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gerrit-public.fairphone.software / platform / external / python / google-api-python-client / 715bd7f9ca9a324a05ee05a6476af383e54930f9 / . / docs / dyn / ml_v1.projects.models.versions.html
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Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]1<html><body>
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Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]75<h1><a href="ml_v1.html">Cloud Machine Learning Engine</a> . <a href="ml_v1.projects.html">projects</a> . <a href="ml_v1.projects.models.html">models</a> . <a href="ml_v1.projects.models.versions.html">versions</a></h1>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[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="#create">create(parent, body, x__xgafv=None)</a></code></p>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]79<p class="firstline">Creates a new version of a model from a trained TensorFlow model.</p>
80<p class="toc_element">
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]81 <code><a href="#delete">delete(name, x__xgafv=None)</a></code></p>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]82<p class="firstline">Deletes a model version.</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 Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]85<p class="firstline">Gets information about a model version.</p>
86<p class="toc_element">
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]87 <code><a href="#list">list(parent, pageToken=None, x__xgafv=None, pageSize=None, filter=None)</a></code></p>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]88<p class="firstline">Gets basic information about all the versions of a model.</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<p class="toc_element">
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]93 <code><a href="#patch">patch(name, body, updateMask=None, x__xgafv=None)</a></code></p>
94<p class="firstline">Updates the specified Version resource.</p>
95<p class="toc_element">
96 <code><a href="#setDefault">setDefault(name, body=None, x__xgafv=None)</a></code></p>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]97<p class="firstline">Designates a version to be the default for the model.</p>
98<h3>Method Details</h3>
99<div class="method">
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]100 <code class="details" id="create">create(parent, body, x__xgafv=None)</code>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]101 <pre>Creates a new version of a model from a trained TensorFlow model.
102
103If the version created in the cloud by this call is the first deployed
104version of the specified model, it will be made the default version of the
105model. When you add a version to a model that already has one or more
106versions, the default version does not automatically change. If you want a
107new version to be the default, you must call
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]108[projects.models.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]109
110Args:
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]111 parent: string, Required. The name of the model. (required)
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]112 body: object, The request body. (required)
113 The object takes the form of:
114
115{ # Represents a version of the model.
116 #
117 # Each version is a trained model deployed in the cloud, ready to handle
118 # prediction requests. A model can have multiple versions. You can get
119 # information about all of the versions of a given model by calling
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]120 # [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]121 "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
122 "labels": { # Optional. One or more labels that you can add, to organize your model
123 # versions. Each label is a key-value pair, where both the key and the value
124 # are arbitrary strings that you supply.
125 # For more information, see the documentation on
126 # <a href="/ml-engine/docs/tensorflow/resource-labels">using labels</a>.
127 "a_key": "A String",
128 },
129 "machineType": "A String", # Optional. The type of machine on which to serve the model. Currently only
130 # applies to online prediction service.
131 # <dl>
132 # <dt>mls1-c1-m2</dt>
133 # <dd>
134 # The <b>default</b> machine type, with 1 core and 2 GB RAM. The deprecated
135 # name for this machine type is "mls1-highmem-1".
136 # </dd>
137 # <dt>mls1-c4-m2</dt>
138 # <dd>
139 # In <b>Beta</b>. This machine type has 4 cores and 2 GB RAM. The
140 # deprecated name for this machine type is "mls1-highcpu-4".
141 # </dd>
142 # </dl>
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]143 "description": "A String", # Optional. The description specified for the version when it was created.
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]144 "runtimeVersion": "A String", # Optional. The AI Platform runtime version to use for this deployment.
145 # If not set, AI Platform uses the default stable version, 1.0. For more
146 # information, see the
147 # [runtime version list](/ml-engine/docs/runtime-version-list) and
148 # [how to manage runtime versions](/ml-engine/docs/versioning).
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]149 "manualScaling": { # Options for manually scaling a model. # Manually select the number of nodes to use for serving the
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]150 # model. You should generally use `auto_scaling` with an appropriate
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]151 # `min_nodes` instead, but this option is available if you want more
152 # predictable billing. Beware that latency and error rates will increase
153 # if the traffic exceeds that capability of the system to serve it based
154 # on the selected number of nodes.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]155 "nodes": 42, # The number of nodes to allocate for this model. These nodes are always up,
156 # starting from the time the model is deployed, so the cost of operating
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]157 # this model will be proportional to `nodes` * number of hours since
158 # last billing cycle plus the cost for each prediction performed.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]159 },
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]160 "predictionClass": "A String", # Optional. The fully qualified name
161 # (<var>module_name</var>.<var>class_name</var>) of a class that implements
162 # the Predictor interface described in this reference field. The module
163 # containing this class should be included in a package provided to the
164 # [`packageUris` field](#Version.FIELDS.package_uris).
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]165 #
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]166 # Specify this field if and only if you are deploying a [custom prediction
167 # routine (beta)](/ml-engine/docs/tensorflow/custom-prediction-routines).
168 # If you specify this field, you must set
169 # [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
170 #
171 # The following code sample provides the Predictor interface:
172 #
173 # ```py
174 # class Predictor(object):
175 # """Interface for constructing custom predictors."""
176 #
177 # def predict(self, instances, **kwargs):
178 # """Performs custom prediction.
179 #
180 # Instances are the decoded values from the request. They have already
181 # been deserialized from JSON.
182 #
183 # Args:
184 # instances: A list of prediction input instances.
185 # **kwargs: A dictionary of keyword args provided as additional
186 # fields on the predict request body.
187 #
188 # Returns:
189 # A list of outputs containing the prediction results. This list must
190 # be JSON serializable.
191 # """
192 # raise NotImplementedError()
193 #
194 # @classmethod
195 # def from_path(cls, model_dir):
196 # """Creates an instance of Predictor using the given path.
197 #
198 # Loading of the predictor should be done in this method.
199 #
200 # Args:
201 # model_dir: The local directory that contains the exported model
202 # file along with any additional files uploaded when creating the
203 # version resource.
204 #
205 # Returns:
206 # An instance implementing this Predictor class.
207 # """
208 # raise NotImplementedError()
209 # ```
210 #
211 # Learn more about [the Predictor interface and custom prediction
212 # routines](/ml-engine/docs/tensorflow/custom-prediction-routines).
213 "autoScaling": { # Options for automatically scaling a model. # Automatically scale the number of nodes used to serve the model in
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]214 # response to increases and decreases in traffic. Care should be
215 # taken to ramp up traffic according to the model's ability to scale
216 # or you will start seeing increases in latency and 429 response codes.
217 "minNodes": 42, # Optional. The minimum number of nodes to allocate for this model. These
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]218 # nodes are always up, starting from the time the model is deployed.
219 # Therefore, the cost of operating this model will be at least
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]220 # `rate` * `min_nodes` * number of hours since last billing cycle,
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]221 # where `rate` is the cost per node-hour as documented in the
222 # [pricing guide](/ml-engine/docs/pricing),
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]223 # even if no predictions are performed. There is additional cost for each
224 # prediction performed.
225 #
226 # Unlike manual scaling, if the load gets too heavy for the nodes
227 # that are up, the service will automatically add nodes to handle the
228 # increased load as well as scale back as traffic drops, always maintaining
229 # at least `min_nodes`. You will be charged for the time in which additional
230 # nodes are used.
231 #
232 # If not specified, `min_nodes` defaults to 0, in which case, when traffic
233 # to a model stops (and after a cool-down period), nodes will be shut down
234 # and no charges will be incurred until traffic to the model resumes.
