Package com.google.cloud.aiplatform.v1
Class DeployedModel.Builder
java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<DeployedModel.Builder>
com.google.cloud.aiplatform.v1.DeployedModel.Builder
- All Implemented Interfaces:
DeployedModelOrBuilder,com.google.protobuf.Message.Builder,com.google.protobuf.MessageLite.Builder,com.google.protobuf.MessageLiteOrBuilder,com.google.protobuf.MessageOrBuilder,Cloneable
- Enclosing class:
- DeployedModel
public static final class DeployedModel.Builder
extends com.google.protobuf.GeneratedMessage.Builder<DeployedModel.Builder>
implements DeployedModelOrBuilder
A deployment of a Model. Endpoints contain one or more DeployedModels.Protobuf type
google.cloud.aiplatform.v1.DeployedModel-
Method Summary
Modifier and TypeMethodDescriptionbuild()clear()A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.The checkpoint id of the model.Output only.A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.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.If true, deploy the model without explainable feature, regardless the existence of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] or [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec].The display name of the DeployedModel.If true, online prediction access logs are sent to Cloud Logging.Explanation configuration for this DeployedModel.Configuration for faster model deployment.clearId()Immutable.The resource name of the Model that this is the deployment of.Output only.Output only.The service account that the DeployedModel's container runs as.The resource name of the shared DeploymentResourcePool to deploy on.Optional.Output only.booleanSystem labels to apply to Model Garden deployments.A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.The checkpoint id of the model.com.google.protobuf.ByteStringThe checkpoint id of the model.com.google.protobuf.TimestampOutput only.com.google.protobuf.Timestamp.BuilderOutput only.com.google.protobuf.TimestampOrBuilderOutput only.A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.static final com.google.protobuf.Descriptors.Descriptorcom.google.protobuf.Descriptors.DescriptorbooleanFor custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default.booleanIf true, deploy the model without explainable feature, regardless the existence of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] or [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec].The display name of the DeployedModel.com.google.protobuf.ByteStringThe display name of the DeployedModel.booleanIf true, online prediction access logs are sent to Cloud Logging.Explanation configuration for this DeployedModel.Explanation configuration for this DeployedModel.Explanation configuration for this DeployedModel.Configuration for faster model deployment.Configuration for faster model deployment.Configuration for faster model deployment.getId()Immutable.com.google.protobuf.ByteStringImmutable.getModel()The resource name of the Model that this is the deployment of.com.google.protobuf.ByteStringThe resource name of the Model that this is the deployment of.Output only.com.google.protobuf.ByteStringOutput only.Deprecated.Output only.Output only.Output only.The service account that the DeployedModel's container runs as.com.google.protobuf.ByteStringThe service account that the DeployedModel's container runs as.The resource name of the shared DeploymentResourcePool to deploy on.com.google.protobuf.ByteStringThe resource name of the shared DeploymentResourcePool to deploy on.Optional.Optional.Optional.Output only.Output only.Output only.Deprecated.intSystem labels to apply to Model Garden deployments.System labels to apply to Model Garden deployments.getSystemLabelsOrDefault(String key, String defaultValue) System labels to apply to Model Garden deployments.System labels to apply to Model Garden deployments.booleanA description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.booleanOutput only.booleanA description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.booleanExplanation configuration for this DeployedModel.booleanConfiguration for faster model deployment.booleanOutput only.booleanThe resource name of the shared DeploymentResourcePool to deploy on.booleanOptional.booleanOutput only.protected com.google.protobuf.GeneratedMessage.FieldAccessorTableprotected com.google.protobuf.MapFieldReflectionAccessorinternalGetMapFieldReflection(int number) protected com.google.protobuf.MapFieldReflectionAccessorinternalGetMutableMapFieldReflection(int number) final booleanA description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.mergeCreateTime(com.google.protobuf.Timestamp value) Output only.A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.Explanation configuration for this DeployedModel.Configuration for faster model deployment.mergeFrom(DeployedModel other) mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) mergeFrom(com.google.protobuf.Message other) Output only.Optional.mergeStatus(DeployedModel.Status value) Output only.putAllSystemLabels(Map<String, String> values) System labels to apply to Model Garden deployments.putSystemLabels(String key, String value) System labels to apply to Model Garden deployments.removeSystemLabels(String key) System labels to apply to Model Garden deployments.A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.setAutomaticResources(AutomaticResources.Builder builderForValue) A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration.setCheckpointId(String value) The checkpoint id of the model.setCheckpointIdBytes(com.google.protobuf.ByteString value) The checkpoint id of the model.setCreateTime(com.google.protobuf.Timestamp value) Output only.setCreateTime(com.google.protobuf.Timestamp.Builder builderForValue) Output