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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.BuilderImplements
DeployedModelOrBuilderMethods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public DeployedModel.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
DeployedModel.Builder |
build()
public DeployedModel build()
Type | Description |
DeployedModel |
buildPartial()
public DeployedModel buildPartial()
Type | Description |
DeployedModel |
clear()
public DeployedModel.Builder clear()
Type | Description |
DeployedModel.Builder |
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;
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];
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;
Type | Description |
DeployedModel.Builder |
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;
Type | Description |
DeployedModel.Builder | This builder for chaining. |
clearEnableAccessLogging()
public DeployedModel.Builder clearEnableAccessLogging()
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;
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 Stackdriver Logging.
Only supported for custom-trained Models and AutoML Tabular Models.
bool enable_container_logging = 12;
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;
Type | Description |
DeployedModel.Builder |
clearField(Descriptors.FieldDescriptor field)
public DeployedModel.Builder clearField(Descriptors.FieldDescriptor field)
Name | Description |
field | FieldDescriptor |
Type | Description |
DeployedModel.Builder |
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];
Type | Description |
DeployedModel.Builder | This builder for chaining. |
clearModel()
public DeployedModel.Builder clearModel()
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) = { ... }
Type | Description |
DeployedModel.Builder | This builder for chaining. |
clearOneof(Descriptors.OneofDescriptor oneof)
public DeployedModel.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Name | Description |
oneof | OneofDescriptor |
Type | Description |
DeployedModel.Builder |
clearPredictionResources()
public DeployedModel.Builder clearPredictionResources()
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];
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;
Type | Description |
DeployedModel.Builder | This builder for chaining. |
clone()
public DeployedModel.Builder clone()
Type | Description |
DeployedModel.Builder |
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;
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;
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;
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];
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];
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];
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;
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;
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;
Type | Description |
DedicatedResourcesOrBuilder |
getDefaultInstanceForType()
public DeployedModel getDefaultInstanceForType()
Type | Description |
DeployedModel |
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Type | Description |
Descriptor |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Type | Description |
Descriptor |
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;
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;
Type | Description |
ByteString | The bytes for displayName. |
getEnableAccessLogging()
public 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;
Type | Description |
boolean | The enableAccessLogging. |
getEnableContainerLogging()
public 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;
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;
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;
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;
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];
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];
Type | Description |
ByteString | The bytes for id. |
getModel()
public 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) = { ... }
Type | Description |
String | The model. |
getModelBytes()
public 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) = { ... }
Type | Description |
ByteString | The bytes for model. |
getPredictionResourcesCase()
public DeployedModel.PredictionResourcesCase getPredictionResourcesCase()
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];
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];
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];
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;
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;
Type | Description |
ByteString | The bytes for serviceAccount. |
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;
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];
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;
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;
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];
Type | Description |
boolean | Whether the privateEndpoints field is set. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Type | Description |
FieldAccessorTable |
isInitialized()
public final boolean isInitialized()
Type | Description |
boolean |
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;
Name | Description |
value | AutomaticResources |
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];
Name | Description |
value | Timestamp |
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;
Name | Description |
value | DedicatedResources |
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;
Name | Description |
value | ExplanationSpec |
Type | Description |
DeployedModel.Builder |
mergeFrom(DeployedModel other)
public DeployedModel.Builder mergeFrom(DeployedModel other)
Name | Description |
other | DeployedModel |
Type | Description |
DeployedModel.Builder |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public DeployedModel.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Name | Description |
input | CodedInputStream |
extensionRegistry | ExtensionRegistryLite |
Type | Description |
DeployedModel.Builder |
Type | Description |
IOException |
mergeFrom(Message other)
public DeployedModel.Builder mergeFrom(Message other)
Name | Description |
other | Message |
Type | Description |
DeployedModel.Builder |
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];
Name | Description |
value | PrivateEndpoints |
Type | Description |
DeployedModel.Builder |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final DeployedModel.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
DeployedModel.Builder |
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;
Name | Description |
value | AutomaticResources |
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;
Name | Description |
builderForValue | AutomaticResources.Builder |
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];
Name | Description |
value | Timestamp |
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];
Name | Description |
builderForValue | Builder |
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;
Name | Description |
value | DedicatedResources |
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;
Name | Description |
builderForValue | DedicatedResources.Builder |
Type | Description |
DeployedModel.Builder |
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;
Name | Description |
value | String The displayName to set. |
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;
Name | Description |
value | ByteString The bytes for displayName to set. |
Type | Description |
DeployedModel.Builder | This builder for chaining. |
setEnableAccessLogging(boolean value)
public DeployedModel.Builder setEnableAccessLogging(boolean value)
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;
Name | Description |
value | boolean The enableAccessLogging to set. |
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 Stackdriver Logging.
Only supported for custom-trained Models and AutoML Tabular Models.
bool enable_container_logging = 12;
Name | Description |
value | boolean The enableContainerLogging to set. |
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;
Name | Description |
value | ExplanationSpec |
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;
Name | Description |
builderForValue | ExplanationSpec.Builder |
Type | Description |
DeployedModel.Builder |
setField(Descriptors.FieldDescriptor field, Object value)
public DeployedModel.Builder setField(Descriptors.FieldDescriptor field, Object value)
Name | Description |
field | FieldDescriptor |
value | Object |
Type | Description |
DeployedModel.Builder |
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];
Name | Description |
value | String The id to set. |
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];
Name | Description |
value | ByteString The bytes for id to set. |
Type | Description |
DeployedModel.Builder | This builder for chaining. |
setModel(String value)
public DeployedModel.Builder setModel(String value)
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) = { ... }
Name | Description |
value | String The model to set. |
Type | Description |
DeployedModel.Builder | This builder for chaining. |
setModelBytes(ByteString value)
public DeployedModel.Builder setModelBytes(ByteString value)
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) = { ... }
Name | Description |
value | ByteString The bytes for model to set. |
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];
Name | Description |
value | PrivateEndpoints |
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];
Name | Description |
builderForValue | PrivateEndpoints.Builder |
Type | Description |
DeployedModel.Builder |
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public DeployedModel.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Name | Description |
field | FieldDescriptor |
index | int |
value | Object |
Type | Description |
DeployedModel.Builder |
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;
Name | Description |
value | String The serviceAccount to set. |
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;
Name | Description |
value | ByteString The bytes for serviceAccount to set. |
Type | Description |
DeployedModel.Builder | This builder for chaining. |
setUnknownFields(UnknownFieldSet unknownFields)
public final DeployedModel.Builder setUnknownFields(UnknownFieldSet unknownFields)
Name | Description |
unknownFields | UnknownFieldSet |
Type | Description |
DeployedModel.Builder |