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]235 #
236 # You can set `min_nodes` when creating the model version, and you can also
237 # update `min_nodes` for an existing version:
238 # <pre>
239 # update_body.json:
240 # {
241 # 'autoScaling': {
242 # 'minNodes': 5
243 # }
244 # }
245 # </pre>
246 # HTTP request:
247 # <pre>
248 # PATCH
249 # https://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes
250 # -d @./update_body.json
251 # </pre>
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]252 },
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]253 "serviceAccount": "A String", # Optional. Specifies the service account for resource access control.
254 "state": "A String", # Output only. The state of a version.
255 "pythonVersion": "A String", # Optional. The version of Python used in prediction. If not set, the default
256 # version is '2.7'. Python '3.5' is available when `runtime_version` is set
257 # to '1.4' and above. Python '2.7' works with all supported runtime versions.
258 "framework": "A String", # Optional. The machine learning framework AI Platform uses to train
259 # this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`,
260 # `XGBOOST`. If you do not specify a framework, AI Platform
261 # will analyze files in the deployment_uri to determine a framework. If you
262 # choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version
263 # of the model to 1.4 or greater.
264 #
265 # Do **not** specify a framework if you're deploying a [custom
266 # prediction routine](/ml-engine/docs/tensorflow/custom-prediction-routines).
267 "packageUris": [ # Optional. Cloud Storage paths (`gs://…`) of packages for [custom
268 # prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines)
269 # or [scikit-learn pipelines with custom
270 # code](/ml-engine/docs/scikit/exporting-for-prediction#custom-pipeline-code).
271 #
272 # For a custom prediction routine, one of these packages must contain your
273 # Predictor class (see
274 # [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally,
275 # include any dependencies used by your Predictor or scikit-learn pipeline
276 # uses that are not already included in your selected [runtime
277 # version](/ml-engine/docs/tensorflow/runtime-version-list).
278 #
279 # If you specify this field, you must also set
280 # [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
281 "A String",
282 ],
283 "etag": "A String", # `etag` is used for optimistic concurrency control as a way to help
284 # prevent simultaneous updates of a model from overwriting each other.
285 # It is strongly suggested that systems make use of the `etag` in the
286 # read-modify-write cycle to perform model updates in order to avoid race
287 # conditions: An `etag` is returned in the response to `GetVersion`, and
288 # systems are expected to put that etag in the request to `UpdateVersion` to
289 # ensure that their change will be applied to the model as intended.
290 "lastUseTime": "A String", # Output only. The time the version was last used for prediction.
291 "deploymentUri": "A String", # Required. The Cloud Storage location of the trained model used to
292 # create the version. See the
293 # [guide to model
294 # deployment](/ml-engine/docs/tensorflow/deploying-models) for more
295 # information.
296 #
297 # When passing Version to
298 # [projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create)
299 # the model service uses the specified location as the source of the model.
300 # Once deployed, the model version is hosted by the prediction service, so
301 # this location is useful only as a historical record.
302 # The total number of model files can't exceed 1000.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]303 "createTime": "A String", # Output only. The time the version was created.
304 "isDefault": True or False, # Output only. If true, this version will be used to handle prediction
305 # requests that do not specify a version.
306 #
307 # You can change the default version by calling
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]308 # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]309 "name": "A String", # Required.The name specified for the version when it was created.
310 #
311 # The version name must be unique within the model it is created in.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]312}
313
314 x__xgafv: string, V1 error format.
315 Allowed values
316 1 - v1 error format
317 2 - v2 error format
318
319Returns:
320 An object of the form:
321
322 { # This resource represents a long-running operation that is the result of a
323 # network API call.
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]324 "metadata": { # Service-specific metadata associated with the operation. It typically
325 # contains progress information and common metadata such as create time.
326 # Some services might not provide such metadata. Any method that returns a
327 # long-running operation should document the metadata type, if any.
328 "a_key": "", # Properties of the object. Contains field @type with type URL.
329 },
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]330 "error": { # The `Status` type defines a logical error model that is suitable for # The error result of the operation in case of failure or cancellation.
331 # different programming environments, including REST APIs and RPC APIs. It is
332 # used by [gRPC](https://github.com/grpc). Each `Status` message contains
333 # three pieces of data: error code, error message, and error details.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]334 #
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]335 # You can find out more about this error model and how to work with it in the
336 # [API Design Guide](https://cloud.google.com/apis/design/errors).
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]337 "message": "A String", # A developer-facing error message, which should be in English. Any
338 # user-facing error message should be localized and sent in the
339 # google.rpc.Status.details field, or localized by the client.
340 "code": 42, # The status code, which should be an enum value of google.rpc.Code.
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]341 "details": [ # A list of messages that carry the error details. There is a common set of
342 # message types for APIs to use.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]343 {
344 "a_key": "", # Properties of the object. Contains field @type with type URL.
345 },
346 ],
347 },
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]348 "done": True or False, # If the value is `false`, it means the operation is still in progress.
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]349 # If `true`, the operation is completed, and either `error` or `response` is
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]350 # available.
351 "response": { # The normal response of the operation in case of success. If the original
352 # method returns no data on success, such as `Delete`, the response is
353 # `google.protobuf.Empty`. If the original method is standard
354 # `Get`/`Create`/`Update`, the response should be the resource. For other
355 # methods, the response should have the type `XxxResponse`, where `Xxx`
356 # is the original method name. For example, if the original method name
357 # is `TakeSnapshot()`, the inferred response type is
358 # `TakeSnapshotResponse`.
359 "a_key": "", # Properties of the object. Contains field @type with type URL.
360 },
361 "name": "A String", # The server-assigned name, which is only unique within the same service that
362 # originally returns it. If you use the default HTTP mapping, the
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]363 # `name` should be a resource name ending with `operations/{unique_id}`.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]364 }</pre>
365</div>
366
367<div class="method">
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]368 <code class="details" id="delete">delete(name, x__xgafv=None)</code>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]369 <pre>Deletes a model version.
370
371Each model can have multiple versions deployed and in use at any given
372time. Use this method to remove a single version.
373
374Note: You cannot delete the version that is set as the default version
375of the model unless it is the only remaining version.
376
377Args:
378 name: string, Required. The name of the version. You can get the names of all the
379versions of a model by calling
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]380[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list). (required)
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]381 x__xgafv: string, V1 error format.
382 Allowed values
383 1 - v1 error format
384 2 - v2 error format
385
386Returns:
387 An object of the form:
388
389 { # This resource represents a long-running operation that is the result of a
390 # network API call.
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]391 "metadata": { # Service-specific metadata associated with the operation. It typically
392 # contains progress information and common metadata such as create time.
393 # Some services might not provide such metadata. Any method that returns a
394 # long-running operation should document the metadata type, if any.
395 "a_key": "", # Properties of the object. Contains field @type with type URL.
396 },
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]397 "error": { # The `Status` type defines a logical error model that is suitable for # The error result of the operation in case of failure or cancellation.
398 # different programming environments, including REST APIs and RPC APIs. It is
399 # used by [gRPC](https://github.com/grpc). Each `Status` message contains
400 # three pieces of data: error code, error message, and error details.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]401 #
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]402 # You can find out more about this error model and how to work with it in the
403 # [API Design Guide](https://cloud.google.com/apis/design/errors).
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]404 "message": "A String", # A developer-facing error message, which should be in English. Any
405 # user-facing error message should be localized and sent in the
406 # google.rpc.Status.details field, or localized by the client.