only.A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.setDedicatedResources(DedicatedResources.Builder builderForValue) A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.setDisableContainerLogging(boolean value) 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.setDisableExplanations(boolean value) If true, deploy the model without explainable feature, regardless the existence of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] or [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec].setDisplayName(String value) The display name of the DeployedModel.setDisplayNameBytes(com.google.protobuf.ByteString value) The display name of the DeployedModel.setEnableAccessLogging(boolean value) If true, online prediction access logs are sent to Cloud Logging.Explanation configuration for this DeployedModel.setExplanationSpec(ExplanationSpec.Builder builderForValue) Explanation configuration for this DeployedModel.Configuration for faster model deployment.setFasterDeploymentConfig(FasterDeploymentConfig.Builder builderForValue) Configuration for faster model deployment.Immutable.setIdBytes(com.google.protobuf.ByteString value) Immutable.The resource name of the Model that this is the deployment of.setModelBytes(com.google.protobuf.ByteString value) The resource name of the Model that this is the deployment of.setModelVersionId(String value) Output only.setModelVersionIdBytes(com.google.protobuf.ByteString value) Output only.Output only.setPrivateEndpoints(PrivateEndpoints.Builder builderForValue) Output only.setServiceAccount(String value) The service account that the DeployedModel's container runs as.setServiceAccountBytes(com.google.protobuf.ByteString value) The service account that the DeployedModel's container runs as.setSharedResources(String value) The resource name of the shared DeploymentResourcePool to deploy on.setSharedResourcesBytes(com.google.protobuf.ByteString value) The resource name of the shared DeploymentResourcePool to deploy on.Optional.setSpeculativeDecodingSpec(SpeculativeDecodingSpec.Builder builderForValue) Optional.setStatus(DeployedModel.Status value) Output only.setStatus(DeployedModel.Status.Builder builderForValue) Output only.Methods inherited from class com.google.protobuf.GeneratedMessage.Builder
addRepeatedField, clearField, clearOneof, clone, getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMutableMapField, isClean, markClean, mergeUnknownFields, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setField, setRepeatedField, setUnknownFields, setUnknownFieldSetBuilder, setUnknownFieldsProto3Methods inherited from class com.google.protobuf.AbstractMessage.Builder
findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toStringMethods inherited from class com.google.protobuf.AbstractMessageLite.Builder
addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, mergeFrom, newUninitializedMessageExceptionMethods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, waitMethods inherited from interface com.google.protobuf.Message.Builder
mergeDelimitedFrom, mergeDelimitedFromMethods inherited from interface com.google.protobuf.MessageLite.Builder
mergeFromMethods inherited from interface com.google.protobuf.MessageOrBuilder
findInitializationErrors, getAllFields, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof
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Method Details
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getDescriptor
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() -
internalGetMapFieldReflection
protected com.google.protobuf.MapFieldReflectionAccessor internalGetMapFieldReflection(int number) - Overrides:
internalGetMapFieldReflectionin classcom.google.protobuf.GeneratedMessage.Builder<DeployedModel.Builder>
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internalGetMutableMapFieldReflection
protected com.google.protobuf.MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number) - Overrides:
internalGetMutableMapFieldReflectionin classcom.google.protobuf.GeneratedMessage.Builder<DeployedModel.Builder>
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internalGetFieldAccessorTable
protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()- Specified by:
internalGetFieldAccessorTablein classcom.google.protobuf.GeneratedMessage.Builder<DeployedModel.Builder>
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clear
- Specified by:
clearin interfacecom.google.protobuf.Message.Builder- Specified by:
clearin interfacecom.google.protobuf.MessageLite.Builder- Overrides:
clearin classcom.google.protobuf.GeneratedMessage.Builder<DeployedModel.Builder>
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getDescriptorForType
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()- Specified by:
getDescriptorForTypein interfacecom.google.protobuf.Message.Builder- Specified by:
getDescriptorForTypein interfacecom.google.protobuf.MessageOrBuilder- Overrides:
getDescriptorForTypein classcom.google.protobuf.GeneratedMessage.Builder<DeployedModel.Builder>
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getDefaultInstanceForType
- Specified by:
getDefaultInstanceForTypein interfacecom.google.protobuf.MessageLiteOrBuilder- Specified by:
getDefaultInstanceForTypein interfacecom.google.protobuf.MessageOrBuilder
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build
- Specified by:
buildin interfacecom.google.protobuf.Message.Builder- Specified by:
buildin interfacecom.google.protobuf.MessageLite.Builder
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buildPartial
- Specified by:
buildPartialin interfacecom.google.protobuf.Message.Builder- Specified by:
buildPartialin interfacecom.google.protobuf.MessageLite.Builder
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mergeFrom
