📄 Source: GoogleCloudMlV1Version.php
<?php
/*
* Copyright 2014 Google Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License"); you may not
* use this file except in compliance with the License. You may obtain a copy of
* the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations under
* the License.
*/
namespace Google\Service\CloudMachineLearningEngine;
class GoogleCloudMlV1Version extends \Google\Collection
{
/**
* Unspecified framework. Assigns a value based on the file suffix.
*/
public const FRAMEWORK_FRAMEWORK_UNSPECIFIED = 'FRAMEWORK_UNSPECIFIED';
/**
* Tensorflow framework.
*/
public const FRAMEWORK_TENSORFLOW = 'TENSORFLOW';
/**
* Scikit-learn framework.
*/
public const FRAMEWORK_SCIKIT_LEARN = 'SCIKIT_LEARN';
/**
* XGBoost framework.
*/
public const FRAMEWORK_XGBOOST = 'XGBOOST';
/**
* The version state is unspecified.
*/
public const STATE_UNKNOWN = 'UNKNOWN';
/**
* The version is ready for prediction.
*/
public const STATE_READY = 'READY';
/**
* The version is being created. New UpdateVersion and DeleteVersion requests
* will fail if a version is in the CREATING state.
*/
public const STATE_CREATING = 'CREATING';
/**
* The version failed to be created, possibly cancelled. `error_message`
* should contain the details of the failure.
*/
public const STATE_FAILED = 'FAILED';
/**
* The version is being deleted. New UpdateVersion and DeleteVersion requests
* will fail if a version is in the DELETING state.
*/
public const STATE_DELETING = 'DELETING';
/**
* The version is being updated. New UpdateVersion and DeleteVersion requests
* will fail if a version is in the UPDATING state.
*/
public const STATE_UPDATING = 'UPDATING';
protected $collection_key = 'packageUris';
protected $acceleratorConfigType = GoogleCloudMlV1AcceleratorConfig::class;
protected $acceleratorConfigDataType = '';
protected $autoScalingType = GoogleCloudMlV1AutoScaling::class;
protected $autoScalingDataType = '';
protected $containerType = GoogleCloudMlV1ContainerSpec::class;
protected $containerDataType = '';
/**
* Output only. The time the version was created.
*
* @var string
*/
public $createTime;
/**
* The Cloud Storage URI of a directory containing trained model artifacts to
* be used to create the model version. See the [guide to deploying
* models](/ai-platform/prediction/docs/deploying-models) for more
* information. The total number of files under this directory must not exceed
* 1000. During projects.models.versions.create, AI Platform Prediction copies
* all files from the specified directory to a location managed by the
* service. From then on, AI Platform Prediction uses these copies of the
* model artifacts to serve predictions, not the original files in Cloud
* Storage, so this location is useful only as a historical record. If you
* specify container, then this field is optional. Otherwise, it is required.
* Learn [how to use this field with a custom container](/ai-
* platform/prediction/docs/custom-container-requirements#artifacts).
*
* @var string
*/
public $deploymentUri;
/**
* Optional. The description specified for the version when it was created.
*
* @var string
*/
public $description;
/**
* Output only. The details of a failure or a cancellation.
*
* @var string
*/
public $errorMessage;
/**
* `etag` is used for optimistic concurrency control as a way to help prevent
* simultaneous updates of a model from overwriting each other. It is strongly
* suggested that systems make use of the `etag` in the read-modify-write
* cycle to perform model updates in order to avoid race conditions: An `etag`
* is returned in the response to `GetVersion`, and systems are expected to
* put that etag in the request to `UpdateVersion` to ensure that their change
* will be applied to the model as intended.
*
* @var string
*/
public $etag;
protected $explanationConfigType = GoogleCloudMlV1ExplanationConfig::class;
protected $explanationConfigDataType = '';
/**
* Optional. The machine learning framework AI Platform uses to train this
* version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`,
* `XGBOOST`. If you do not specify a framework, AI Platform will analyze
* files in the deployment_uri to determine a framework. If you choose
* `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version of the
* model to 1.4 or greater. Do **not** specify a framework if you're deploying
* a [custom prediction routine](/ai-platform/prediction/docs/custom-
* prediction-routines) or if you're using a [custom container](/ai-
* platform/prediction/docs/use-custom-container).