407 "code": 42, # The status code, which should be an enum value of google.rpc.Code.
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]408 "details": [ # A list of messages that carry the error details. There is a common set of
409 # message types for APIs to use.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]410 {
411 "a_key": "", # Properties of the object. Contains field @type with type URL.
412 },
413 ],
414 },
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]415 "done": True or False, # If the value is `false`, it means the operation is still in progress.
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]416 # If `true`, the operation is completed, and either `error` or `response` is
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]417 # available.
418 "response": { # The normal response of the operation in case of success. If the original
419 # method returns no data on success, such as `Delete`, the response is
420 # `google.protobuf.Empty`. If the original method is standard
421 # `Get`/`Create`/`Update`, the response should be the resource. For other
422 # methods, the response should have the type `XxxResponse`, where `Xxx`
423 # is the original method name. For example, if the original method name
424 # is `TakeSnapshot()`, the inferred response type is
425 # `TakeSnapshotResponse`.
426 "a_key": "", # Properties of the object. Contains field @type with type URL.
427 },
428 "name": "A String", # The server-assigned name, which is only unique within the same service that
429 # originally returns it. If you use the default HTTP mapping, the
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]430 # `name` should be a resource name ending with `operations/{unique_id}`.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]431 }</pre>
432</div>
433
434<div class="method">
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]435 <code class="details" id="get">get(name, x__xgafv=None)</code>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]436 <pre>Gets information about a model version.
437
438Models can have multiple versions. You can call
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]439[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list)
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]440to get the same information that this method returns for all of the
441versions of a model.
442
443Args:
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]444 name: string, Required. The name of the version. (required)
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]445 x__xgafv: string, V1 error format.
446 Allowed values
447 1 - v1 error format
448 2 - v2 error format
449
450Returns:
451 An object of the form:
452
453 { # Represents a version of the model.
454 #
455 # Each version is a trained model deployed in the cloud, ready to handle
456 # prediction requests. A model can have multiple versions. You can get
457 # information about all of the versions of a given model by calling
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]458 # [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]459 "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
460 "labels": { # Optional. One or more labels that you can add, to organize your model
461 # versions. Each label is a key-value pair, where both the key and the value
462 # are arbitrary strings that you supply.
463 # For more information, see the documentation on
464 # <a href="/ml-engine/docs/tensorflow/resource-labels">using labels</a>.
465 "a_key": "A String",
466 },
467 "machineType": "A String", # Optional. The type of machine on which to serve the model. Currently only
468 # applies to online prediction service.
469 # <dl>
470 # <dt>mls1-c1-m2</dt>
471 # <dd>
472 # The <b>default</b> machine type, with 1 core and 2 GB RAM. The deprecated
473 # name for this machine type is "mls1-highmem-1".
474 # </dd>
475 # <dt>mls1-c4-m2</dt>
476 # <dd>
477 # In <b>Beta</b>. This machine type has 4 cores and 2 GB RAM. The
478 # deprecated name for this machine type is "mls1-highcpu-4".
479 # </dd>
480 # </dl>
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]481 "description": "A String", # Optional. The description specified for the version when it was created.
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]482 "runtimeVersion": "A String", # Optional. The AI Platform runtime version to use for this deployment.
483 # If not set, AI Platform uses the default stable version, 1.0. For more
484 # information, see the
485 # [runtime version list](/ml-engine/docs/runtime-version-list) and
486 # [how to manage runtime versions](/ml-engine/docs/versioning).
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]487 "manualScaling": { # Options for manually scaling a model. # Manually select the number of nodes to use for serving the
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]488 # model. You should generally use `auto_scaling` with an appropriate
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]489 # `min_nodes` instead, but this option is available if you want more
490 # predictable billing. Beware that latency and error rates will increase
491 # if the traffic exceeds that capability of the system to serve it based
492 # on the selected number of nodes.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]493 "nodes": 42, # The number of nodes to allocate for this model. These nodes are always up,
494 # starting from the time the model is deployed, so the cost of operating
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]495 # this model will be proportional to `nodes` * number of hours since
496 # last billing cycle plus the cost for each prediction performed.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]497 },
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]498 "predictionClass": "A String", # Optional. The fully qualified name
499 # (<var>module_name</var>.<var>class_name</var>) of a class that implements
500 # the Predictor interface described in this reference field. The module
501 # containing this class should be included in a package provided to the
502 # [`packageUris` field](#Version.FIELDS.package_uris).
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]503 #
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]504 # Specify this field if and only if you are deploying a [custom prediction
505 # routine (beta)](/ml-engine/docs/tensorflow/custom-prediction-routines).
506 # If you specify this field, you must set
507 # [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
508 #
509 # The following code sample provides the Predictor interface:
510 #
511 # ```py
512 # class Predictor(object):
513 # """Interface for constructing custom predictors."""
514 #
515 # def predict(self, instances, **kwargs):
516 # """Performs custom prediction.
517 #
518 # Instances are the decoded values from the request. They have already
519 # been deserialized from JSON.
520 #
521 # Args:
522 # instances: A list of prediction input instances.
523 # **kwargs: A dictionary of keyword args provided as additional
524 # fields on the predict request body.
525 #
526 # Returns:
527 # A list of outputs containing the prediction results. This list must
528 # be JSON serializable.
529 # """
530 # raise NotImplementedError()
531 #
532 # @classmethod
533 # def from_path(cls, model_dir):
534 # """Creates an instance of Predictor using the given path.
535 #
536 # Loading of the predictor should be done in this method.
537 #
538 # Args:
539 # model_dir: The local directory that contains the exported model
540 # file along with any additional files uploaded when creating the
541 # version resource.
542 #
543 # Returns:
544 # An instance implementing this Predictor class.
545 # """
546 # raise NotImplementedError()
547 # ```
548 #
549 # Learn more about [the Predictor interface and custom prediction
550 # routines](/ml-engine/docs/tensorflow/custom-prediction-routines).
551 "autoScaling": { # Options for automatically scaling a model. # Automatically scale the number of nodes used to serve the model in
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]552 # response to increases and decreases in traffic. Care should be
553 # taken to ramp up traffic according to the model's ability to scale
554 # or you will start seeing increases in latency and 429 response codes.
555 "minNodes": 42, # Optional. The minimum number of nodes to allocate for this model. These
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]556 # nodes are always up, starting from the time the model is deployed.
557 # Therefore, the cost of operating this model will be at least
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]558 # `rate` * `min_nodes` * number of hours since last billing cycle,
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]559 # where `rate` is the cost per node-hour as documented in the
560 # [pricing guide](/ml-engine/docs/pricing),
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]561 # even if no predictions are performed. There is additional cost for each
562 # prediction performed.
563 #
564 # Unlike manual scaling, if the load gets too heavy for the nodes
565 # that are up, the service will automatically add nodes to handle the
566 # increased load as well as scale back as traffic drops, always maintaining
567 # at least `min_nodes`. You will be charged for the time in which additional
568 # nodes are used.
569 #
570 # If not specified, `min_nodes` defaults to 0, in which case, when traffic
571 # to a model stops (and after a cool-down period), nodes will be shut down
572 # and no charges will be incurred until traffic to the model resumes.