- Specified by:
mergeFromin interfacecom.google.protobuf.Message.Builder- Overrides:
mergeFromin classcom.google.protobuf.AbstractMessage.Builder<DeployedModel.Builder>
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mergeFrom
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isInitialized
public final boolean isInitialized()- Specified by:
isInitializedin interfacecom.google.protobuf.MessageLiteOrBuilder- Overrides:
isInitializedin classcom.google.protobuf.GeneratedMessage.Builder<DeployedModel.Builder>
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mergeFrom
public DeployedModel.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException - Specified by:
mergeFromin interfacecom.google.protobuf.Message.Builder- Specified by:
mergeFromin interfacecom.google.protobuf.MessageLite.Builder- Overrides:
mergeFromin classcom.google.protobuf.AbstractMessage.Builder<DeployedModel.Builder>- Throws:
IOException
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getPredictionResourcesCase
- Specified by:
getPredictionResourcesCasein interfaceDeployedModelOrBuilder
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clearPredictionResources
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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.v1.DedicatedResources dedicated_resources = 7;- Specified by:
hasDedicatedResourcesin interfaceDeployedModelOrBuilder- Returns:
- Whether the dedicatedResources field is set.
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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;- Specified by:
getDedicatedResourcesin interfaceDeployedModelOrBuilder- Returns:
- The dedicatedResources.
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setDedicatedResources
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; -
setDedicatedResources
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; -
mergeDedicatedResources
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; -
clearDedicatedResources
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; -
getDedicatedResourcesBuilder
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; -
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;- Specified by:
getDedicatedResourcesOrBuilderin interfaceDeployedModelOrBuilder
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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.v1.AutomaticResources automatic_resources = 8;- Specified by:
hasAutomaticResourcesin interfaceDeployedModelOrBuilder- Returns:
- Whether the automaticResources field is set.
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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;- Specified by:
getAutomaticResourcesin interfaceDeployedModelOrBuilder- Returns:
- The automaticResources.
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setAutomaticResources
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; -
setAutomaticResources
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; -
mergeAutomaticResources
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; -
clearAutomaticResources
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; -
getAutomaticResourcesBuilder
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; -
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;- Specified by:
getAutomaticResourcesOrBuilderin interfaceDeployedModelOrBuilder
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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];- Specified by:
getIdin interfaceDeployedModelOrBuilder- Returns:
- The id.
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getIdBytes
public com.google.protobuf.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];- Specified by:
getIdBytesin interfaceDeployedModelOrBuilder- Returns:
- The bytes for id.
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setId
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];- Parameters:
value- The id to set.- Returns:
- This builder for chaining.
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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:
- This builder for chaining.
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setIdBytes
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];- Parameters:
value- The bytes for id to set.- Returns:
- This builder for chaining.
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getModel
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.resource_reference) = { ... }- Specified by:
getModelin interfaceDeployedModelOrBuilder- Returns:
- The model.
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getModelBytes
public com.google.protobuf.ByteString getModelBytes()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.resource_reference) = { ... }- Specified by:
getModelBytesin interfaceDeployedModelOrBuilder- Returns:
- The bytes for model.
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setModel
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.resource_reference) = { ... }- Parameters:
value- The model to set.- Returns:
- This builder for chaining.
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clearModel
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.resource_reference) = { ... }- Returns:
- This builder for chaining.
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setModelBytes
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.resource_reference) = { ... }- Parameters:
value- The bytes for model to set.- Returns:
- This builder for chaining.
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getModelVersionId
Output only. The version ID of the model that is deployed.
string model_version_id = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
getModelVersionIdin interfaceDeployedModelOrBuilder- Returns:
- The modelVersionId.
