586 name: string, Required. The name of the job to get the description of.
587
588Authorization: requires `Viewer` role on the parent project. (required)
589 x__xgafv: string, V1 error format.
590 Allowed values
591 1 - v1 error format
592 2 - v2 error format
593
594Returns:
595 An object of the form:
596
597 { # Represents a training or prediction job.
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]598 "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]599 "trainingOutput": { # Represents results of a training job. Output only. # The current training job result.
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]600 "completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
601 # Only set for hyperparameter tuning jobs.
602 "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]603 "trials": [ # Results for individual Hyperparameter trials.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]604 # Only set for hyperparameter tuning jobs.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]605 { # Represents the result of a single hyperparameter tuning trial from a
606 # training job. The TrainingOutput object that is returned on successful
607 # completion of a training job with hyperparameter tuning includes a list
608 # of HyperparameterOutput objects, one for each successful trial.
609 "hyperparameters": { # The hyperparameters given to this trial.
610 "a_key": "A String",
611 },
612 "trialId": "A String", # The trial id for these results.
613 "allMetrics": [ # All recorded object metrics for this trial.
614 { # An observed value of a metric.
615 "trainingStep": "A String", # The global training step for this metric.
616 "objectiveValue": 3.14, # The objective value at this training step.
617 },
618 ],
619 "finalMetric": { # An observed value of a metric. # The final objective metric seen for this trial.
620 "trainingStep": "A String", # The global training step for this metric.
621 "objectiveValue": 3.14, # The objective value at this training step.
622 },
623 },
624 ],
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]625 "consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]626 },
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]627 "startTime": "A String", # Output only. When the job processing was started.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]628 "trainingInput": { # Represents input parameters for a training job. # Input parameters to create a training job.
629 "workerType": "A String", # Optional. Specifies the type of virtual machine to use for your training
630 # job's worker nodes.
631 #
632 # The supported values are the same as those described in the entry for
633 # `masterType`.
634 #
635 # This value must be present when `scaleTier` is set to `CUSTOM` and
636 # `workerCount` is greater than zero.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]637 "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for training. If not
638 # set, Google Cloud ML will choose the latest stable version.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]639 "scaleTier": "A String", # Required. Specifies the machine types, the number of replicas for workers
640 # and parameter servers.
641 "masterType": "A String", # Optional. Specifies the type of virtual machine to use for your training
642 # job's master worker.
643 #
644 # The following types are supported:
645 #
646 # <dl>
647 # <dt>standard</dt>
648 # <dd>
649 # A basic machine configuration suitable for training simple models with
650 # small to moderate datasets.
651 # </dd>
652 # <dt>large_model</dt>
653 # <dd>
654 # A machine with a lot of memory, specially suited for parameter servers
655 # when your model is large (having many hidden layers or layers with very
656 # large numbers of nodes).
657 # </dd>
658 # <dt>complex_model_s</dt>
659 # <dd>
660 # A machine suitable for the master and workers of the cluster when your
661 # model requires more computation than the standard machine can handle
662 # satisfactorily.
663 # </dd>
664 # <dt>complex_model_m</dt>
665 # <dd>
666 # A machine with roughly twice the number of cores and roughly double the
667 # memory of <code suppresswarning="true">complex_model_s</code>.
668 # </dd>
669 # <dt>complex_model_l</dt>
670 # <dd>
671 # A machine with roughly twice the number of cores and roughly double the
672 # memory of <code suppresswarning="true">complex_model_m</code>.
673 # </dd>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]674 # <dt>standard_gpu</dt>
675 # <dd>
676 # A machine equivalent to <code suppresswarning="true">standard</code> that
677 # also includes a
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]678 # <a href="/ml-engine/docs/how-tos/using-gpus">
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]679 # GPU that you can use in your trainer</a>.
680 # </dd>
681 # <dt>complex_model_m_gpu</dt>
682 # <dd>
683 # A machine equivalent to
684 # <code suppresswarning="true">coplex_model_m</code> that also includes
685 # four GPUs.
686 # </dd>
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]687 # </dl>
688 #
689 # You must set this value when `scaleTier` is set to `CUSTOM`.
690 "hyperparameters": { # Represents a set of hyperparameters to optimize. # Optional. The set of Hyperparameters to tune.
691 "maxTrials": 42, # Optional. How many training trials should be attempted to optimize
692 # the specified hyperparameters.
693 #
694 # Defaults to one.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]695 "hyperparameterMetricTag": "A String", # Optional. The Tensorflow summary tag name to use for optimizing trials. For
696 # current versions of Tensorflow, this tag name should exactly match what is
697 # shown in Tensorboard, including all scopes. For versions of Tensorflow
698 # prior to 0.12, this should be only the tag passed to tf.Summary.