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]573 #
574 # You can set `min_nodes` when creating the model version, and you can also
575 # update `min_nodes` for an existing version:
576 # <pre>
577 # update_body.json:
578 # {
579 # 'autoScaling': {
580 # 'minNodes': 5
581 # }
582 # }
583 # </pre>
584 # HTTP request:
585 # <pre>
586 # PATCH
587 # https://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes
588 # -d @./update_body.json
589 # </pre>
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]590 },
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]591 "serviceAccount": "A String", # Optional. Specifies the service account for resource access control.
592 "state": "A String", # Output only. The state of a version.
593 "pythonVersion": "A String", # Optional. The version of Python used in prediction. If not set, the default
594 # version is '2.7'. Python '3.5' is available when `runtime_version` is set
595 # to '1.4' and above. Python '2.7' works with all supported runtime versions.
596 "framework": "A String", # Optional. The machine learning framework AI Platform uses to train
597 # this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`,
598 # `XGBOOST`. If you do not specify a framework, AI Platform
599 # will analyze files in the deployment_uri to determine a framework. If you
600 # choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version
601 # of the model to 1.4 or greater.
602 #
603 # Do **not** specify a framework if you're deploying a [custom
604 # prediction routine](/ml-engine/docs/tensorflow/custom-prediction-routines).
605 "packageUris": [ # Optional. Cloud Storage paths (`gs://…`) of packages for [custom
606 # prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines)
607 # or [scikit-learn pipelines with custom
608 # code](/ml-engine/docs/scikit/exporting-for-prediction#custom-pipeline-code).
609 #
610 # For a custom prediction routine, one of these packages must contain your
611 # Predictor class (see
612 # [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally,
613 # include any dependencies used by your Predictor or scikit-learn pipeline
614 # uses that are not already included in your selected [runtime
615 # version](/ml-engine/docs/tensorflow/runtime-version-list).
616 #
617 # If you specify this field, you must also set
618 # [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
619 "A String",
620 ],
621 "etag": "A String", # `etag` is used for optimistic concurrency control as a way to help
622 # prevent simultaneous updates of a model from overwriting each other.
623 # It is strongly suggested that systems make use of the `etag` in the
624 # read-modify-write cycle to perform model updates in order to avoid race
625 # conditions: An `etag` is returned in the response to `GetVersion`, and
626 # systems are expected to put that etag in the request to `UpdateVersion` to
627 # ensure that their change will be applied to the model as intended.
628 "lastUseTime": "A String", # Output only. The time the version was last used for prediction.
629 "deploymentUri": "A String", # Required. The Cloud Storage location of the trained model used to
630 # create the version. See the
631 # [guide to model
632 # deployment](/ml-engine/docs/tensorflow/deploying-models) for more
633 # information.
634 #
635 # When passing Version to
636 # [projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create)
637 # the model service uses the specified location as the source of the model.
638 # Once deployed, the model version is hosted by the prediction service, so
639 # this location is useful only as a historical record.
640 # The total number of model files can't exceed 1000.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]641 "createTime": "A String", # Output only. The time the version was created.
642 "isDefault": True or False, # Output only. If true, this version will be used to handle prediction
643 # requests that do not specify a version.
644 #
645 # You can change the default version by calling
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]646 # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]647 "name": "A String", # Required.The name specified for the version when it was created.
648 #
649 # The version name must be unique within the model it is created in.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]650 }</pre>
651</div>
652
653<div class="method">
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]654 <code class="details" id="list">list(parent, pageToken=None, x__xgafv=None, pageSize=None, filter=None)</code>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]655 <pre>Gets basic information about all the versions of a model.
656
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]657If you expect that a model has many versions, or if you need to handle
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]658only a limited number of results at a time, you can request that the list
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]659be retrieved in batches (called pages).
660
661If there are no versions that match the request parameters, the list
662request returns an empty response body: {}.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]663
664Args:
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]665 parent: string, Required. The name of the model for which to list the version. (required)
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]666 pageToken: string, Optional. A page token to request the next page of results.
667
668You get the token from the `next_page_token` field of the response from
669the previous call.
670 x__xgafv: string, V1 error format.
671 Allowed values
672 1 - v1 error format
673 2 - v2 error format
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]674 pageSize: integer, Optional. The number of versions to retrieve per "page" of results. If
675there are more remaining results than this number, the response message
676will contain a valid value in the `next_page_token` field.
677
678The default value is 20, and the maximum page size is 100.
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]679 filter: string, Optional. Specifies the subset of versions to retrieve.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]680
681Returns:
682 An object of the form:
683
684 { # Response message for the ListVersions method.
685 "nextPageToken": "A String", # Optional. Pass this token as the `page_token` field of the request for a
686 # subsequent call.
687 "versions": [ # The list of versions.
688 { # Represents a version of the model.
689 #
690 # Each version is a trained model deployed in the cloud, ready to handle
691 # prediction requests. A model can have multiple versions. You can get
692 # information about all of the versions of a given model by calling
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]693 # [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]694 "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
695 "labels": { # Optional. One or more labels that you can add, to organize your model
696 # versions. Each label is a key-value pair, where both the key and the value
697 # are arbitrary strings that you supply.
698 # For more information, see the documentation on
699 # <a href="/ml-engine/docs/tensorflow/resource-labels">using labels</a>.
700 "a_key": "A String",
701 },
702 "machineType": "A String", # Optional. The type of machine on which to serve the model. Currently only
703 # applies to online prediction service.
704 # <dl>
705 # <dt>mls1-c1-m2</dt>
706 # <dd>
707 # The <b>default</b> machine type, with 1 core and 2 GB RAM. The deprecated
708 # name for this machine type is "mls1-highmem-1".
709 # </dd>
710 # <dt>mls1-c4-m2</dt>
711 # <dd>
712 # In <b>Beta</b>. This machine type has 4 cores and 2 GB RAM. The
713 # deprecated name for this machine type is "mls1-highcpu-4".
714 # </dd>
715 # </dl>
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]716 "description": "A String", # Optional. The description specified for the version when it was created.
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]717 "runtimeVersion": "A String", # Optional. The AI Platform runtime version to use for this deployment.
718 # If not set, AI Platform uses the default stable version, 1.0. For more
719 # information, see the
720 # [runtime version list](/ml-engine/docs/runtime-version-list) and
721 # [how to manage runtime versions](/ml-engine/docs/versioning).
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]722 "manualScaling": { # Options for manually scaling a model. # Manually select the number of nodes to use for serving the
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]723 # model. You should generally use `auto_scaling` with an appropriate
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]724 # `min_nodes` instead, but this option is available if you want more
725 # predictable billing. Beware that latency and error rates will increase
726 # if the traffic exceeds that capability of the system to serve it based
727 # on the selected number of nodes.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]728 "nodes": 42, # The number of nodes to allocate for this model. These nodes are always up,
729 # starting from the time the model is deployed, so the cost of operating
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]730 # this model will be proportional to `nodes` * number of hours since
731 # last billing cycle plus the cost for each prediction performed.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]732 },
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]733 "predictionClass": "A String", # Optional. The fully qualified name
734 # (<var>module_name</var>.<var>class_name</var>) of a class that implements
735 # the Predictor interface described in this reference field. The module
736 # containing this class should be included in a package provided to the
737 # [`packageUris` field](#Version.FIELDS.package_uris).
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]738 #
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]739 # Specify this field if and only if you are deploying a [custom prediction
740 # routine (beta)](/ml-engine/docs/tensorflow/custom-prediction-routines).
741 # If you specify this field, you must set
742 # [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
743 #
744 # The following code sample provides the Predictor interface:
745 #
746 # ```py
747 # class Predictor(object):
748 # """Interface for constructing custom predictors."""
