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<?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\Aiplatform;
class GoogleCloudAiplatformV1DeployedModel extends \Google\Model
{
protected $automaticResourcesType = GoogleCloudAiplatformV1AutomaticResources::class;
protected $automaticResourcesDataType = '';
/**
* The checkpoint id of the model.
*
* @var string
*/
public $checkpointId;
/**
* Output only. Timestamp when the DeployedModel was created.
*
* @var string
*/
public $createTime;
protected $dedicatedResourcesType = GoogleCloudAiplatformV1DedicatedResources::class;
protected $dedicatedResourcesDataType = '';
/**
* For custom-trained Models and AutoML Tabular Models, the container of the
* DeployedModel instances will send `stderr` and `stdout` streams to Cloud
* Logging by default. Please note that the logs incur cost, which are subject
* to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User
* can disable container logging by setting this flag to true.
*
* @var bool
*/
public $disableContainerLogging;
/**
* If true, deploy the model without explainable feature, regardless the
* existence of Model.explanation_spec or explanation_spec.
*
* @var bool
*/
public $disableExplanations;
/**
* The display name of the DeployedModel. If not provided upon creation, the
* Model's display_name is used.
*
* @var string
*/
public $displayName;
/**
* If true, online prediction access logs are sent to Cloud Logging. These
* logs are like standard server access logs, containing information like
* timestamp and latency for each prediction request. Note that logs may incur
* a cost, especially if your project receives prediction requests at a high
* queries per second rate (QPS). Estimate your costs before enabling this
* option.
*
* @var bool
*/
public $enableAccessLogging;
protected $explanationSpecType = GoogleCloudAiplatformV1ExplanationSpec::class;
protected $explanationSpecDataType = '';
protected $fasterDeploymentConfigType = GoogleCloudAiplatformV1FasterDeploymentConfig::class;
protected $fasterDeploymentConfigDataType = '';
/**
* GDC pretrained / Gemini model name. The model name is a plain model name,
* e.g. gemini-1.5-flash-002.
*
* @var string
*/
public $gdcConnectedModel;
/**
* Immutable. The ID of the DeployedModel. If not provided upon deployment,
* Vertex AI will generate a value for this ID. This value should be 1-10
* characters, and valid characters are `/[0-9]/`.
*
* @var string
*/
public $id;
/**
* The resource name of the Model that this is the deployment of. Note that
* the Model may be in a different location than the DeployedModel's Endpoint.
* The resource name may contain version id or version alias to specify the
* version. Example:
* `projects/{project}/locations/{location}/models/{model}@2` or
* `projects/{project}/locations/{location}/models/{model}@golden` if no
* version is specified, the default version will be deployed.
*
* @var string
*/
public $model;
/**
* Output only. The version ID of the model that is deployed.
*
* @var string
*/
public $modelVersionId;
protected $privateEndpointsType = GoogleCloudAiplatformV1PrivateEndpoints::class;
protected $privateEndpointsDataType = '';
/**
* The service account that the DeployedModel's container runs as. Specify the
* email address of the service account. If this service account is not
* specified, the container runs as a service account that doesn't have access
* to the resource project. Users deploying the Model must have the
* `iam.serviceAccounts.actAs` permission on this service account.
*
* @var string
*/
public $serviceAccount;
/**
* The resource name of the shared DeploymentResourcePool to deploy on.
* Format: `projects/{project}/locations/{location}/deploymentResourcePools/{d
* eployment_resource_pool}`
*
* @var string
*/
public $sharedResources;
protected $speculativeDecodingSpecType = GoogleCloudAiplatformV1SpeculativeDecodingSpec::class;
protected $speculativeDecodingSpecDataType = '';
protected $statusType = GoogleCloudAiplatformV1DeployedModelStatus::class;
protected $statusDataType = '';
/**
* System labels to apply to Model Garden deployments. System labels are
* managed by Google for internal use only.
*
* @var string[]
*/
public $systemLabels;
/**
* A description of resources that to large degree are decided by Vertex AI,
* and require only a modest additional configuration.
*
* @param GoogleCloudAiplatformV1AutomaticResources $automaticResources
*/
public function setAutomaticResources(GoogleCloudAiplatformV1AutomaticResources $automaticResources)
{
$this->automaticResources = $automaticResources;
}
/**
* @return GoogleCloudAiplatformV1AutomaticResources
*/
public function getAutomaticResources()
{
return $this->automaticResources;
}
/**
* The checkpoint id of the model.