699 # By default, "training/hptuning/metric" will be used.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]700 "params": [ # Required. The set of parameters to tune.
701 { # Represents a single hyperparameter to optimize.
702 "maxValue": 3.14, # Required if typeis `DOUBLE` or `INTEGER`. This field
703 # should be unset if type is `CATEGORICAL`. This value should be integers if
704 # type is `INTEGER`.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]705 "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field
706 # should be unset if type is `CATEGORICAL`. This value should be integers if
707 # type is INTEGER.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]708 "discreteValues": [ # Required if type is `DISCRETE`.
709 # A list of feasible points.
710 # The list should be in strictly increasing order. For instance, this
711 # parameter might have possible settings of 1.5, 2.5, and 4.0. This list
712 # should not contain more than 1,000 values.
713 3.14,
714 ],
715 "parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in
716 # a HyperparameterSpec message. E.g., "learning_rate".
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]717 "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories.
718 "A String",
719 ],
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]720 "type": "A String", # Required. The type of the parameter.
721 "scaleType": "A String", # Optional. How the parameter should be scaled to the hypercube.
722 # Leave unset for categorical parameters.
723 # Some kind of scaling is strongly recommended for real or integral
724 # parameters (e.g., `UNIT_LINEAR_SCALE`).
725 },
726 ],
727 "maxParallelTrials": 42, # Optional. The number of training trials to run concurrently.
728 # You can reduce the time it takes to perform hyperparameter tuning by adding
729 # trials in parallel. However, each trail only benefits from the information
730 # gained in completed trials. That means that a trial does not get access to
731 # the results of trials running at the same time, which could reduce the
732 # quality of the overall optimization.
733 #
734 # Each trial will use the same scale tier and machine types.
735 #
736 # Defaults to one.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]737 "goal": "A String", # Required. The type of goal to use for tuning. Available types are
738 # `MAXIMIZE` and `MINIMIZE`.
739 #
740 # Defaults to `MAXIMIZE`.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]741 },
742 "region": "A String", # Required. The Google Compute Engine region to run the training job in.
743 "args": [ # Optional. Command line arguments to pass to the program.
744 "A String",
745 ],
746 "pythonModule": "A String", # Required. The Python module name to run after installing the packages.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]747 "jobDir": "A String", # Optional. A Google Cloud Storage path in which to store training outputs
748 # and other data needed for training. This path is passed to your TensorFlow
749 # program as the 'job_dir' command-line argument. The benefit of specifying
750 # this field is that Cloud ML validates the path for use in training.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]751 "packageUris": [ # Required. The Google Cloud Storage location of the packages with
752 # the training program and any additional dependencies.
753 "A String",
754 ],
755 "workerCount": "A String", # Optional. The number of worker replicas to use for the training job. Each
756 # replica in the cluster will be of the type specified in `worker_type`.
757 #
758 # This value can only be used when `scale_tier` is set to `CUSTOM`. If you
759 # set this value, you must also set `worker_type`.
760 "parameterServerType": "A String", # Optional. Specifies the type of virtual machine to use for your training
761 # job's parameter server.
762 #
763 # The supported values are the same as those described in the entry for
764 # `master_type`.
765 #
766 # This value must be present when `scaleTier` is set to `CUSTOM` and
767 # `parameter_server_count` is greater than zero.
768 "parameterServerCount": "A String", # Optional. The number of parameter server replicas to use for the training
769 # job. Each replica in the cluster will be of the type specified in
770 # `parameter_server_type`.
771 #
772 # This value can only be used when `scale_tier` is set to `CUSTOM`.If you
773 # set this value, you must also set `parameter_server_type`.
774 },
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]775 "jobId": "A String", # Required. The user-specified id of the job.
776 "state": "A String", # Output only. The detailed state of a job.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]777 "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
778 "modelName": "A String", # Use this field if you want to use the default version for the specified
779 # model. The string must use the following format:
780 #
781 # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
782 "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this batch
783 # prediction. If not set, Google Cloud ML will pick the runtime version used
784 # during the CreateVersion request for this model version, or choose the
785 # latest stable version when model version information is not available
786 # such as when the model is specified by uri.
787 "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
788 # May contain wildcards.
789 "A String",
790 ],
791 "maxWorkerCount": "A String", # Optional. The maximum number of workers to be used for parallel processing.
792 # Defaults to 10 if not specified.