749 #
750 # def predict(self, instances, **kwargs):
751 # """Performs custom prediction.
752 #
753 # Instances are the decoded values from the request. They have already
754 # been deserialized from JSON.
755 #
756 # Args:
757 # instances: A list of prediction input instances.
758 # **kwargs: A dictionary of keyword args provided as additional
759 # fields on the predict request body.
760 #
761 # Returns:
762 # A list of outputs containing the prediction results. This list must
763 # be JSON serializable.
764 # """
765 # raise NotImplementedError()
766 #
767 # @classmethod
768 # def from_path(cls, model_dir):
769 # """Creates an instance of Predictor using the given path.
770 #
771 # Loading of the predictor should be done in this method.
772 #
773 # Args:
774 # model_dir: The local directory that contains the exported model
775 # file along with any additional files uploaded when creating the
776 # version resource.
777 #
778 # Returns:
779 # An instance implementing this Predictor class.
780 # """
781 # raise NotImplementedError()
782 # ```
783 #
784 # Learn more about [the Predictor interface and custom prediction
785 # routines](/ml-engine/docs/tensorflow/custom-prediction-routines).
786 "autoScaling": { # Options for automatically scaling a model. # Automatically scale the number of nodes used to serve the model in
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]787 # response to increases and decreases in traffic. Care should be
788 # taken to ramp up traffic according to the model's ability to scale
789 # or you will start seeing increases in latency and 429 response codes.
790 "minNodes": 42, # Optional. The minimum number of nodes to allocate for this model. These
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]791 # nodes are always up, starting from the time the model is deployed.
792 # Therefore, the cost of operating this model will be at least
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]793 # `rate` * `min_nodes` * number of hours since last billing cycle,
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]794 # where `rate` is the cost per node-hour as documented in the
795 # [pricing guide](/ml-engine/docs/pricing),
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]796 # even if no predictions are performed. There is additional cost for each
797 # prediction performed.
798 #
799 # Unlike manual scaling, if the load gets too heavy for the nodes
800 # that are up, the service will automatically add nodes to handle the
801 # increased load as well as scale back as traffic drops, always maintaining
802 # at least `min_nodes`. You will be charged for the time in which additional
803 # nodes are used.
804 #
805 # If not specified, `min_nodes` defaults to 0, in which case, when traffic
806 # to a model stops (and after a cool-down period), nodes will be shut down
807 # and no charges will be incurred until traffic to the model resumes.
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]808 #
809 # You can set `min_nodes` when creating the model version, and you can also
810 # update `min_nodes` for an existing version:
811 # <pre>
812 # update_body.json:
813 # {
814 # 'autoScaling': {
815 # 'minNodes': 5
816 # }
817 # }
818 # </pre>
819 # HTTP request:
820 # <pre>
821 # PATCH
822 # https://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes
823 # -d @./update_body.json
824 # </pre>
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]825 },
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]826 "serviceAccount": "A String", # Optional. Specifies the service account for resource access control.
827 "state": "A String", # Output only. The state of a version.
828 "pythonVersion": "A String", # Optional. The version of Python used in prediction. If not set, the default
829 # version is '2.7'. Python '3.5' is available when `runtime_version` is set
830 # to '1.4' and above. Python '2.7' works with all supported runtime versions.
831 "framework": "A String", # Optional. The machine learning framework AI Platform uses to train
832 # this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`,
833 # `XGBOOST`. If you do not specify a framework, AI Platform
834 # will analyze files in the deployment_uri to determine a framework. If you
835 # choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version
836 # of the model to 1.4 or greater.
837 #
838 # Do **not** specify a framework if you're deploying a [custom
839 # prediction routine](/ml-engine/docs/tensorflow/custom-prediction-routines).
840 "packageUris": [ # Optional. Cloud Storage paths (`gs://…`) of packages for [custom
841 # prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines)
842 # or [scikit-learn pipelines with custom
843 # code](/ml-engine/docs/scikit/exporting-for-prediction#custom-pipeline-code).
844 #
845 # For a custom prediction routine, one of these packages must contain your
846 # Predictor class (see
847 # [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally,
848 # include any dependencies used by your Predictor or scikit-learn pipeline
849 # uses that are not already included in your selected [runtime
850 # version](/ml-engine/docs/tensorflow/runtime-version-list).
851 #
852 # If you specify this field, you must also set
853 # [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
854 "A String",
855 ],
856 "etag": "A String", # `etag` is used for optimistic concurrency control as a way to help
857 # prevent simultaneous updates of a model from overwriting each other.
858 # It is strongly suggested that systems make use of the `etag` in the
859 # read-modify-write cycle to perform model updates in order to avoid race
860 # conditions: An `etag` is returned in the response to `GetVersion`, and
861 # systems are expected to put that etag in the request to `UpdateVersion` to
862 # ensure that their change will be applied to the model as intended.
863 "lastUseTime": "A String", # Output only. The time the version was last used for prediction.
864 "deploymentUri": "A String", # Required. The Cloud Storage location of the trained model used to
865 # create the version. See the
866 # [guide to model
867 # deployment](/ml-engine/docs/tensorflow/deploying-models) for more
868 # information.
869 #
870 # When passing Version to
871 # [projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create)
872 # the model service uses the specified location as the source of the model.
873 # Once deployed, the model version is hosted by the prediction service, so
874 # this location is useful only as a historical record.
875 # The total number of model files can't exceed 1000.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]876 "createTime": "A String", # Output only. The time the version was created.
877 "isDefault": True or False, # Output only. If true, this version will be used to handle prediction
878 # requests that do not specify a version.
879 #
880 # You can change the default version by calling
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]881 # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]882 "name": "A String", # Required.The name specified for the version when it was created.
883 #
884 # The version name must be unique within the model it is created in.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]885 },
886 ],
887 }</pre>
888</div>
889
890<div class="method">
891 <code class="details" id="list_next">list_next(previous_request, previous_response)</code>
892 <pre>Retrieves the next page of results.
893
894Args:
895 previous_request: The request for the previous page. (required)
896 previous_response: The response from the request for the previous page. (required)
897
898Returns:
899 A request object that you can call 'execute()' on to request the next
900 page. Returns None if there are no more items in the collection.
901 </pre>
902</div>
903
904<div class="method">
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]905 <code class="details" id="patch">patch(name, body, updateMask=None, x__xgafv=None)</code>
906 <pre>Updates the specified Version resource.
907
908Currently the only update-able fields are `description` and
909`autoScaling.minNodes`.
910
911Args:
912 name: string, Required. The name of the model. (required)
913 body: object, The request body. (required)
914 The object takes the form of:
915
916{ # Represents a version of the model.
917 #
918 # Each version is a trained model deployed in the cloud, ready to handle
919 # prediction requests. A model can have multiple versions. You can get
920 # information about all of the versions of a given model by calling
921 # [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).
922 "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
923 "labels": { # Optional. One or more labels that you can add, to organize your model
924 # versions. Each label is a key-value pair, where both the key and the value
925 # are arbitrary strings that you supply.
926 # For more information, see the documentation on
927 # <a href="/ml-engine/docs/tensorflow/resource-labels">using labels</a>.
928 "a_key": "A String",
929 },
930 "machineType": "A String", # Optional. The type of machine on which to serve the model. Currently only
931 # applies to online prediction service.