*
* @var string
*/
public $framework;
/**
* Output only. If true, this version will be used to handle prediction
* requests that do not specify a version. You can change the default version
* by calling projects.methods.versions.setDefault.
*
* @var bool
*/
public $isDefault;
/**
* Optional. One or more labels that you can add, to organize your model
* versions. Each label is a key-value pair, where both the key and the value
* are arbitrary strings that you supply. For more information, see the
* documentation on using labels. Note that this field is not updatable for
* mls1* models.
*
* @var string[]
*/
public $labels;
/**
* Output only. The [AI Platform (Unified)
* `Model`](https://cloud.google.com/ai-platform-
* unified/docs/reference/rest/v1beta1/projects.locations.models) ID for the
* last [model migration](https://cloud.google.com/ai-platform-
* unified/docs/start/migrating-to-ai-platform-unified).
*
* @var string
*/
public $lastMigrationModelId;
/**
* Output only. The last time this version was successfully [migrated to AI
* Platform (Unified)](https://cloud.google.com/ai-platform-
* unified/docs/start/migrating-to-ai-platform-unified).
*
* @var string
*/
public $lastMigrationTime;
/**
* Output only. The time the version was last used for prediction.
*
* @var string
*/
public $lastUseTime;
/**
* Optional. The type of machine on which to serve the model. Currently only
* applies to online prediction service. To learn about valid values for this
* field, read [Choosing a machine type for online prediction](/ai-
* platform/prediction/docs/machine-types-online-prediction). If this field is
* not specified and you are using a [regional endpoint](/ai-
* platform/prediction/docs/regional-endpoints), then the machine type
* defaults to `n1-standard-2`. If this field is not specified and you are
* using the global endpoint (`ml.googleapis.com`), then the machine type
* defaults to `mls1-c1-m2`.
*
* @var string
*/
public $machineType;
protected $manualScalingType = GoogleCloudMlV1ManualScaling::class;
protected $manualScalingDataType = '';
/**
* Required. The name specified for the version when it was created. The
* version name must be unique within the model it is created in.
*
* @var string
*/
public $name;
/**
* Optional. Cloud Storage paths (`gs://…`) of packages for [custom prediction
* routines](/ml-engine/docs/tensorflow/custom-prediction-routines) or
* [scikit-learn pipelines with custom code](/ml-engine/docs/scikit/exporting-
* for-prediction#custom-pipeline-code). For a custom prediction routine, one
* of these packages must contain your Predictor class (see
* [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally,
* include any dependencies used by your Predictor or scikit-learn pipeline
* uses that are not already included in your selected [runtime version](/ml-
* engine/docs/tensorflow/runtime-version-list). If you specify this field,
* you must also set [`runtimeVersion`](#Version.FIELDS.runtime_version) to
* 1.4 or greater.
*
* @var string[]
*/
public $packageUris;
/**
* Optional. The fully qualified name (module_name.class_name) of a class that
* implements the Predictor interface described in this reference field. The
* module containing this class should be included in a package provided to
* the [`packageUris` field](#Version.FIELDS.package_uris). Specify this field
* if and only if you are deploying a [custom prediction routine (beta)](/ml-
* engine/docs/tensorflow/custom-prediction-routines). If you specify this
* field, you must set [`runtimeVersion`](#Version.FIELDS.runtime_version) to
* 1.4 or greater and you must set `machineType` to a [legacy (MLS1) machine
* type](/ml-engine/docs/machine-types-online-prediction). The following code
* sample provides the Predictor interface: class Predictor(object): Interface
* for constructing custom predictors. def predict(self, instances, **kwargs):
* Performs custom prediction. Instances are the decoded values from the
* request. They have already been deserialized from JSON. Args: instances: A
* list of prediction input instances. **kwargs: A dictionary of keyword args
* provided as additional fields on the predict request body. Returns: A list
* of outputs containing the prediction results. This list must be JSON
* serializable. raise NotImplementedError() @classmethod def from_path(cls,
* model_dir): Creates an instance of Predictor using the given path. Loading
* of the predictor should be done in this method. Args: model_dir: The local
* directory that contains the exported model file along with any additional
* files uploaded when creating the version resource. Returns: An instance
* implementing this Predictor class. raise NotImplementedError() Learn more
* about [the Predictor interface and custom prediction routines](/ml-
* engine/docs/tensorflow/custom-prediction-routines).
