Class DeployedModel.Builder (3.43.0) 

public static final class DeployedModel.Builder extends GeneratedMessageV3.Builder<DeployedModel.Builder> implements DeployedModelOrBuilder

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

Protobuf type google.cloud.aiplatform.v1beta1.DeployedModel

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > DeployedModel.Builder

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
Type Description
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public DeployedModel.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
Name Description
field FieldDescriptor
value Object
Returns
Type Description
DeployedModel.Builder
Overrides

build()

public DeployedModel build()
Returns
Type Description
DeployedModel

buildPartial()

public DeployedModel buildPartial()
Returns
Type Description
DeployedModel

clear()

public DeployedModel.Builder clear()
Returns
Type Description
DeployedModel.Builder
Overrides

clearAutomaticResources()

public DeployedModel.Builder clearAutomaticResources()

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
Type Description
DeployedModel.Builder

clearCreateTime()

public DeployedModel.Builder clearCreateTime()

Output only. Timestamp when the DeployedModel was created.

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

Returns
Type Description
DeployedModel.Builder

clearDedicatedResources()

public DeployedModel.Builder clearDedicatedResources()

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
Type Description
DeployedModel.Builder

clearDisableExplanations()

public DeployedModel.Builder clearDisableExplanations()

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

bool disable_explanations = 19;

Returns
Type Description
DeployedModel.Builder

This builder for chaining.

clearDisplayName()

public DeployedModel.Builder clearDisplayName()

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
DeployedModel.Builder

This builder for chaining.

clearEnableAccessLogging()

public DeployedModel.Builder clearEnableAccessLogging()

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
DeployedModel.Builder

This builder for chaining.

clearEnableContainerLogging()

public DeployedModel.Builder clearEnableContainerLogging()

If true, the container of the DeployedModel instances will send stderr and stdout streams to Cloud Logging.

Only supported for custom-trained Models and AutoML Tabular Models.

bool enable_container_logging = 12;

Returns
Type Description
DeployedModel.Builder

This builder for chaining.

clearExplanationSpec()

public DeployedModel.Builder clearExplanationSpec()

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.v1beta1.ExplanationSpec explanation_spec = 9;

Returns
Type Description
DeployedModel.Builder

clearField(Descriptors.FieldDescriptor field)

public DeployedModel.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
Name Description
field FieldDescriptor
Returns
Type Description
DeployedModel.Builder
Overrides

clearId()

public DeployedModel.Builder clearId()

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
DeployedModel.Builder

This builder for chaining.

clearModel()

public DeployedModel.Builder clearModel()

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
DeployedModel.Builder

This builder for chaining.

clearModelVersionId()

public DeployedModel.Builder clearModelVersionId()

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
DeployedModel.Builder

This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public DeployedModel.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
Name Description
oneof OneofDescriptor
Returns
Type Description
DeployedModel.Builder
Overrides

clearPredictionResources()

public DeployedModel.Builder clearPredictionResources()
Returns
Type Description
DeployedModel.Builder

clearPrivateEndpoints()

public DeployedModel.Builder clearPrivateEndpoints()

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

Returns
Type Description
DeployedModel.Builder

clearServiceAccount()

public DeployedModel.Builder clearServiceAccount()

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
DeployedModel.Builder

This builder for chaining.

clearSharedResources()

public DeployedModel.Builder clearSharedResources()

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

string shared_resources = 17 [(.google.api.resource_reference) = { ... }

Returns
Type Description
DeployedModel.Builder

This builder for chaining.

clone()

public DeployedModel.Builder clone()
Returns
Type Description
DeployedModel.Builder
Overrides

getAutomaticResources()

public 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
Type Description
AutomaticResources

The automaticResources.

getAutomaticResourcesBuilder()

public AutomaticResources.Builder getAutomaticResourcesBuilder()

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
Type Description
AutomaticResources.Builder

getAutomaticResourcesOrBuilder()

public 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;

Returns
Type Description
AutomaticResourcesOrBuilder

getCreateTime()

public 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.

getCreateTimeBuilder()

public Timestamp.Builder getCreateTimeBuilder()

Output only. Timestamp when the DeployedModel was created.