793 "uri": "A String", # Use this field if you want to specify a Google Cloud Storage path for
794 # the model to use.
795 "outputPath": "A String", # Required. The output Google Cloud Storage location.
796 "dataFormat": "A String", # Required. The format of the input data files.
797 "versionName": "A String", # Use this field if you want to specify a version of the model to use. The
798 # string is formatted the same way as `model_version`, with the addition
799 # of the version information:
800 #
801 # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"`
802 "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
803 },
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]804 "endTime": "A String", # Output only. When the job processing was completed.
805 "predictionOutput": { # Represents results of a prediction job. # The current prediction job result.
806 "outputPath": "A String", # The output Google Cloud Storage location provided at the job creation time.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]807 "nodeHours": 3.14, # Node hours used by the batch prediction job.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]808 "predictionCount": "A String", # The number of generated predictions.
809 "errorCount": "A String", # The number of data instances which resulted in errors.
810 },
811 "createTime": "A String", # Output only. When the job was created.
812 }</pre>
813</div>
814
815<div class="method">
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]816 <code class="details" id="list">list(parent, pageSize=None, filter=None, pageToken=None, x__xgafv=None)</code>
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]817 <pre>Lists the jobs in the project.
818
819Args:
820 parent: string, Required. The name of the project for which to list jobs.
821
822Authorization: requires `Viewer` role on the specified project. (required)
823 pageSize: integer, Optional. The number of jobs to retrieve per "page" of results. If there
824are more remaining results than this number, the response message will
825contain a valid value in the `next_page_token` field.
826
827The default value is 20, and the maximum page size is 100.
828 filter: string, Optional. Specifies the subset of jobs to retrieve.
829 pageToken: string, Optional. A page token to request the next page of results.
830
831You get the token from the `next_page_token` field of the response from
832the previous call.
833 x__xgafv: string, V1 error format.
834 Allowed values
835 1 - v1 error format
836 2 - v2 error format
837
838Returns:
839 An object of the form:
840
841 { # Response message for the ListJobs method.
842 "nextPageToken": "A String", # Optional. Pass this token as the `page_token` field of the request for a
843 # subsequent call.
844 "jobs": [ # The list of jobs.
845 { # Represents a training or prediction job.
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]846 "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]847 "trainingOutput": { # Represents results of a training job. Output only. # The current training job result.
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]848 "completedTrialCount": "A String", # The number of hyperparameter tuning trials that completed successfully.
849 # Only set for hyperparameter tuning jobs.
850 "isHyperparameterTuningJob": True or False, # Whether this job is a hyperparameter tuning job.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]851 "trials": [ # Results for individual Hyperparameter trials.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]852 # Only set for hyperparameter tuning jobs.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]853 { # Represents the result of a single hyperparameter tuning trial from a
854 # training job. The TrainingOutput object that is returned on successful
855 # completion of a training job with hyperparameter tuning includes a list
856 # of HyperparameterOutput objects, one for each successful trial.
857 "hyperparameters": { # The hyperparameters given to this trial.
858 "a_key": "A String",
859 },
860 "trialId": "A String", # The trial id for these results.
861 "allMetrics": [ # All recorded object metrics for this trial.
862 { # An observed value of a metric.
863 "trainingStep": "A String", # The global training step for this metric.
864 "objectiveValue": 3.14, # The objective value at this training step.
865 },
866 ],
867 "finalMetric": { # An observed value of a metric. # The final objective metric seen for this trial.
868 "trainingStep": "A String", # The global training step for this metric.
869 "objectiveValue": 3.14, # The objective value at this training step.
870 },
871 },
872 ],
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]873 "consumedMLUnits": 3.14, # The amount of ML units consumed by the job.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]874 },
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]875 "startTime": "A String", # Output only. When the job processing was started.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]876 "trainingInput": { # Represents input parameters for a training job. # Input parameters to create a training job.
877 "workerType": "A String", # Optional. Specifies the type of virtual machine to use for your training
878 # job's worker nodes.
879 #
880 # The supported values are the same as those described in the entry for
881 # `masterType`.
882 #
883 # This value must be present when `scaleTier` is set to `CUSTOM` and
884 # `workerCount` is greater than zero.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]885 "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for training. If not
886 # set, Google Cloud ML will choose the latest stable version.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]887 "scaleTier": "A String", # Required. Specifies the machine types, the number of replicas for workers
888 # and parameter servers.
889 "masterType": "A String", # Optional. Specifies the type of virtual machine to use for your training
890 # job's master worker.
891 #
892 # The following types are supported:
893 #
894 # <dl>
895 # <dt>standard</dt>
896 # <dd>
897 # A basic machine configuration suitable for training simple models with
898 # small to moderate datasets.