*
* @var string
*/
public $predictionClass;
/**
* Required. The version of Python used in prediction. The following Python
* versions are available: * Python '3.7' is available when `runtime_version`
* is set to '1.15' or later. * Python '3.5' is available when
* `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7'
* is available when `runtime_version` is set to '1.15' or earlier. Read more
* about the Python versions available for [each runtime version](/ml-
* engine/docs/runtime-version-list).
*
* @var string
*/
public $pythonVersion;
protected $requestLoggingConfigType = GoogleCloudMlV1RequestLoggingConfig::class;
protected $requestLoggingConfigDataType = '';
protected $routesType = GoogleCloudMlV1RouteMap::class;
protected $routesDataType = '';
/**
* Required. The AI Platform runtime version to use for this deployment. For
* more information, see the [runtime version list](/ml-engine/docs/runtime-
* version-list) and [how to manage runtime versions](/ml-
* engine/docs/versioning).
*
* @var string
*/
public $runtimeVersion;
/**
* Optional. Specifies the service account for resource access control. If you
* specify this field, then you must also specify either the `containerSpec`
* or the `predictionClass` field. Learn more about [using a custom service
* account](/ai-platform/prediction/docs/custom-service-account).
*
* @var string
*/
public $serviceAccount;
/**
* Output only. The state of a version.
*
* @var string
*/
public $state;
/**
* Optional. Accelerator config for using GPUs for online prediction (beta).
* Only specify this field if you have specified a Compute Engine (N1) machine
* type in the `machineType` field. Learn more about [using GPUs for online
* prediction](/ml-engine/docs/machine-types-online-prediction#gpus).
*
* @param GoogleCloudMlV1AcceleratorConfig $acceleratorConfig
*/
public function setAcceleratorConfig(GoogleCloudMlV1AcceleratorConfig $acceleratorConfig)
{
$this->acceleratorConfig = $acceleratorConfig;
}
/**
* @return GoogleCloudMlV1AcceleratorConfig
*/
public function getAcceleratorConfig()
{
return $this->acceleratorConfig;
}
/**
* Automatically scale the number of nodes used to serve the model in response
* to increases and decreases in traffic. Care should be taken to ramp up
* traffic according to the model's ability to scale or you will start seeing
* increases in latency and 429 response codes.
*
* @param GoogleCloudMlV1AutoScaling $autoScaling
*/
public function setAutoScaling(GoogleCloudMlV1AutoScaling $autoScaling)
{
$this->autoScaling = $autoScaling;
}
/**
* @return GoogleCloudMlV1AutoScaling
*/
public function getAutoScaling()
{
return $this->autoScaling;
}
/**
* Optional. Specifies a custom container to use for serving predictions. If
* you specify this field, then `machineType` is required. If you specify this
* field, then `deploymentUri` is optional. If you specify this field, then
* you must not specify `runtimeVersion`, `packageUris`, `framework`,
* `pythonVersion`, or `predictionClass`.
*
* @param GoogleCloudMlV1ContainerSpec $container
*/
public function setContainer(GoogleCloudMlV1ContainerSpec $container)
{
$this->container = $container;
}
/**
* @return GoogleCloudMlV1ContainerSpec
*/
public function getContainer()
{
return $this->container;
}
/**
* Output only. The time the version was created.
*
* @param string $createTime
*/
public function setCreateTime($createTime)
{
$this->createTime = $createTime;
}
/**
* @return string
*/
public function getCreateTime()
{
return $this->createTime;
}
/**
* The Cloud Storage URI of a directory containing trained model artifacts to
* be used to create the model version. See the [guide to deploying
* models](/ai-platform/prediction/docs/deploying-models) for more
* information. The total number of files under this directory must not exceed
* 1000. During projects.models.versions.create, AI Platform Prediction copies
* all files from the specified directory to a location managed by the
* service. From then on, AI Platform Prediction uses these copies of the
* model artifacts to serve predictions, not the original files in Cloud
* Storage, so this location is useful only as a historical record. If you
* specify container, then this field is optional. Otherwise, it is required.
* Learn [how to use this field with a custom container](/ai-
* platform/prediction/docs/custom-container-requirements#artifacts).