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

Returns
Type Description
Builder

getCreateTimeOrBuilder()

public 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 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
Type Description
DedicatedResources

The dedicatedResources.

getDedicatedResourcesBuilder()

public DedicatedResources.Builder getDedicatedResourcesBuilder()

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
Type Description
DedicatedResources.Builder

getDedicatedResourcesOrBuilder()

public 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;

Returns
Type Description
DedicatedResourcesOrBuilder

getDefaultInstanceForType()

public DeployedModel getDefaultInstanceForType()
Returns
Type Description
DeployedModel

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
Type Description
Descriptor
Overrides

getDisableExplanations()

public boolean getDisableExplanations()

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

bool disable_explanations = 19;

Returns
Type Description
boolean

The disableExplanations.

getDisplayName()

public 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 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 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.

getEnableContainerLogging()

public boolean getEnableContainerLogging()

If true, the container of the DeployedModel instances will send stderr and stdout streams to Cloud Logging.

Only supported for custom-trained Models and AutoML Tabular Models.

bool enable_container_logging = 12;

Returns
Type Description
boolean

The enableContainerLogging.

getExplanationSpec()

public 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.v1beta1.ExplanationSpec explanation_spec = 9;

Returns
Type Description
ExplanationSpec

The explanationSpec.

getExplanationSpecBuilder()

public ExplanationSpec.Builder getExplanationSpecBuilder()

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.v1beta1.ExplanationSpec explanation_spec = 9;

Returns
Type Description
ExplanationSpec.Builder

getExplanationSpecOrBuilder()

public ExplanationSpecOrBuilder getExplanationSpecOrBuilder()

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.v1beta1.ExplanationSpec explanation_spec = 9;

Returns
Type Description
ExplanationSpecOrBuilder

getId()

public 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 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 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 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.

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
ByteString

The bytes for model.

getModelVersionId()

public 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 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 DeployedModel.PredictionResourcesCase getPredictionResourcesCase()
Returns
Type Description
DeployedModel.PredictionResourcesCase

getPrivateEndpoints()

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

Returns
Type Description
PrivateEndpoints

The privateEndpoints.

getPrivateEndpointsBuilder()

public PrivateEndpoints.Builder getPrivateEndpointsBuilder()

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

Returns
Type Description
PrivateEndpoints.Builder

getPrivateEndpointsOrBuilder()

public 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 is configured.

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

Returns
Type Description
PrivateEndpointsOrBuilder

getServiceAccount()

public 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 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
Type Description
ByteString

The bytes for serviceAccount.

getSharedResources()

public String getSharedResources()

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

string shared_resources = 17 [(.google.api.resource_reference) = { ... }

Returns
Type Description
String

The sharedResources.

getSharedResourcesBytes()

public ByteString getSharedResourcesBytes()

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

string shared_resources = 17 [(.google.api.resource_reference) = { ... }

Returns
Type Description
ByteString

The bytes for sharedResources.

hasAutomaticResources()

public 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
Type Description
boolean

Whether the automaticResources field is set.

hasCreateTime()

public 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 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
Type Description
boolean

Whether the dedicatedResources field is set.

hasExplanationSpec()

public boolean hasExplanationSpec()

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.v1beta1.ExplanationSpec explanation_spec = 9;

Returns
Type Description
boolean

Whether the explanationSpec field is set.

hasPrivateEndpoints()

public 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 is configured.

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

Returns
Type Description
boolean

Whether the privateEndpoints field is set.

hasSharedResources()

public boolean hasSharedResources()

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

string shared_resources = 17 [(.google.api.resource_reference) = { ... }

Returns
Type Description
boolean

Whether the sharedResources field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
Type Description
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
Type Description
boolean
Overrides

mergeAutomaticResources(AutomaticResources value)

public DeployedModel.Builder mergeAutomaticResources(AutomaticResources value)

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;

Parameter
Name Description
value AutomaticResources
Returns
Type Description
DeployedModel.Builder

mergeCreateTime(Timestamp value)

public DeployedModel.Builder mergeCreateTime(Timestamp value)

Output only. Timestamp when the DeployedModel was created.