932 # <dl>
933 # <dt>mls1-c1-m2</dt>
934 # <dd>
935 # The <b>default</b> machine type, with 1 core and 2 GB RAM. The deprecated
936 # name for this machine type is "mls1-highmem-1".
937 # </dd>
938 # <dt>mls1-c4-m2</dt>
939 # <dd>
940 # In <b>Beta</b>. This machine type has 4 cores and 2 GB RAM. The
941 # deprecated name for this machine type is "mls1-highcpu-4".
942 # </dd>
943 # </dl>
944 "description": "A String", # Optional. The description specified for the version when it was created.
945 "runtimeVersion": "A String", # Optional. The AI Platform runtime version to use for this deployment.
946 # If not set, AI Platform uses the default stable version, 1.0. For more
947 # information, see the
948 # [runtime version list](/ml-engine/docs/runtime-version-list) and
949 # [how to manage runtime versions](/ml-engine/docs/versioning).
950 "manualScaling": { # Options for manually scaling a model. # Manually select the number of nodes to use for serving the
951 # model. You should generally use `auto_scaling` with an appropriate
952 # `min_nodes` instead, but this option is available if you want more
953 # predictable billing. Beware that latency and error rates will increase
954 # if the traffic exceeds that capability of the system to serve it based
955 # on the selected number of nodes.
956 "nodes": 42, # The number of nodes to allocate for this model. These nodes are always up,
957 # starting from the time the model is deployed, so the cost of operating
958 # this model will be proportional to `nodes` * number of hours since
959 # last billing cycle plus the cost for each prediction performed.
960 },
961 "predictionClass": "A String", # Optional. The fully qualified name
962 # (<var>module_name</var>.<var>class_name</var>) of a class that implements
963 # the Predictor interface described in this reference field. The module
964 # containing this class should be included in a package provided to the
965 # [`packageUris` field](#Version.FIELDS.package_uris).
966 #
967 # Specify this field if and only if you are deploying a [custom prediction
968 # routine (beta)](/ml-engine/docs/tensorflow/custom-prediction-routines).
969 # If you specify this field, you must set
970 # [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
971 #
972 # The following code sample provides the Predictor interface:
973 #
974 # ```py
975 # class Predictor(object):
976 # """Interface for constructing custom predictors."""
977 #
978 # def predict(self, instances, **kwargs):
979 # """Performs custom prediction.
980 #
981 # Instances are the decoded values from the request. They have already
982 # been deserialized from JSON.
983 #
984 # Args:
985 # instances: A list of prediction input instances.
986 # **kwargs: A dictionary of keyword args provided as additional
987 # fields on the predict request body.
988 #
989 # Returns:
990 # A list of outputs containing the prediction results. This list must
991 # be JSON serializable.
992 # """
993 # raise NotImplementedError()
994 #
995 # @classmethod
996 # def from_path(cls, model_dir):
997 # """Creates an instance of Predictor using the given path.
998 #
999 # Loading of the predictor should be done in this method.
1000 #
1001 # Args:
1002 # model_dir: The local directory that contains the exported model
1003 # file along with any additional files uploaded when creating the
1004 # version resource.
1005 #
1006 # Returns:
1007 # An instance implementing this Predictor class.
1008 # """
1009 # raise NotImplementedError()
1010 # ```
1011 #
1012 # Learn more about [the Predictor interface and custom prediction
1013 # routines](/ml-engine/docs/tensorflow/custom-prediction-routines).
1014 "autoScaling": { # Options for automatically scaling a model. # Automatically scale the number of nodes used to serve the model in
1015 # response to increases and decreases in traffic. Care should be
1016 # taken to ramp up traffic according to the model's ability to scale
1017 # or you will start seeing increases in latency and 429 response codes.
1018 "minNodes": 42, # Optional. The minimum number of nodes to allocate for this model. These
1019 # nodes are always up, starting from the time the model is deployed.
1020 # Therefore, the cost of operating this model will be at least
1021 # `rate` * `min_nodes` * number of hours since last billing cycle,
1022 # where `rate` is the cost per node-hour as documented in the
1023 # [pricing guide](/ml-engine/docs/pricing),
1024 # even if no predictions are performed. There is additional cost for each
1025 # prediction performed.
1026 #
1027 # Unlike manual scaling, if the load gets too heavy for the nodes
1028 # that are up, the service will automatically add nodes to handle the
1029 # increased load as well as scale back as traffic drops, always maintaining
1030 # at least `min_nodes`. You will be charged for the time in which additional
1031 # nodes are used.
1032 #
1033 # If not specified, `min_nodes` defaults to 0, in which case, when traffic
1034 # to a model stops (and after a cool-down period), nodes will be shut down
1035 # and no charges will be incurred until traffic to the model resumes.
1036 #
1037 # You can set `min_nodes` when creating the model version, and you can also
1038 # update `min_nodes` for an existing version:
1039 # <pre>
1040 # update_body.json:
1041 # {
1042 # 'autoScaling': {
1043 # 'minNodes': 5
1044 # }
1045 # }
1046 # </pre>
1047 # HTTP request:
1048 # <pre>
1049 # PATCH
1050 # https://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes
1051 # -d @./update_body.json
1052 # </pre>
1053 },
1054 "serviceAccount": "A String", # Optional. Specifies the service account for resource access control.
1055 "state": "A String", # Output only. The state of a version.
1056 "pythonVersion": "A String", # Optional. The version of Python used in prediction. If not set, the default
1057 # version is '2.7'. Python '3.5' is available when `runtime_version` is set
1058 # to '1.4' and above. Python '2.7' works with all supported runtime versions.
1059 "framework": "A String", # Optional. The machine learning framework AI Platform uses to train
1060 # this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`,
1061 # `XGBOOST`. If you do not specify a framework, AI Platform
1062 # will analyze files in the deployment_uri to determine a framework. If you
1063 # choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version
1064 # of the model to 1.4 or greater.
1065 #
1066 # Do **not** specify a framework if you're deploying a [custom
1067 # prediction routine](/ml-engine/docs/tensorflow/custom-prediction-routines).
1068 "packageUris": [ # Optional. Cloud Storage paths (`gs://…`) of packages for [custom
1069 # prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines)
1070 # or [scikit-learn pipelines with custom
1071 # code](/ml-engine/docs/scikit/exporting-for-prediction#custom-pipeline-code).
1072 #
1073 # For a custom prediction routine, one of these packages must contain your
1074 # Predictor class (see
1075 # [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally,
1076 # include any dependencies used by your Predictor or scikit-learn pipeline
1077 # uses that are not already included in your selected [runtime
1078 # version](/ml-engine/docs/tensorflow/runtime-version-list).
1079 #
1080 # If you specify this field, you must also set
1081 # [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
1082 "A String",
1083 ],
1084 "etag": "A String", # `etag` is used for optimistic concurrency control as a way to help
1085 # prevent simultaneous updates of a model from overwriting each other.
1086 # It is strongly suggested that systems make use of the `etag` in the
1087 # read-modify-write cycle to perform model updates in order to avoid race
1088 # conditions: An `etag` is returned in the response to `GetVersion`, and
1089 # systems are expected to put that etag in the request to `UpdateVersion` to
1090 # ensure that their change will be applied to the model as intended.
1091 "lastUseTime": "A String", # Output only. The time the version was last used for prediction.
1092 "deploymentUri": "A String", # Required. The Cloud Storage location of the trained model used to
1093 # create the version. See the
1094 # [guide to model
1095 # deployment](/ml-engine/docs/tensorflow/deploying-models) for more
1096 # information.