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getModelVersionIdBytes
public com.google.protobuf.ByteString getModelVersionIdBytes()Output only. The version ID of the model that is deployed.
string model_version_id = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
getModelVersionIdBytesin interfaceDeployedModelOrBuilder- Returns:
- The bytes for modelVersionId.
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setModelVersionId
Output only. The version ID of the model that is deployed.
string model_version_id = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];- Parameters:
value- The modelVersionId to set.- Returns:
- This builder for chaining.
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clearModelVersionId
Output only. The version ID of the model that is deployed.
string model_version_id = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];- Returns:
- This builder for chaining.
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setModelVersionIdBytes
Output only. The version ID of the model that is deployed.
string model_version_id = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];- Parameters:
value- The bytes for modelVersionId to set.- Returns:
- This builder for chaining.
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getDisplayName
The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.
string display_name = 3;- Specified by:
getDisplayNamein interfaceDeployedModelOrBuilder- Returns:
- The displayName.
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getDisplayNameBytes
public 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;- Specified by:
getDisplayNameBytesin interfaceDeployedModelOrBuilder- Returns:
- The bytes for displayName.
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setDisplayName
The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.
string display_name = 3;- Parameters:
value- The displayName to set.- Returns:
- This builder for chaining.
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clearDisplayName
The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.
string display_name = 3;- Returns:
- This builder for chaining.
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setDisplayNameBytes
The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used.
string display_name = 3;- Parameters:
value- The bytes for displayName to set.- Returns:
- This builder for chaining.
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hasCreateTime
public boolean hasCreateTime()Output only. Timestamp when the DeployedModel was created.
.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
hasCreateTimein interfaceDeployedModelOrBuilder- Returns:
- Whether the createTime field is set.
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getCreateTime
public 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];- Specified by:
getCreateTimein interfaceDeployedModelOrBuilder- Returns:
- The createTime.
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setCreateTime
Output only. Timestamp when the DeployedModel was created.
.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
setCreateTime
Output only. Timestamp when the DeployedModel was created.
.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
mergeCreateTime
Output only. Timestamp when the DeployedModel was created.
.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
clearCreateTime
Output only. Timestamp when the DeployedModel was created.
.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
getCreateTimeBuilder
public com.google.protobuf.Timestamp.Builder getCreateTimeBuilder()Output only. Timestamp when the DeployedModel was created.
.google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
getCreateTimeOrBuilder
public 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];- Specified by:
getCreateTimeOrBuilderin interfaceDeployedModelOrBuilder
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hasExplanationSpec
public boolean hasExplanationSpec()Explanation configuration for this DeployedModel. When deploying a Model using [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel], this value overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]. All fields of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] are optional in the request. If a field of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] is not populated, the value of the same field of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is inherited. If the corresponding [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is not populated, all fields of the [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] will be used for the explanation configuration.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9;- Specified by:
hasExplanationSpecin interfaceDeployedModelOrBuilder- Returns:
- Whether the explanationSpec field is set.
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getExplanationSpec
Explanation configuration for this DeployedModel. When deploying a Model using [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel], this value overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]. All fields of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] are optional in the request. If a field of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] is not populated, the value of the same field of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is inherited. If the corresponding [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is not populated, all fields of the [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] will be used for the explanation configuration.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9;- Specified by:
getExplanationSpecin interfaceDeployedModelOrBuilder- Returns:
- The explanationSpec.
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setExplanationSpec
Explanation configuration for this DeployedModel. When deploying a Model using [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel], this value overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]. All fields of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] are optional in the request. If a field of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] is not populated, the value of the same field of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is inherited. If the corresponding [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is not populated, all fields of the [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] will be used for the explanation configuration.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9; -
setExplanationSpec
Explanation configuration for this DeployedModel. When deploying a Model using [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel], this value overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]. All fields of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] are optional in the request. If a field of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] is not populated, the value of the same field of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is inherited. If the corresponding [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is not populated, all fields of the [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] will be used for the explanation configuration.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9; -
mergeExplanationSpec
Explanation configuration for this DeployedModel. When deploying a Model using [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel], this value overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]. All fields of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] are optional in the request. If a field of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] is not populated, the value of the same field of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is inherited. If the corresponding [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is not populated, all fields of the [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] will be used for the explanation configuration.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9; -
clearExplanationSpec
Explanation configuration for this DeployedModel. When deploying a Model using [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel], this value overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]. All fields of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] are optional in the request. If a field of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] is not populated, the value of the same field of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is inherited. If the corresponding [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is not populated, all fields of the [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] will be used for the explanation configuration.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9; -
getExplanationSpecBuilder
Explanation configuration for this DeployedModel. When deploying a Model using [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel], this value overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]. All fields of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] are optional in the request. If a field of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] is not populated, the value of the same field of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is inherited. If the corresponding [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is not populated, all fields of the [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] will be used for the explanation configuration.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9; -
getExplanationSpecOrBuilder
Explanation configuration for this DeployedModel. When deploying a Model using [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel], this value overrides the value of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]. All fields of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] are optional in the request. If a field of [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] is not populated, the value of the same field of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is inherited. If the corresponding [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] is not populated, all fields of the [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] will be used for the explanation configuration.