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

Parameter
Name Description
value Timestamp
Returns
Type Description
DeployedModel.Builder

mergeDedicatedResources(DedicatedResources value)

public DeployedModel.Builder mergeDedicatedResources(DedicatedResources value)

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;

Parameter
Name Description
value DedicatedResources
Returns
Type Description
DeployedModel.Builder

mergeExplanationSpec(ExplanationSpec value)

public DeployedModel.Builder mergeExplanationSpec(ExplanationSpec value)

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.v1beta1.ExplanationSpec explanation_spec = 9;

Parameter
Name Description
value ExplanationSpec
Returns
Type Description
DeployedModel.Builder

mergeFrom(DeployedModel other)

public DeployedModel.Builder mergeFrom(DeployedModel other)
Parameter
Name Description
other DeployedModel
Returns
Type Description
DeployedModel.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public DeployedModel.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
Name Description
input CodedInputStream
extensionRegistry ExtensionRegistryLite
Returns
Type Description
DeployedModel.Builder
Overrides
Exceptions
Type Description
IOException

mergeFrom(Message other)

public DeployedModel.Builder mergeFrom(Message other)
Parameter
Name Description
other Message
Returns
Type Description
DeployedModel.Builder
Overrides

mergePrivateEndpoints(PrivateEndpoints value)

public DeployedModel.Builder mergePrivateEndpoints(PrivateEndpoints value)

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

Parameter
Name Description
value PrivateEndpoints
Returns
Type Description
DeployedModel.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final DeployedModel.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
DeployedModel.Builder
Overrides

setAutomaticResources(AutomaticResources value)

public DeployedModel.Builder setAutomaticResources(AutomaticResources value)

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;

Parameter
Name Description
value AutomaticResources
Returns
Type Description
DeployedModel.Builder

setAutomaticResources(AutomaticResources.Builder builderForValue)

public DeployedModel.Builder setAutomaticResources(AutomaticResources.Builder builderForValue)

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;

Parameter
Name Description
builderForValue AutomaticResources.Builder
Returns
Type Description
DeployedModel.Builder

setCreateTime(Timestamp value)

public DeployedModel.Builder setCreateTime(Timestamp value)

Output only. Timestamp when the DeployedModel was created.

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

Parameter
Name Description
value Timestamp
Returns
Type Description
DeployedModel.Builder

setCreateTime(Timestamp.Builder builderForValue)

public DeployedModel.Builder setCreateTime(Timestamp.Builder builderForValue)

Output only. Timestamp when the DeployedModel was created.

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

Parameter
Name Description
builderForValue Builder
Returns
Type Description
DeployedModel.Builder

setDedicatedResources(DedicatedResources value)

public DeployedModel.Builder setDedicatedResources(DedicatedResources value)

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;

Parameter
Name Description
value DedicatedResources
Returns
Type Description
DeployedModel.Builder

setDedicatedResources(DedicatedResources.Builder builderForValue)

public DeployedModel.Builder setDedicatedResources(DedicatedResources.Builder builderForValue)

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;

Parameter
Name Description
builderForValue DedicatedResources.Builder
Returns
Type Description
DeployedModel.Builder

setDisableExplanations(boolean value)

public DeployedModel.Builder setDisableExplanations(boolean value)

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

bool disable_explanations = 19;

Parameter
Name Description
value boolean

The disableExplanations to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setDisplayName(String value)

public DeployedModel.Builder setDisplayName(String value)

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

string display_name = 3;

Parameter
Name Description
value String

The displayName to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setDisplayNameBytes(ByteString value)

public DeployedModel.Builder setDisplayNameBytes(ByteString value)

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

string display_name = 3;

Parameter
Name Description
value ByteString

The bytes for displayName to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setEnableAccessLogging(boolean value)

public DeployedModel.Builder setEnableAccessLogging(boolean value)

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;

Parameter
Name Description
value boolean

The enableAccessLogging to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setEnableContainerLogging(boolean value)

public DeployedModel.Builder setEnableContainerLogging(boolean value)

If true, the container of the DeployedModel instances will send stderr and stdout streams to Cloud Logging.