*
* @param string $deploymentUri
*/
public function setDeploymentUri($deploymentUri)
{
$this->deploymentUri = $deploymentUri;
}
/**
* @return string
*/
public function getDeploymentUri()
{
return $this->deploymentUri;
}
/**
* Optional. The description specified for the version when it was created.
*
* @param string $description
*/
public function setDescription($description)
{
$this->description = $description;
}
/**
* @return string
*/
public function getDescription()
{
return $this->description;
}
/**
* Output only. The details of a failure or a cancellation.
*
* @param string $errorMessage
*/
public function setErrorMessage($errorMessage)
{
$this->errorMessage = $errorMessage;
}
/**
* @return string
*/
public function getErrorMessage()
{
return $this->errorMessage;
}
/**
* `etag` is used for optimistic concurrency control as a way to help prevent
* simultaneous updates of a model from overwriting each other. It is strongly
* suggested that systems make use of the `etag` in the read-modify-write
* cycle to perform model updates in order to avoid race conditions: An `etag`
* is returned in the response to `GetVersion`, and systems are expected to
* put that etag in the request to `UpdateVersion` to ensure that their change
* will be applied to the model as intended.
*
* @param string $etag
*/
public function setEtag($etag)
{
$this->etag = $etag;
}
/**
* @return string
*/
public function getEtag()
{
return $this->etag;
}
/**
* Optional. Configures explainability features on the model's version. Some
* explanation features require additional metadata to be loaded as part of
* the model payload.
*
* @param GoogleCloudMlV1ExplanationConfig $explanationConfig
*/
public function setExplanationConfig(GoogleCloudMlV1ExplanationConfig $explanationConfig)
{
$this->explanationConfig = $explanationConfig;
}
/**
* @return GoogleCloudMlV1ExplanationConfig
*/
public function getExplanationConfig()
{
return $this->explanationConfig;
}
/**
* Optional. The machine learning framework AI Platform uses to train this
* version of the model. Valid values are `TENSORFLOW`, `SCIKIT_LEARN`,
* `XGBOOST`. If you do not specify a framework, AI Platform will analyze
* files in the deployment_uri to determine a framework. If you choose
* `SCIKIT_LEARN` or `XGBOOST`, you must also set the runtime version of the
* model to 1.4 or greater. Do **not** specify a framework if you're deploying
* a [custom prediction routine](/ai-platform/prediction/docs/custom-
* prediction-routines) or if you're using a [custom container](/ai-
* platform/prediction/docs/use-custom-container).
*
* Accepted values: FRAMEWORK_UNSPECIFIED, TENSORFLOW, SCIKIT_LEARN, XGBOOST
*
* @param self::FRAMEWORK_* $framework
*/
public function setFramework($framework)
{
$this->framework = $framework;
}
/**
* @return self::FRAMEWORK_*
*/
public function getFramework()
{
return $this->framework;
}
/**
* Output only. If true, this version will be used to handle prediction
* requests that do not specify a version. You can change the default version
* by calling projects.methods.versions.setDefault.
*
* @param bool $isDefault
*/
public function setIsDefault($isDefault)
{
$this->isDefault = $isDefault;
}
/**
* @return bool
*/
public function getIsDefault()
{
return $this->isDefault;
}
/**
* Optional. One or more labels that you can add, to organize your model
* versions. Each label is a key-value pair, where both the key and the value
* are arbitrary strings that you supply. For more information, see the
* documentation on using labels. Note that this field is not updatable for
* mls1* models.
*
* @param string[] $labels
*/
public function setLabels($labels)
{
$this->labels = $labels;
}
/**
* @return string[]
*/
public function getLabels()
{
return $this->labels;
}
/**
* Output only. The [AI Platform (Unified)
* `Model`](https://cloud.google.com/ai-platform-
* unified/docs/reference/rest/v1beta1/projects.locations.models) ID for the
* last [model migration](https://cloud.google.com/ai-platform-
* unified/docs/start/migrating-to-ai-platform-unified).
*
* @param string $lastMigrationModelId
*/
public function setLastMigrationModelId($lastMigrationModelId)
{
$this->lastMigrationModelId = $lastMigrationModelId;
}
/**
* @return string
*/
public function getLastMigrationModelId()
{
return $this->lastMigrationModelId;
}
/**
* Output only. The last time this version was successfully [migrated to AI
* Platform (Unified)](https://cloud.google.com/ai-platform-
* unified/docs/start/migrating-to-ai-platform-unified).