*
* @param string $checkpointId
*/
public function setCheckpointId($checkpointId)
{
$this->checkpointId = $checkpointId;
}
/**
* @return string
*/
public function getCheckpointId()
{
return $this->checkpointId;
}
/**
* Output only. Timestamp when the DeployedModel was created.
*
* @param string $createTime
*/
public function setCreateTime($createTime)
{
$this->createTime = $createTime;
}
/**
* @return string
*/
public function getCreateTime()
{
return $this->createTime;
}
/**
* A description of resources that are dedicated to the DeployedModel, and
* that need a higher degree of manual configuration.
*
* @param GoogleCloudAiplatformV1DedicatedResources $dedicatedResources
*/
public function setDedicatedResources(GoogleCloudAiplatformV1DedicatedResources $dedicatedResources)
{
$this->dedicatedResources = $dedicatedResources;
}
/**
* @return GoogleCloudAiplatformV1DedicatedResources
*/
public function getDedicatedResources()
{
return $this->dedicatedResources;
}
/**
* For custom-trained Models and AutoML Tabular Models, the container of the
* DeployedModel instances will send `stderr` and `stdout` streams to Cloud
* Logging by default. Please note that the logs incur cost, which are subject
* to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User
* can disable container logging by setting this flag to true.
*
* @param bool $disableContainerLogging
*/
public function setDisableContainerLogging($disableContainerLogging)
{
$this->disableContainerLogging = $disableContainerLogging;
}
/**
* @return bool
*/
public function getDisableContainerLogging()
{
return $this->disableContainerLogging;
}
/**
* If true, deploy the model without explainable feature, regardless the
* existence of Model.explanation_spec or explanation_spec.
*
* @param bool $disableExplanations
*/
public function setDisableExplanations($disableExplanations)
{
$this->disableExplanations = $disableExplanations;
}
/**
* @return bool
*/
public function getDisableExplanations()
{
return $this->disableExplanations;
}
/**
* The display name of the DeployedModel. If not provided upon creation, the
* Model's display_name is used.
*
* @param string $displayName
*/
public function setDisplayName($displayName)
{
$this->displayName = $displayName;
}
/**
* @return string
*/
public function getDisplayName()
{
return $this->displayName;
}
/**
* If true, online prediction access logs are sent to Cloud Logging. These
* logs are like standard server access logs, containing information like
* timestamp and latency for each prediction request. Note that logs may incur
* a cost, especially if your project receives prediction requests at a high
* queries per second rate (QPS). Estimate your costs before enabling this
* option.
*
* @param bool $enableAccessLogging
*/
public function setEnableAccessLogging($enableAccessLogging)
{
$this->enableAccessLogging = $enableAccessLogging;
}
/**
* @return bool
*/
public function getEnableAccessLogging()
{
return $this->enableAccessLogging;
}
/**
* Explanation configuration for this DeployedModel. When deploying a Model
* using EndpointService.DeployModel, this value overrides the value of
* Model.explanation_spec. All fields of explanation_spec are optional in the
* request. If a field of explanation_spec is not populated, the value of the
* same field of Model.explanation_spec is inherited. If the corresponding
* Model.explanation_spec is not populated, all fields of the explanation_spec
* will be used for the explanation configuration.
*
* @param GoogleCloudAiplatformV1ExplanationSpec $explanationSpec
*/
public function setExplanationSpec(GoogleCloudAiplatformV1ExplanationSpec $explanationSpec)
{
$this->explanationSpec = $explanationSpec;
}
/**
* @return GoogleCloudAiplatformV1ExplanationSpec
*/
public function getExplanationSpec()
{
return $this->explanationSpec;
}
/**
* Configuration for faster model deployment.
*
* @param GoogleCloudAiplatformV1FasterDeploymentConfig $fasterDeploymentConfig
*/
public function setFasterDeploymentConfig(GoogleCloudAiplatformV1FasterDeploymentConfig $fasterDeploymentConfig)
{
$this->fasterDeploymentConfig = $fasterDeploymentConfig;
}
/**
* @return GoogleCloudAiplatformV1FasterDeploymentConfig
*/
public function getFasterDeploymentConfig()
{
return $this->fasterDeploymentConfig;
}
/**
* GDC pretrained / Gemini model name. The model name is a plain model name,
* e.g. gemini-1.5-flash-002.