Only supported for custom-trained Models and AutoML Tabular Models.

bool enable_container_logging = 12;

Parameter
Name Description
value boolean

The enableContainerLogging to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setExplanationSpec(ExplanationSpec value)

public DeployedModel.Builder setExplanationSpec(ExplanationSpec value)

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.v1beta1.ExplanationSpec explanation_spec = 9;

Parameter
Name Description
value ExplanationSpec
Returns
Type Description
DeployedModel.Builder

setExplanationSpec(ExplanationSpec.Builder builderForValue)

public DeployedModel.Builder setExplanationSpec(ExplanationSpec.Builder builderForValue)

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.v1beta1.ExplanationSpec explanation_spec = 9;

Parameter
Name Description
builderForValue ExplanationSpec.Builder
Returns
Type Description
DeployedModel.Builder

setField(Descriptors.FieldDescriptor field, Object value)

public DeployedModel.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
Name Description
field FieldDescriptor
value Object
Returns
Type Description
DeployedModel.Builder
Overrides

setId(String value)

public DeployedModel.Builder setId(String value)

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];

Parameter
Name Description
value String

The id to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setIdBytes(ByteString value)

public DeployedModel.Builder setIdBytes(ByteString value)

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];

Parameter
Name Description
value ByteString

The bytes for id to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setModel(String value)

public DeployedModel.Builder setModel(String value)

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) = { ... }

Parameter
Name Description
value String

The model to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setModelBytes(ByteString value)

public DeployedModel.Builder setModelBytes(ByteString value)

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) = { ... }

Parameter
Name Description
value ByteString

The bytes for model to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setModelVersionId(String value)

public DeployedModel.Builder setModelVersionId(String value)

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

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

Parameter
Name Description
value String

The modelVersionId to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setModelVersionIdBytes(ByteString value)

public DeployedModel.Builder setModelVersionIdBytes(ByteString value)

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

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

Parameter
Name Description
value ByteString

The bytes for modelVersionId to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setPrivateEndpoints(PrivateEndpoints value)

public DeployedModel.Builder setPrivateEndpoints(PrivateEndpoints value)

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

Parameter
Name Description
value PrivateEndpoints
Returns
Type Description
DeployedModel.Builder

setPrivateEndpoints(PrivateEndpoints.Builder builderForValue)

public DeployedModel.Builder setPrivateEndpoints(PrivateEndpoints.Builder builderForValue)

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

Parameter
Name Description
builderForValue PrivateEndpoints.Builder
Returns
Type Description
DeployedModel.Builder

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public DeployedModel.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
Name Description
field FieldDescriptor
index int
value Object
Returns
Type Description
DeployedModel.Builder
Overrides

setServiceAccount(String value)

public DeployedModel.Builder setServiceAccount(String value)

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;

Parameter
Name Description
value String

The serviceAccount to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setServiceAccountBytes(ByteString value)

public DeployedModel.Builder setServiceAccountBytes(ByteString value)

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;

Parameter
Name Description
value ByteString

The bytes for serviceAccount to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setSharedResources(String value)

public DeployedModel.Builder setSharedResources(String value)

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

string shared_resources = 17 [(.google.api.resource_reference) = { ... }

Parameter
Name Description
value String

The sharedResources to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setSharedResourcesBytes(ByteString value)

public DeployedModel.Builder setSharedResourcesBytes(ByteString value)

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

string shared_resources = 17 [(.google.api.resource_reference) = { ... }

Parameter
Name Description
value ByteString

The bytes for sharedResources to set.
Returns
Type Description
DeployedModel.Builder

This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final DeployedModel.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
DeployedModel.Builder
Overrides