899 # </dd>
900 # <dt>large_model</dt>
901 # <dd>
902 # A machine with a lot of memory, specially suited for parameter servers
903 # when your model is large (having many hidden layers or layers with very
904 # large numbers of nodes).
905 # </dd>
906 # <dt>complex_model_s</dt>
907 # <dd>
908 # A machine suitable for the master and workers of the cluster when your
909 # model requires more computation than the standard machine can handle
910 # satisfactorily.
911 # </dd>
912 # <dt>complex_model_m</dt>
913 # <dd>
914 # A machine with roughly twice the number of cores and roughly double the
915 # memory of <code suppresswarning="true">complex_model_s</code>.
916 # </dd>
917 # <dt>complex_model_l</dt>
918 # <dd>
919 # A machine with roughly twice the number of cores and roughly double the
920 # memory of <code suppresswarning="true">complex_model_m</code>.
921 # </dd>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]922 # <dt>standard_gpu</dt>
923 # <dd>
924 # A machine equivalent to <code suppresswarning="true">standard</code> that
925 # also includes a
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]926 # <a href="/ml-engine/docs/how-tos/using-gpus">
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]927 # GPU that you can use in your trainer</a>.
928 # </dd>
929 # <dt>complex_model_m_gpu</dt>
930 # <dd>
931 # A machine equivalent to
932 # <code suppresswarning="true">coplex_model_m</code> that also includes
933 # four GPUs.
934 # </dd>
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]935 # </dl>
936 #
937 # You must set this value when `scaleTier` is set to `CUSTOM`.
938 "hyperparameters": { # Represents a set of hyperparameters to optimize. # Optional. The set of Hyperparameters to tune.
939 "maxTrials": 42, # Optional. How many training trials should be attempted to optimize
940 # the specified hyperparameters.
941 #
942 # Defaults to one.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]943 "hyperparameterMetricTag": "A String", # Optional. The Tensorflow summary tag name to use for optimizing trials. For
944 # current versions of Tensorflow, this tag name should exactly match what is
945 # shown in Tensorboard, including all scopes. For versions of Tensorflow
946 # prior to 0.12, this should be only the tag passed to tf.Summary.
947 # By default, "training/hptuning/metric" will be used.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]948 "params": [ # Required. The set of parameters to tune.
949 { # Represents a single hyperparameter to optimize.
950 "maxValue": 3.14, # Required if typeis `DOUBLE` or `INTEGER`. This field
951 # should be unset if type is `CATEGORICAL`. This value should be integers if
952 # type is `INTEGER`.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]953 "minValue": 3.14, # Required if type is `DOUBLE` or `INTEGER`. This field
954 # should be unset if type is `CATEGORICAL`. This value should be integers if
955 # type is INTEGER.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]956 "discreteValues": [ # Required if type is `DISCRETE`.
957 # A list of feasible points.
958 # The list should be in strictly increasing order. For instance, this
959 # parameter might have possible settings of 1.5, 2.5, and 4.0. This list
960 # should not contain more than 1,000 values.
961 3.14,
962 ],
963 "parameterName": "A String", # Required. The parameter name must be unique amongst all ParameterConfigs in
964 # a HyperparameterSpec message. E.g., "learning_rate".
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]965 "categoricalValues": [ # Required if type is `CATEGORICAL`. The list of possible categories.
966 "A String",
967 ],
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]968 "type": "A String", # Required. The type of the parameter.
969 "scaleType": "A String", # Optional. How the parameter should be scaled to the hypercube.
970 # Leave unset for categorical parameters.
971 # Some kind of scaling is strongly recommended for real or integral
972 # parameters (e.g., `UNIT_LINEAR_SCALE`).
973 },
974 ],
975 "maxParallelTrials": 42, # Optional. The number of training trials to run concurrently.
976 # You can reduce the time it takes to perform hyperparameter tuning by adding
977 # trials in parallel. However, each trail only benefits from the information
978 # gained in completed trials. That means that a trial does not get access to
979 # the results of trials running at the same time, which could reduce the
980 # quality of the overall optimization.
981 #
982 # Each trial will use the same scale tier and machine types.
983 #
984 # Defaults to one.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]985 "goal": "A String", # Required. The type of goal to use for tuning. Available types are
986 # `MAXIMIZE` and `MINIMIZE`.
987 #
988 # Defaults to `MAXIMIZE`.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]989 },
990 "region": "A String", # Required. The Google Compute Engine region to run the training job in.