*
* @param string $lastMigrationTime
*/
public function setLastMigrationTime($lastMigrationTime)
{
$this->lastMigrationTime = $lastMigrationTime;
}
/**
* @return string
*/
public function getLastMigrationTime()
{
return $this->lastMigrationTime;
}
/**
* Output only. The time the version was last used for prediction.
*
* @param string $lastUseTime
*/
public function setLastUseTime($lastUseTime)
{
$this->lastUseTime = $lastUseTime;
}
/**
* @return string
*/
public function getLastUseTime()
{
return $this->lastUseTime;
}
/**
* Optional. The type of machine on which to serve the model. Currently only
* applies to online prediction service. To learn about valid values for this
* field, read [Choosing a machine type for online prediction](/ai-
* platform/prediction/docs/machine-types-online-prediction). If this field is
* not specified and you are using a [regional endpoint](/ai-
* platform/prediction/docs/regional-endpoints), then the machine type
* defaults to `n1-standard-2`. If this field is not specified and you are
* using the global endpoint (`ml.googleapis.com`), then the machine type
* defaults to `mls1-c1-m2`.
*
* @param string $machineType
*/
public function setMachineType($machineType)
{
$this->machineType = $machineType;
}
/**
* @return string
*/
public function getMachineType()
{
return $this->machineType;
}
/**
* Manually select the number of nodes to use for serving the model. You
* should generally use `auto_scaling` with an appropriate `min_nodes`
* instead, but this option is available if you want more predictable billing.
* Beware that latency and error rates will increase if the traffic exceeds
* that capability of the system to serve it based on the selected number of
* nodes.
*
* @param GoogleCloudMlV1ManualScaling $manualScaling
*/
public function setManualScaling(GoogleCloudMlV1ManualScaling $manualScaling)
{
$this->manualScaling = $manualScaling;
}
/**
* @return GoogleCloudMlV1ManualScaling
*/
public function getManualScaling()
{
return $this->manualScaling;
}
/**
* Required. The name specified for the version when it was created. The
* version name must be unique within the model it is created in.
*
* @param string $name
*/
public function setName($name)
{
$this->name = $name;
}
/**
* @return string
*/
public function getName()
{
return $this->name;
}
/**
* Optional. Cloud Storage paths (`gs://…`) of packages for [custom prediction
* routines](/ml-engine/docs/tensorflow/custom-prediction-routines) or
* [scikit-learn pipelines with custom code](/ml-engine/docs/scikit/exporting-
* for-prediction#custom-pipeline-code). For a custom prediction routine, one
* of these packages must contain your Predictor class (see
* [`predictionClass`](#Version.FIELDS.prediction_class)). Additionally,
* include any dependencies used by your Predictor or scikit-learn pipeline
* uses that are not already included in your selected [runtime version](/ml-
* engine/docs/tensorflow/runtime-version-list). If you specify this field,
* you must also set [`runtimeVersion`](#Version.FIELDS.runtime_version) to
* 1.4 or greater.
*
* @param string[] $packageUris
*/
public function setPackageUris($packageUris)
{
$this->packageUris = $packageUris;
}
/**
* @return string[]
*/
public function getPackageUris()
{
return $this->packageUris;
}
/**
* Optional. The fully qualified name (module_name.class_name) of a class that
* implements the Predictor interface described in this reference field. The
* module containing this class should be included in a package provided to
* the [`packageUris` field](#Version.FIELDS.package_uris). Specify this field
* if and only if you are deploying a [custom prediction routine (beta)](/ml-
* engine/docs/tensorflow/custom-prediction-routines). If you specify this
* field, you must set [`runtimeVersion`](#Version.FIELDS.runtime_version) to
* 1.4 or greater and you must set `machineType` to a [legacy (MLS1) machine
* type](/ml-engine/docs/machine-types-online-prediction). The following code
* sample provides the Predictor interface: class Predictor(object): Interface
* for constructing custom predictors. def predict(self, instances, **kwargs):
* Performs custom prediction. Instances are the decoded values from the
* request. They have already been deserialized from JSON. Args: instances: A
* list of prediction input instances. **kwargs: A dictionary of keyword args
* provided as additional fields on the predict request body. Returns: A list
* of outputs containing the prediction results. This list must be JSON
* serializable. raise NotImplementedError() @classmethod def from_path(cls,
* model_dir): Creates an instance of Predictor using the given path. Loading
* of the predictor should be done in this method. Args: model_dir: The local
* directory that contains the exported model file along with any additional
* files uploaded when creating the version resource. Returns: An instance
* implementing this Predictor class. raise NotImplementedError() Learn more
* about [the Predictor interface and custom prediction routines](/ml-
* engine/docs/tensorflow/custom-prediction-routines).
