com.google.cloud.aiplatform.v1beta1

Interface DeployedModelOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

DeployedModel, DeployedModel.Builder

public interface DeployedModelOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
AutomaticResources	getAutomaticResources() A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.
AutomaticResourcesOrBuilder	getAutomaticResourcesOrBuilder() A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.
com.google.protobuf.Timestamp	getCreateTime() Output only.
com.google.protobuf.TimestampOrBuilder	getCreateTimeOrBuilder() Output only.
DedicatedResources	getDedicatedResources() A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.
DedicatedResourcesOrBuilder	getDedicatedResourcesOrBuilder() A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.
String	getDisplayName() The display name of the DeployedModel.
com.google.protobuf.ByteString	getDisplayNameBytes() The display name of the DeployedModel.
boolean	getEnableAccessLogging() These logs are like standard server access logs, containing information like timestamp and latency for each prediction request.
boolean	getEnableContainerLogging() If true, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Stackdriver Logging.
ExplanationSpec	getExplanationSpec() Explanation configuration for this DeployedModel.
ExplanationSpecOrBuilder	getExplanationSpecOrBuilder() Explanation configuration for this DeployedModel.
String	getId() Output only.
com.google.protobuf.ByteString	getIdBytes() Output only.
String	getModel() Required.
com.google.protobuf.ByteString	getModelBytes() Required.
DeployedModel.PredictionResourcesCase	getPredictionResourcesCase()
PrivateEndpoints	getPrivateEndpoints() Output only.
PrivateEndpointsOrBuilder	getPrivateEndpointsOrBuilder() Output only.
String	getServiceAccount() The service account that the DeployedModel's container runs as.
com.google.protobuf.ByteString	getServiceAccountBytes() The service account that the DeployedModel's container runs as.
boolean	hasAutomaticResources() A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.
boolean	hasCreateTime() Output only.
boolean	hasDedicatedResources() A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.
boolean	hasExplanationSpec() Explanation configuration for this DeployedModel.
boolean	hasPrivateEndpoints() Output only.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

hasDedicatedResources

boolean hasDedicatedResources()

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

.google.cloud.aiplatform.v1beta1.DedicatedResources dedicated_resources = 7;

Returns:

Whether the dedicatedResources field is set.

getDedicatedResources

DedicatedResources getDedicatedResources()

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

.google.cloud.aiplatform.v1beta1.DedicatedResources dedicated_resources = 7;

Returns:

The dedicatedResources.

getDedicatedResourcesOrBuilder

DedicatedResourcesOrBuilder getDedicatedResourcesOrBuilder()

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

.google.cloud.aiplatform.v1beta1.DedicatedResources dedicated_resources = 7;

hasAutomaticResources

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.v1beta1.AutomaticResources automatic_resources = 8;

Returns:

Whether the automaticResources field is set.

getAutomaticResources

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.v1beta1.AutomaticResources automatic_resources = 8;

Returns:

The automaticResources.

getAutomaticResourcesOrBuilder

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.v1beta1.AutomaticResources automatic_resources = 8;

getId

String getId()

 Output only. The ID of the DeployedModel.
 

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

Returns:

The id.

getIdBytes

com.google.protobuf.ByteString getIdBytes()

 Output only. The ID of the DeployedModel.
 

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

Returns:

The bytes for id.

getModel

String getModel()

 Required. The 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:

The model.

getModelBytes

com.google.protobuf.ByteString getModelBytes()

 Required. The 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:

The bytes for model.

getDisplayName

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:

The displayName.

getDisplayNameBytes

com.google.protobuf.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:

The bytes for displayName.

hasCreateTime

boolean hasCreateTime()

 Output only. Timestamp when the DeployedModel was created.
 

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

Returns:

Whether the createTime field is set.

getCreateTime

com.google.protobuf.Timestamp getCreateTime()

 Output only. Timestamp when the DeployedModel was created.
 

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

Returns:

The createTime.

getCreateTimeOrBuilder

com.google.protobuf.TimestampOrBuilder getCreateTimeOrBuilder()

 Output only. Timestamp when the DeployedModel was created.
 

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

hasExplanationSpec

boolean hasExplanationSpec()

 Explanation configuration for this DeployedModel.
 When deploying a Model using [EndpointService.DeployModel][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel], this value
 overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec]. All fields of
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] are optional in the request. If a field of
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] is not populated, the value of the same field of
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec] is inherited. If the corresponding
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec] is not populated, all fields of the
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] will be used for the explanation configuration.
 

.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 9;

Returns:

Whether the explanationSpec field is set.

getExplanationSpec

ExplanationSpec getExplanationSpec()

 Explanation configuration for this DeployedModel.
 When deploying a Model using [EndpointService.DeployModel][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel], this value
 overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec]. All fields of
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] are optional in the request. If a field of
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] is not populated, the value of the same field of
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec] is inherited. If the corresponding
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec] is not populated, all fields of the
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] will be used for the explanation configuration.
 

.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 9;

Returns:

The explanationSpec.

getExplanationSpecOrBuilder

ExplanationSpecOrBuilder getExplanationSpecOrBuilder()

 Explanation configuration for this DeployedModel.
 When deploying a Model using [EndpointService.DeployModel][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel], this value
 overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec]. All fields of
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] are optional in the request. If a field of
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] is not populated, the value of the same field of
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec] is inherited. If the corresponding
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec] is not populated, all fields of the
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec] will be used for the explanation configuration.
 

.google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 9;

getServiceAccount

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:

The serviceAccount.

getServiceAccountBytes

com.google.protobuf.ByteString getServiceAccountBytes()

 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:

The bytes for serviceAccount.

getEnableContainerLogging

boolean getEnableContainerLogging()

 If true, the container of the DeployedModel instances will send `stderr`
 and `stdout` streams to Stackdriver Logging.
 Only supported for custom-trained Models and AutoML Tabular Models.
 

bool enable_container_logging = 12;

Returns:

The enableContainerLogging.

getEnableAccessLogging

boolean getEnableAccessLogging()

 These logs are like standard server access logs, containing
 information like timestamp and latency for each prediction request.
 Note that Stackdriver 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:

The enableAccessLogging.

hasPrivateEndpoints

boolean hasPrivateEndpoints()

 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][google.cloud.aiplatform.v1beta1.Endpoint.network] is configured.
 

.google.cloud.aiplatform.v1beta1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

Whether the privateEndpoints field is set.

getPrivateEndpoints

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][google.cloud.aiplatform.v1beta1.Endpoint.network] is configured.
 

.google.cloud.aiplatform.v1beta1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

Returns:

The privateEndpoints.

getPrivateEndpointsOrBuilder

PrivateEndpointsOrBuilder getPrivateEndpointsOrBuilder()

 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][google.cloud.aiplatform.v1beta1.Endpoint.network] is configured.
 

.google.cloud.aiplatform.v1beta1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

getPredictionResourcesCase

DeployedModel.PredictionResourcesCase getPredictionResourcesCase()