Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::DeployedModel (v0.46.0)

Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::DeployedModel.

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

Inherits

Object

Extended By

Google::Protobuf::MessageExts::ClassMethods

Includes

Google::Protobuf::MessageExts

Methods

#automatic_resources

def automatic_resources() -> ::Google::Cloud::AIPlatform::V1::AutomaticResources

Returns

(::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.

#automatic_resources=

def automatic_resources=(value) -> ::Google::Cloud::AIPlatform::V1::AutomaticResources

Parameter

value (::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.

Returns

(::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.

#create_time

def create_time() -> ::Google::Protobuf::Timestamp

Returns

(::Google::Protobuf::Timestamp) — Output only. Timestamp when the DeployedModel was created.

#dedicated_resources

def dedicated_resources() -> ::Google::Cloud::AIPlatform::V1::DedicatedResources

Returns

(::Google::Cloud::AIPlatform::V1::DedicatedResources) — A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.

#dedicated_resources=

def dedicated_resources=(value) -> ::Google::Cloud::AIPlatform::V1::DedicatedResources

Parameter

value (::Google::Cloud::AIPlatform::V1::DedicatedResources) — A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.

Returns

(::Google::Cloud::AIPlatform::V1::DedicatedResources) — A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.

#disable_container_logging

def disable_container_logging() -> ::Boolean

Returns

(::Boolean) — 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.

#disable_container_logging=

def disable_container_logging=(value) -> ::Boolean

Parameter

value (::Boolean) — 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

(::Boolean) — 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.

#disable_explanations

def disable_explanations() -> ::Boolean

Returns

(::Boolean) — If true, deploy the model without explainable feature, regardless the existence of Model.explanation_spec or explanation_spec.

#disable_explanations=

def disable_explanations=(value) -> ::Boolean

Parameter

value (::Boolean) — If true, deploy the model without explainable feature, regardless the existence of Model.explanation_spec or explanation_spec.

Returns

(::Boolean) — If true, deploy the model without explainable feature, regardless the existence of Model.explanation_spec or explanation_spec.

#display_name

def display_name() -> ::String

Returns

(::String) — The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.

#display_name=

def display_name=(value) -> ::String

Parameter

value (::String) — The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.

Returns

(::String) — The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.

#enable_access_logging

def enable_access_logging() -> ::Boolean

Returns

(::Boolean) — 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.

#enable_access_logging=

def enable_access_logging=(value) -> ::Boolean

Parameter

value (::Boolean) — 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

(::Boolean) — 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.

#explanation_spec

def explanation_spec() -> ::Google::Cloud::AIPlatform::V1::ExplanationSpec

Returns

(::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.

#explanation_spec=

def explanation_spec=(value) -> ::Google::Cloud::AIPlatform::V1::ExplanationSpec

Parameter

value (::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.

Returns

(::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.

#id

def id() -> ::String

Returns

(::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]/.

#id=

def id=(value) -> ::String

Parameter

value (::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]/.

Returns

(::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

def model() -> ::String

Returns

(::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=

def model=(value) -> ::String

Parameter

value (::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.

Returns

(::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

def model_version_id() -> ::String

Returns

(::String) — Output only. The version ID of the model that is deployed.

#private_endpoints

def private_endpoints() -> ::Google::Cloud::AIPlatform::V1::PrivateEndpoints

Returns

(::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.

#service_account

def service_account() -> ::String

Returns

(::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.

#service_account=

def service_account=(value) -> ::String

Parameter

value (::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.

Returns

(::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.

#shared_resources

def shared_resources() -> ::String

Returns

(::String) — The resource name of the shared DeploymentResourcePool to deploy on. Format: projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}

#shared_resources=

def shared_resources=(value) -> ::String

Parameter

value (::String) — The resource name of the shared DeploymentResourcePool to deploy on. Format: projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}

Returns

(::String) — The resource name of the shared DeploymentResourcePool to deploy on. Format: projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}