Google Cloud Ai Platform V1 Client - Class DeployedModel (1.8.0)

Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class DeployedModel.

A deployment of a Model. Endpoints contain one or more DeployedModels.

Generated from protobuf message google.cloud.aiplatform.v1.DeployedModel

Namespace

Google \ Cloud \ AIPlatform \ V1

Methods

__construct

Constructor.

Parameters
Name Description
data array

Optional. Data for populating the Message object.
↳ dedicated_resources Google\Cloud\AIPlatform\V1\DedicatedResources

A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.
↳ automatic_resources Google\Cloud\AIPlatform\V1\AutomaticResources

A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.
↳ shared_resources string

The resource name of the shared DeploymentResourcePool to deploy on. Format: projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}
↳ id string

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]/.
↳ model string

Required. 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.
↳ model_version_id string

Output only. The version ID of the model that is deployed.
↳ display_name string

The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.
↳ create_time Google\Protobuf\Timestamp

Output only. Timestamp when the DeployedModel was created.
↳ explanation_spec Google\Cloud\AIPlatform\V1\ExplanationSpec

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.
↳ disable_explanations bool

If true, deploy the model without explainable feature, regardless the existence of Model.explanation_spec or explanation_spec.
↳ service_account string

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.
↳ disable_container_logging bool

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. User can disable container logging by setting this flag to true.
↳ enable_access_logging bool

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.
↳ private_endpoints Google\Cloud\AIPlatform\V1\PrivateEndpoints

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.

getDedicatedResources

A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.

Returns
Type Description
Google\Cloud\AIPlatform\V1\DedicatedResources|null

hasDedicatedResources

setDedicatedResources

A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.

Parameter
Name Description
var Google\Cloud\AIPlatform\V1\DedicatedResources
Returns
Type Description
$this

getAutomaticResources

A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.

Returns
Type Description
Google\Cloud\AIPlatform\V1\AutomaticResources|null

hasAutomaticResources

setAutomaticResources

A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.

Parameter
Name Description
var Google\Cloud\AIPlatform\V1\AutomaticResources
Returns
Type Description
$this

getSharedResources

The resource name of the shared DeploymentResourcePool to deploy on.

Format: projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}

Returns
Type Description
string

hasSharedResources

setSharedResources

The resource name of the shared DeploymentResourcePool to deploy on.

Format: projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}

Parameter
Name Description
var string
Returns
Type Description
$this

getId

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]/.

Returns
Type Description
string

setId

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]/.

Parameter
Name Description
var string
Returns
Type Description
$this

getModel

Required. 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.

Returns
Type Description
string

setModel

Required. 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.

Parameter
Name Description
var string
Returns
Type Description
$this

getModelVersionId

Output only. The version ID of the model that is deployed.

Returns
Type Description
string

setModelVersionId

Output only. The version ID of the model that is deployed.

Parameter
Name Description
var string
Returns
Type Description
$this

getDisplayName

The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.

Returns
Type Description
string

setDisplayName

The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.

Parameter
Name Description
var string
Returns
Type Description
$this

getCreateTime

Output only. Timestamp when the DeployedModel was created.

Returns
Type Description
Google\Protobuf\Timestamp|null

hasCreateTime

clearCreateTime

setCreateTime

Output only. Timestamp when the DeployedModel was created.

Parameter
Name Description
var Google\Protobuf\Timestamp
Returns
Type Description
$this

getExplanationSpec

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.

Returns
Type Description
Google\Cloud\AIPlatform\V1\ExplanationSpec|null

hasExplanationSpec

clearExplanationSpec

setExplanationSpec

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.

Parameter
Name Description
var Google\Cloud\AIPlatform\V1\ExplanationSpec
Returns
Type Description
$this

getDisableExplanations

If true, deploy the model without explainable feature, regardless the existence of Model.explanation_spec or explanation_spec.

Returns
Type Description
bool

setDisableExplanations

If true, deploy the model without explainable feature, regardless the existence of Model.explanation_spec or explanation_spec.

Parameter
Name Description
var bool
Returns
Type Description
$this

getServiceAccount

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.

Returns
Type Description
string

setServiceAccount

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.

Parameter
Name Description
var string
Returns
Type Description
$this

getDisableContainerLogging

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.

User can disable container logging by setting this flag to true.

Returns
Type Description
bool

setDisableContainerLogging

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.

User can disable container logging by setting this flag to true.

Parameter
Name Description
var bool
Returns
Type Description
$this

getEnableAccessLogging

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.

Returns
Type Description
bool

setEnableAccessLogging

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.

Parameter
Name Description
var bool
Returns
Type Description
$this

getPrivateEndpoints

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.

Returns
Type Description
Google\Cloud\AIPlatform\V1\PrivateEndpoints|null

hasPrivateEndpoints

clearPrivateEndpoints

setPrivateEndpoints

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.

Parameter
Name Description
var Google\Cloud\AIPlatform\V1\PrivateEndpoints
Returns
Type Description
$this

getPredictionResources

Returns
Type Description
string