1097 #
1098 # When passing Version to
1099 # [projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create)
1100 # the model service uses the specified location as the source of the model.
1101 # Once deployed, the model version is hosted by the prediction service, so
1102 # this location is useful only as a historical record.
1103 # The total number of model files can't exceed 1000.
1104 "createTime": "A String", # Output only. The time the version was created.
1105 "isDefault": True or False, # Output only. If true, this version will be used to handle prediction
1106 # requests that do not specify a version.
1107 #
1108 # You can change the default version by calling
1109 # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
1110 "name": "A String", # Required.The name specified for the version when it was created.
1111 #
1112 # The version name must be unique within the model it is created in.
1113}
1114
1115 updateMask: string, Required. Specifies the path, relative to `Version`, of the field to
1116update. Must be present and non-empty.
1117
1118For example, to change the description of a version to "foo", the
1119`update_mask` parameter would be specified as `description`, and the
1120`PATCH` request body would specify the new value, as follows:
1121 {
1122 "description": "foo"
1123 }
1124
1125Currently the only supported update mask fields are `description` and
1126`autoScaling.minNodes`.
1127 x__xgafv: string, V1 error format.
1128 Allowed values
1129 1 - v1 error format
1130 2 - v2 error format
1131
1132Returns:
1133 An object of the form:
1134
1135 { # This resource represents a long-running operation that is the result of a
1136 # network API call.
1137 "metadata": { # Service-specific metadata associated with the operation. It typically
1138 # contains progress information and common metadata such as create time.
1139 # Some services might not provide such metadata. Any method that returns a
1140 # long-running operation should document the metadata type, if any.
1141 "a_key": "", # Properties of the object. Contains field @type with type URL.
1142 },
1143 "error": { # The `Status` type defines a logical error model that is suitable for # The error result of the operation in case of failure or cancellation.
1144 # different programming environments, including REST APIs and RPC APIs. It is
1145 # used by [gRPC](https://github.com/grpc). Each `Status` message contains
1146 # three pieces of data: error code, error message, and error details.
1147 #
1148 # You can find out more about this error model and how to work with it in the
1149 # [API Design Guide](https://cloud.google.com/apis/design/errors).
1150 "message": "A String", # A developer-facing error message, which should be in English. Any
1151 # user-facing error message should be localized and sent in the
1152 # google.rpc.Status.details field, or localized by the client.
1153 "code": 42, # The status code, which should be an enum value of google.rpc.Code.
1154 "details": [ # A list of messages that carry the error details. There is a common set of
1155 # message types for APIs to use.
1156 {
1157 "a_key": "", # Properties of the object. Contains field @type with type URL.
1158 },
1159 ],
1160 },
1161 "done": True or False, # If the value is `false`, it means the operation is still in progress.
1162 # If `true`, the operation is completed, and either `error` or `response` is
1163 # available.
1164 "response": { # The normal response of the operation in case of success. If the original
1165 # method returns no data on success, such as `Delete`, the response is
1166 # `google.protobuf.Empty`. If the original method is standard
1167 # `Get`/`Create`/`Update`, the response should be the resource. For other
1168 # methods, the response should have the type `XxxResponse`, where `Xxx`
1169 # is the original method name. For example, if the original method name
1170 # is `TakeSnapshot()`, the inferred response type is
1171 # `TakeSnapshotResponse`.
1172 "a_key": "", # Properties of the object. Contains field @type with type URL.
1173 },
1174 "name": "A String", # The server-assigned name, which is only unique within the same service that
1175 # originally returns it. If you use the default HTTP mapping, the
1176 # `name` should be a resource name ending with `operations/{unique_id}`.
1177 }</pre>
1178</div>
1179
1180<div class="method">
1181 <code class="details" id="setDefault">setDefault(name, body=None, x__xgafv=None)</code>
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]1182 <pre>Designates a version to be the default for the model.
1183
1184The default version is used for prediction requests made against the model
1185that don't specify a version.
1186
1187The first version to be created for a model is automatically set as the
1188default. You must make any subsequent changes to the default version
1189setting manually using this method.
1190
1191Args:
1192 name: string, Required. The name of the version to make the default for the model. You
1193can get the names of all the versions of a model by calling
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]1194[projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list). (required)
1195 body: object, The request body.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]1196 The object takes the form of:
1197
1198{ # Request message for the SetDefaultVersion request.
1199 }
1200
1201 x__xgafv: string, V1 error format.
1202 Allowed values
1203 1 - v1 error format
1204 2 - v2 error format
1205
1206Returns:
1207 An object of the form:
1208
1209 { # Represents a version of the model.
1210 #
1211 # Each version is a trained model deployed in the cloud, ready to handle
1212 # prediction requests. A model can have multiple versions. You can get
1213 # information about all of the versions of a given model by calling
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]1214 # [projects.models.versions.list](/ml-engine/reference/rest/v1/projects.models.versions/list).
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]1215 "errorMessage": "A String", # Output only. The details of a failure or a cancellation.
1216 "labels": { # Optional. One or more labels that you can add, to organize your model
1217 # versions. Each label is a key-value pair, where both the key and the value
1218 # are arbitrary strings that you supply.
1219 # For more information, see the documentation on
1220 # <a href="/ml-engine/docs/tensorflow/resource-labels">using labels</a>.
1221 "a_key": "A String",
1222 },
1223 "machineType": "A String", # Optional. The type of machine on which to serve the model. Currently only
1224 # applies to online prediction service.
1225 # <dl>
1226 # <dt>mls1-c1-m2</dt>
1227 # <dd>
1228 # The <b>default</b> machine type, with 1 core and 2 GB RAM. The deprecated
1229 # name for this machine type is "mls1-highmem-1".
1230 # </dd>
1231 # <dt>mls1-c4-m2</dt>
1232 # <dd>
1233 # In <b>Beta</b>. This machine type has 4 cores and 2 GB RAM. The
1234 # deprecated name for this machine type is "mls1-highcpu-4".
1235 # </dd>
1236 # </dl>
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]1237 "description": "A String", # Optional. The description specified for the version when it was created.
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]1238 "runtimeVersion": "A String", # Optional. The AI Platform runtime version to use for this deployment.
1239 # If not set, AI Platform uses the default stable version, 1.0. For more
1240 # information, see the
1241 # [runtime version list](/ml-engine/docs/runtime-version-list) and
1242 # [how to manage runtime versions](/ml-engine/docs/versioning).
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]1243 "manualScaling": { # Options for manually scaling a model. # Manually select the number of nodes to use for serving the
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]1244 # model. You should generally use `auto_scaling` with an appropriate
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]1245 # `min_nodes` instead, but this option is available if you want more
1246 # predictable billing. Beware that latency and error rates will increase
1247 # if the traffic exceeds that capability of the system to serve it based
1248 # on the selected number of nodes.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]1249 "nodes": 42, # The number of nodes to allocate for this model. These nodes are always up,
1250 # starting from the time the model is deployed, so the cost of operating
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]1251 # this model will be proportional to `nodes` * number of hours since
1252 # last billing cycle plus the cost for each prediction performed.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]1253 },
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]1254 "predictionClass": "A String", # Optional. The fully qualified name
1255 # (<var>module_name</var>.<var>class_name</var>) of a class that implements
1256 # the Predictor interface described in this reference field. The module
1257 # containing this class should be included in a package provided to the
1258 # [`packageUris` field](#Version.FIELDS.package_uris).