991 "args": [ # Optional. Command line arguments to pass to the program.
992 "A String",
993 ],
994 "pythonModule": "A String", # Required. The Python module name to run after installing the packages.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]995 "jobDir": "A String", # Optional. A Google Cloud Storage path in which to store training outputs
996 # and other data needed for training. This path is passed to your TensorFlow
997 # program as the 'job_dir' command-line argument. The benefit of specifying
998 # this field is that Cloud ML validates the path for use in training.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]999 "packageUris": [ # Required. The Google Cloud Storage location of the packages with
1000 # the training program and any additional dependencies.
1001 "A String",
1002 ],
1003 "workerCount": "A String", # Optional. The number of worker replicas to use for the training job. Each
1004 # replica in the cluster will be of the type specified in `worker_type`.
1005 #
1006 # This value can only be used when `scale_tier` is set to `CUSTOM`. If you
1007 # set this value, you must also set `worker_type`.
1008 "parameterServerType": "A String", # Optional. Specifies the type of virtual machine to use for your training
1009 # job's parameter server.
1010 #
1011 # The supported values are the same as those described in the entry for
1012 # `master_type`.
1013 #
1014 # This value must be present when `scaleTier` is set to `CUSTOM` and
1015 # `parameter_server_count` is greater than zero.
1016 "parameterServerCount": "A String", # Optional. The number of parameter server replicas to use for the training
1017 # job. Each replica in the cluster will be of the type specified in
1018 # `parameter_server_type`.
1019 #
1020 # This value can only be used when `scale_tier` is set to `CUSTOM`.If you
1021 # set this value, you must also set `parameter_server_type`.
1022 },
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame^]1023 "jobId": "A String", # Required. The user-specified id of the job.
1024 "state": "A String", # Output only. The detailed state of a job.
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]1025 "predictionInput": { # Represents input parameters for a prediction job. # Input parameters to create a prediction job.
1026 "modelName": "A String", # Use this field if you want to use the default version for the specified
1027 # model. The string must use the following format:
1028 #
1029 # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>[YOUR_MODEL]</var>"`
1030 "runtimeVersion": "A String", # Optional. The Google Cloud ML runtime version to use for this batch
1031 # prediction. If not set, Google Cloud ML will pick the runtime version used
1032 # during the CreateVersion request for this model version, or choose the
1033 # latest stable version when model version information is not available
1034 # such as when the model is specified by uri.
1035 "inputPaths": [ # Required. The Google Cloud Storage location of the input data files.
1036 # May contain wildcards.
1037 "A String",
1038 ],
1039 "maxWorkerCount": "A String", # Optional. The maximum number of workers to be used for parallel processing.
1040 # Defaults to 10 if not specified.
1041 "uri": "A String", # Use this field if you want to specify a Google Cloud Storage path for
1042 # the model to use.
1043 "outputPath": "A String", # Required. The output Google Cloud Storage location.
1044 "dataFormat": "A String", # Required. The format of the input data files.
1045 "versionName": "A String", # Use this field if you want to specify a version of the model to use. The
1046 # string is formatted the same way as `model_version`, with the addition
1047 # of the version information:
1048 #
1049 # `"projects/<var>[YOUR_PROJECT]</var>/models/<var>YOUR_MODEL/versions/<var>[YOUR_VERSION]</var>"`
1050 "region": "A String", # Required. The Google Compute Engine region to run the prediction job in.
1051 },
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]1052 "endTime": "A String", # Output only. When the job processing was completed.
1053 "predictionOutput": { # Represents results of a prediction job. # The current prediction job result.
1054 "outputPath": "A String", # The output Google Cloud Storage location provided at the job creation time.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]1055 "nodeHours": 3.14, # Node hours used by the batch prediction job.
Sai Cheemalapatiea3a5e12016-10-12 14:05:53 -0700[diff] [blame]1056 "predictionCount": "A String", # The number of generated predictions.
1057 "errorCount": "A String", # The number of data instances which resulted in errors.
1058 },
1059 "createTime": "A String", # Output only. When the job was created.
1060 },
1061 ],
1062 }</pre>
1063</div>
1064
1065<div class="method">
1066 <code class="details" id="list_next">list_next(previous_request, previous_response)</code>
1067 <pre>Retrieves the next page of results.
1068
1069Args:
1070 previous_request: The request for the previous page. (required)
1071 previous_response: The response from the request for the previous page. (required)
1072
1073Returns:
1074 A request object that you can call 'execute()' on to request the next
1075 page. Returns None if there are no more items in the collection.
1076 </pre>
1077</div>
1078
1079</body></html>