*
* @param string $predictionClass
*/
public function setPredictionClass($predictionClass)
{
$this->predictionClass = $predictionClass;
}
/**
* @return string
*/
public function getPredictionClass()
{
return $this->predictionClass;
}
/**
* Required. The version of Python used in prediction. The following Python
* versions are available: * Python '3.7' is available when `runtime_version`
* is set to '1.15' or later. * Python '3.5' is available when
* `runtime_version` is set to a version from '1.4' to '1.14'. * Python '2.7'
* is available when `runtime_version` is set to '1.15' or earlier. Read more
* about the Python versions available for [each runtime version](/ml-
* engine/docs/runtime-version-list).
*
* @param string $pythonVersion
*/
public function setPythonVersion($pythonVersion)
{
$this->pythonVersion = $pythonVersion;
}
/**
* @return string
*/
public function getPythonVersion()
{
return $this->pythonVersion;
}
/**
* Optional. *Only* specify this field in a projects.models.versions.patch
* request. Specifying it in a projects.models.versions.create request has no
* effect. Configures the request-response pair logging on predictions from
* this Version.
*
* @param GoogleCloudMlV1RequestLoggingConfig $requestLoggingConfig
*/
public function setRequestLoggingConfig(GoogleCloudMlV1RequestLoggingConfig $requestLoggingConfig)
{
$this->requestLoggingConfig = $requestLoggingConfig;
}
/**
* @return GoogleCloudMlV1RequestLoggingConfig
*/
public function getRequestLoggingConfig()
{
return $this->requestLoggingConfig;
}
/**
* Optional. Specifies paths on a custom container's HTTP server where AI
* Platform Prediction sends certain requests. If you specify this field, then
* you must also specify the `container` field. If you specify the `container`
* field and do not specify this field, it defaults to the following: ```json
* { "predict": "/v1/models/MODEL/versions/VERSION:predict", "health":
* "/v1/models/MODEL/versions/VERSION" } ``` See RouteMap for more details
* about these default values.
*
* @param GoogleCloudMlV1RouteMap $routes
*/
public function setRoutes(GoogleCloudMlV1RouteMap $routes)
{
$this->routes = $routes;
}
/**
* @return GoogleCloudMlV1RouteMap
*/
public function getRoutes()
{
return $this->routes;
}
/**
* Required. The AI Platform runtime version to use for this deployment. For
* more information, see the [runtime version list](/ml-engine/docs/runtime-
* version-list) and [how to manage runtime versions](/ml-
* engine/docs/versioning).
*
* @param string $runtimeVersion
*/
public function setRuntimeVersion($runtimeVersion)
{
$this->runtimeVersion = $runtimeVersion;
}
/**
* @return string
*/
public function getRuntimeVersion()
{
return $this->runtimeVersion;
}
/**
* Optional. Specifies the service account for resource access control. If you
* specify this field, then you must also specify either the `containerSpec`
* or the `predictionClass` field. Learn more about [using a custom service
* account](/ai-platform/prediction/docs/custom-service-account).
*
* @param string $serviceAccount
*/
public function setServiceAccount($serviceAccount)
{
$this->serviceAccount = $serviceAccount;
}
/**
* @return string
*/
public function getServiceAccount()
{
return $this->serviceAccount;
}
/**
* Output only. The state of a version.
*
* Accepted values: UNKNOWN, READY, CREATING, FAILED, DELETING, UPDATING
*
* @param self::STATE_* $state
*/
public function setState($state)
{
$this->state = $state;
}
/**
* @return self::STATE_*
*/
public function getState()
{
return $this->state;
}
}
// Adding a class alias for backwards compatibility with the previous class name.
class_alias(GoogleCloudMlV1Version::class, 'Google_Service_CloudMachineLearningEngine_GoogleCloudMlV1Version');
← Back