Interface DeployedModelOrBuilder (3.21.0)

public interface DeployedModelOrBuilder extends MessageOrBuilder

Implements

MessageOrBuilder

Methods

getAutomaticResources()

public abstract AutomaticResources getAutomaticResources()

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

.google.cloud.aiplatform.v1.AutomaticResources automatic_resources = 8;

Returns
Type	Description
`AutomaticResources`	The automaticResources.

getAutomaticResourcesOrBuilder()

public abstract AutomaticResourcesOrBuilder getAutomaticResourcesOrBuilder()

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

.google.cloud.aiplatform.v1.AutomaticResources automatic_resources = 8;

Returns
Type	Description
`AutomaticResourcesOrBuilder`

getCreateTime()

public abstract Timestamp getCreateTime()

Output only. Timestamp when the DeployedModel was created.

.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
`Timestamp`	The createTime.

getCreateTimeOrBuilder()

public abstract TimestampOrBuilder getCreateTimeOrBuilder()

Output only. Timestamp when the DeployedModel was created.

.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
`TimestampOrBuilder`

getDedicatedResources()

public abstract DedicatedResources getDedicatedResources()

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

.google.cloud.aiplatform.v1.DedicatedResources dedicated_resources = 7;

Returns
Type	Description
`DedicatedResources`	The dedicatedResources.

getDedicatedResourcesOrBuilder()

public abstract DedicatedResourcesOrBuilder getDedicatedResourcesOrBuilder()

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

.google.cloud.aiplatform.v1.DedicatedResources dedicated_resources = 7;

Returns
Type	Description
`DedicatedResourcesOrBuilder`

getDisableContainerLogging()

public abstract boolean 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.

bool disable_container_logging = 15;

Returns
Type	Description
`boolean`	The disableContainerLogging.

getDisplayName()

public abstract String getDisplayName()

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

string display_name = 3;

Returns
Type	Description
`String`	The displayName.

getDisplayNameBytes()

public abstract ByteString getDisplayNameBytes()

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

string display_name = 3;

Returns
Type	Description
`ByteString`	The bytes for displayName.

getEnableAccessLogging()

public abstract boolean 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.

bool enable_access_logging = 13;

Returns
Type	Description
`boolean`	The enableAccessLogging.

getExplanationSpec()

public abstract ExplanationSpec 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.

.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9;

Returns
Type	Description
`ExplanationSpec`	The explanationSpec.

getExplanationSpecOrBuilder()

public abstract ExplanationSpecOrBuilder getExplanationSpecOrBuilder()

Explanation configuration for this DeployedModel.

.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9;

Returns
Type	Description
`ExplanationSpecOrBuilder`

getId()

public abstract String 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]/.

string id = 1 [(.google.api.field_behavior) = IMMUTABLE];

Returns
Type	Description
`String`	The id.

getIdBytes()

public abstract ByteString getIdBytes()

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]/.

string id = 1 [(.google.api.field_behavior) = IMMUTABLE];

Returns
Type	Description
`ByteString`	The bytes for id.

getModel()

public abstract String 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.

string model = 2 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Returns
Type	Description
`String`	The model.

getModelBytes()

public abstract ByteString getModelBytes()

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.

string model = 2 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Returns
Type	Description
`ByteString`	The bytes for model.

getModelVersionId()

public abstract String getModelVersionId()

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

string model_version_id = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
`String`	The modelVersionId.

getModelVersionIdBytes()

public abstract ByteString getModelVersionIdBytes()

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

string model_version_id = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
`ByteString`	The bytes for modelVersionId.

getPredictionResourcesCase()

public abstract DeployedModel.PredictionResourcesCase getPredictionResourcesCase()

Returns
Type	Description
`DeployedModel.PredictionResourcesCase`

getPrivateEndpoints()

public abstract PrivateEndpoints 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.

.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
`PrivateEndpoints`	The privateEndpoints.

getPrivateEndpointsOrBuilder()

public abstract PrivateEndpointsOrBuilder getPrivateEndpointsOrBuilder()

.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
`PrivateEndpointsOrBuilder`

getServiceAccount()

public abstract String 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.

string service_account = 11;

Returns
Type	Description
`String`	The serviceAccount.

getServiceAccountBytes()

public abstract ByteString getServiceAccountBytes()

Users deploying the Model must have the iam.serviceAccounts.actAs permission on this service account.

string service_account = 11;

Returns
Type	Description
`ByteString`	The bytes for serviceAccount.

hasAutomaticResources()

public abstract boolean hasAutomaticResources()

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

.google.cloud.aiplatform.v1.AutomaticResources automatic_resources = 8;

Returns
Type	Description
`boolean`	Whether the automaticResources field is set.

hasCreateTime()

public abstract boolean hasCreateTime()

Output only. Timestamp when the DeployedModel was created.

.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
`boolean`	Whether the createTime field is set.

hasDedicatedResources()

public abstract boolean hasDedicatedResources()

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

.google.cloud.aiplatform.v1.DedicatedResources dedicated_resources = 7;

Returns
Type	Description
`boolean`	Whether the dedicatedResources field is set.

hasExplanationSpec()

public abstract boolean hasExplanationSpec()

Explanation configuration for this DeployedModel.

.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9;

Returns
Type	Description
`boolean`	Whether the explanationSpec field is set.

hasPrivateEndpoints()

public abstract boolean hasPrivateEndpoints()

.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns
Type	Description
`boolean`	Whether the privateEndpoints field is set.