*
* @param string $gdcConnectedModel
*/
public function setGdcConnectedModel($gdcConnectedModel)
{
$this->gdcConnectedModel = $gdcConnectedModel;
}
/**
* @return string
*/
public function getGdcConnectedModel()
{
return $this->gdcConnectedModel;
}
/**
* Immutable. The ID of the DeployedModel. If not provided upon deployment,
* Vertex AI will generate a value for this ID. This value should be 1-10
* characters, and valid characters are `/[0-9]/`.
*
* @param string $id
*/
public function setId($id)
{
$this->id = $id;
}
/**
* @return string
*/
public function getId()
{
return $this->id;
}
/**
* The resource name of the Model that this is the deployment of. Note that
* the Model may be in a different location than the DeployedModel's Endpoint.
* The resource name may contain version id or version alias to specify the
* version. Example:
* `projects/{project}/locations/{location}/models/{model}@2` or
* `projects/{project}/locations/{location}/models/{model}@golden` if no
* version is specified, the default version will be deployed.
*
* @param string $model
*/
public function setModel($model)
{
$this->model = $model;
}
/**
* @return string
*/
public function getModel()
{
return $this->model;
}
/**
* Output only. The version ID of the model that is deployed.
*
* @param string $modelVersionId
*/
public function setModelVersionId($modelVersionId)
{
$this->modelVersionId = $modelVersionId;
}
/**
* @return string
*/
public function getModelVersionId()
{
return $this->modelVersionId;
}
/**
* Output only. Provide paths for users to send predict/explain/health
* requests directly to the deployed model services running on Cloud via
* private services access. This field is populated if network is configured.
*
* @param GoogleCloudAiplatformV1PrivateEndpoints $privateEndpoints
*/
public function setPrivateEndpoints(GoogleCloudAiplatformV1PrivateEndpoints $privateEndpoints)
{
$this->privateEndpoints = $privateEndpoints;
}
/**
* @return GoogleCloudAiplatformV1PrivateEndpoints
*/
public function getPrivateEndpoints()
{
return $this->privateEndpoints;
}
/**
* The service account that the DeployedModel's container runs as. Specify the
* email address of the service account. If this service account is not
* specified, the container runs as a service account that doesn't have access
* to the resource project. Users deploying the Model must have the
* `iam.serviceAccounts.actAs` permission on this service account.
*
* @param string $serviceAccount
*/
public function setServiceAccount($serviceAccount)
{
$this->serviceAccount = $serviceAccount;
}
/**
* @return string
*/
public function getServiceAccount()
{
return $this->serviceAccount;
}
/**
* The resource name of the shared DeploymentResourcePool to deploy on.
* Format: `projects/{project}/locations/{location}/deploymentResourcePools/{d
* eployment_resource_pool}`
*
* @param string $sharedResources
*/
public function setSharedResources($sharedResources)
{
$this->sharedResources = $sharedResources;
}
/**
* @return string
*/
public function getSharedResources()
{
return $this->sharedResources;
}
/**
* Optional. Spec for configuring speculative decoding.
*
* @param GoogleCloudAiplatformV1SpeculativeDecodingSpec $speculativeDecodingSpec
*/
public function setSpeculativeDecodingSpec(GoogleCloudAiplatformV1SpeculativeDecodingSpec $speculativeDecodingSpec)
{
$this->speculativeDecodingSpec = $speculativeDecodingSpec;
}
/**
* @return GoogleCloudAiplatformV1SpeculativeDecodingSpec
*/
public function getSpeculativeDecodingSpec()
{
return $this->speculativeDecodingSpec;
}
/**
* Output only. Runtime status of the deployed model.
*
* @param GoogleCloudAiplatformV1DeployedModelStatus $status
*/
public function setStatus(GoogleCloudAiplatformV1DeployedModelStatus $status)
{
$this->status = $status;
}
/**
* @return GoogleCloudAiplatformV1DeployedModelStatus
*/
public function getStatus()
{
return $this->status;
}
/**
* System labels to apply to Model Garden deployments. System labels are
* managed by Google for internal use only.
*
* @param string[] $systemLabels
*/
public function setSystemLabels($systemLabels)
{
$this->systemLabels = $systemLabels;
}
/**
* @return string[]
*/
public function getSystemLabels()
{
return $this->systemLabels;
}
}
// Adding a class alias for backwards compatibility with the previous class name.
class_alias(GoogleCloudAiplatformV1DeployedModel::class, 'Google_Service_Aiplatform_GoogleCloudAiplatformV1DeployedModel');