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]1259 #
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]1260 # Specify this field if and only if you are deploying a [custom prediction
1261 # routine (beta)](/ml-engine/docs/tensorflow/custom-prediction-routines).
1262 # If you specify this field, you must set
1263 # [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
1264 #
1265 # The following code sample provides the Predictor interface:
1266 #
1267 # ```py
1268 # class Predictor(object):
1269 # """Interface for constructing custom predictors."""
1270 #
1271 # def predict(self, instances, **kwargs):
1272 # """Performs custom prediction.
1273 #
1274 # Instances are the decoded values from the request. They have already
1275 # been deserialized from JSON.
1276 #
1277 # Args:
1278 # instances: A list of prediction input instances.
1279 # **kwargs: A dictionary of keyword args provided as additional
1280 # fields on the predict request body.
1281 #
1282 # Returns:
1283 # A list of outputs containing the prediction results. This list must
1284 # be JSON serializable.
1285 # """
1286 # raise NotImplementedError()
1287 #
1288 # @classmethod
1289 # def from_path(cls, model_dir):
1290 # """Creates an instance of Predictor using the given path.
1291 #
1292 # Loading of the predictor should be done in this method.
1293 #
1294 # Args:
1295 # model_dir: The local directory that contains the exported model
1296 # file along with any additional files uploaded when creating the
1297 # version resource.
1298 #
1299 # Returns:
1300 # An instance implementing this Predictor class.
1301 # """
1302 # raise NotImplementedError()
1303 # ```
1304 #
1305 # Learn more about [the Predictor interface and custom prediction
1306 # routines](/ml-engine/docs/tensorflow/custom-prediction-routines).
1307 "autoScaling": { # Options for automatically scaling a model. # Automatically scale the number of nodes used to serve the model in
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]1308 # response to increases and decreases in traffic. Care should be
1309 # taken to ramp up traffic according to the model's ability to scale
1310 # or you will start seeing increases in latency and 429 response codes.
1311 "minNodes": 42, # Optional. The minimum number of nodes to allocate for this model. These
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]1312 # nodes are always up, starting from the time the model is deployed.
1313 # Therefore, the cost of operating this model will be at least
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]1314 # `rate` * `min_nodes` * number of hours since last billing cycle,
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]1315 # where `rate` is the cost per node-hour as documented in the
1316 # [pricing guide](/ml-engine/docs/pricing),
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]1317 # even if no predictions are performed. There is additional cost for each
1318 # prediction performed.
1319 #
1320 # Unlike manual scaling, if the load gets too heavy for the nodes
1321 # that are up, the service will automatically add nodes to handle the
1322 # increased load as well as scale back as traffic drops, always maintaining
1323 # at least `min_nodes`. You will be charged for the time in which additional
1324 # nodes are used.
1325 #
1326 # If not specified, `min_nodes` defaults to 0, in which case, when traffic
1327 # to a model stops (and after a cool-down period), nodes will be shut down
1328 # and no charges will be incurred until traffic to the model resumes.
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]1329 #
1330 # You can set `min_nodes` when creating the model version, and you can also
1331 # update `min_nodes` for an existing version:
1332 # <pre>
1333 # update_body.json:
1334 # {
1335 # 'autoScaling': {
1336 # 'minNodes': 5
1337 # }
1338 # }
1339 # </pre>
1340 # HTTP request:
1341 # <pre>
1342 # PATCH
1343 # https://ml.googleapis.com/v1/{name=projects/*/models/*/versions/*}?update_mask=autoScaling.minNodes
1344 # -d @./update_body.json
1345 # </pre>
Sai Cheemalapati4ba8c232017-06-06 18:46:08 -0400[diff] [blame]1346 },
Bu Sun Kim715bd7f2019-06-14 16:50:42 -0700[diff] [blame^]1347 "serviceAccount": "A String", # Optional. Specifies the service account for resource access control.
1348 "state": "A String", # Output only. The state of a version.
1349 "pythonVersion": "A String", # Optional. The version of Python used in prediction. If not set, the default
1350 # version is '2.7'. Python '3.5' is available when `runtime_version` is set
1351 # to '1.4' and above. Python '2.7' works with all supported runtime versions.
1352 "framework": "A String", # Optional. The machine learning framework AI Platform uses to train
1353 # this version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`,
1354 # `XGBOOST`. If you do not specify a framework, AI Platform
1355 # will analyze files in the deployment_uri to determine a framework. If you
1356 # choose `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version
1357 # of the model to 1.4 or greater.
1358 #
1359 # Do **not** specify a framework if you're deploying a [custom
1360 # prediction routine](/ml-engine/docs/tensorflow/custom-prediction-routines).
1361 "packageUris": [ # Optional. Cloud Storage paths (`gs://…`) of packages for [custom
1362 # prediction routines](/ml-engine/docs/tensorflow/custom-prediction-routines)
1363 # or [scikit-learn pipelines with custom
1364 # code](/ml-engine/docs/scikit/exporting-for-prediction#custom-pipeline-code).
1365 #
1366 # For a custom prediction routine, one of these packages must contain your
1367 # Predictor class (see
1368 # [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally,
1369 # include any dependencies used by your Predictor or scikit-learn pipeline
1370 # uses that are not already included in your selected [runtime
1371 # version](/ml-engine/docs/tensorflow/runtime-version-list).
1372 #
1373 # If you specify this field, you must also set
1374 # [`runtimeVersion`](#Version.FIELDS.runtime_version) to 1.4 or greater.
1375 "A String",
1376 ],
1377 "etag": "A String", # `etag` is used for optimistic concurrency control as a way to help
1378 # prevent simultaneous updates of a model from overwriting each other.
1379 # It is strongly suggested that systems make use of the `etag` in the
1380 # read-modify-write cycle to perform model updates in order to avoid race
1381 # conditions: An `etag` is returned in the response to `GetVersion`, and
1382 # systems are expected to put that etag in the request to `UpdateVersion` to
1383 # ensure that their change will be applied to the model as intended.
1384 "lastUseTime": "A String", # Output only. The time the version was last used for prediction.
1385 "deploymentUri": "A String", # Required. The Cloud Storage location of the trained model used to
1386 # create the version. See the
1387 # [guide to model
1388 # deployment](/ml-engine/docs/tensorflow/deploying-models) for more
1389 # information.
1390 #
1391 # When passing Version to
1392 # [projects.models.versions.create](/ml-engine/reference/rest/v1/projects.models.versions/create)
1393 # the model service uses the specified location as the source of the model.
1394 # Once deployed, the model version is hosted by the prediction service, so
1395 # this location is useful only as a historical record.
1396 # The total number of model files can't exceed 1000.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]1397 "createTime": "A String", # Output only. The time the version was created.
1398 "isDefault": True or False, # Output only. If true, this version will be used to handle prediction
1399 # requests that do not specify a version.
1400 #
1401 # You can change the default version by calling
Sai Cheemalapatie833b792017-03-24 15:06:46 -0700[diff] [blame]1402 # [projects.methods.versions.setDefault](/ml-engine/reference/rest/v1/projects.models.versions/setDefault).
Thomas Coffee2f245372017-03-27 10:39:26 -0700[diff] [blame]1403 "name": "A String", # Required.The name specified for the version when it was created.
1404 #
1405 # The version name must be unique within the model it is created in.
Sai Cheemalapatic30d2b52017-03-13 12:12:03 -0400[diff] [blame]1406 }</pre>
1407</div>
1408
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