.google.cloud.aiplatform.v1.ExplanationSpec explanation_spec = 9;- Specified by:
getExplanationSpecOrBuilderin interfaceDeployedModelOrBuilder
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getDisableExplanations
public boolean getDisableExplanations()If true, deploy the model without explainable feature, regardless the existence of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] or [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec].
bool disable_explanations = 19;- Specified by:
getDisableExplanationsin interfaceDeployedModelOrBuilder- Returns:
- The disableExplanations.
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setDisableExplanations
If true, deploy the model without explainable feature, regardless the existence of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] or [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec].
bool disable_explanations = 19;- Parameters:
value- The disableExplanations to set.- Returns:
- This builder for chaining.
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clearDisableExplanations
If true, deploy the model without explainable feature, regardless the existence of [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec] or [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec].
bool disable_explanations = 19;- Returns:
- This builder for chaining.
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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;- Specified by:
getServiceAccountin interfaceDeployedModelOrBuilder- Returns:
- The serviceAccount.
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getServiceAccountBytes
public 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;- Specified by:
getServiceAccountBytesin interfaceDeployedModelOrBuilder- Returns:
- The bytes for serviceAccount.
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setServiceAccount
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;- Parameters:
value- The serviceAccount to set.- Returns:
- This builder for chaining.
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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:
- This builder for chaining.
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setServiceAccountBytes
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;- Parameters:
value- The bytes for serviceAccount to set.- Returns:
- This builder for chaining.
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getDisableContainerLogging
public 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](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.
bool disable_container_logging = 15;- Specified by:
getDisableContainerLoggingin interfaceDeployedModelOrBuilder- Returns:
- The disableContainerLogging.
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setDisableContainerLogging
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](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.
bool disable_container_logging = 15;- Parameters:
value- The disableContainerLogging to set.- Returns:
- This builder for chaining.
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clearDisableContainerLogging
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](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true.
bool disable_container_logging = 15;- Returns:
- This builder for chaining.
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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;- Specified by:
getEnableAccessLoggingin interfaceDeployedModelOrBuilder- Returns:
- The enableAccessLogging.
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setEnableAccessLogging
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;- Parameters:
value- The enableAccessLogging to set.- Returns:
- This builder for chaining.
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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:
- This builder for chaining.
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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][google.cloud.aiplatform.v1.Endpoint.network] is configured.
.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
hasPrivateEndpointsin interfaceDeployedModelOrBuilder- Returns:
- Whether the privateEndpoints field is set.
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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.v1.Endpoint.network] is configured.
.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
getPrivateEndpointsin interfaceDeployedModelOrBuilder- Returns:
- The privateEndpoints.
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setPrivateEndpoints
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.v1.Endpoint.network] is configured.
.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
setPrivateEndpoints
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.v1.Endpoint.network] is configured.
.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
mergePrivateEndpoints
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.v1.Endpoint.network] is configured.
.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
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][google.cloud.aiplatform.v1.Endpoint.network] is configured.
.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
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][google.cloud.aiplatform.v1.Endpoint.network] is configured.
.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
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.v1.Endpoint.network] is configured.
.google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
getPrivateEndpointsOrBuilderin interfaceDeployedModelOrBuilder
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hasFasterDeploymentConfig
public boolean hasFasterDeploymentConfig()Configuration for faster model deployment.
.google.cloud.aiplatform.v1.FasterDeploymentConfig faster_deployment_config = 23;- Specified by:
hasFasterDeploymentConfigin interfaceDeployedModelOrBuilder- Returns:
- Whether the fasterDeploymentConfig field is set.
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getFasterDeploymentConfig
Configuration for faster model deployment.
.google.cloud.aiplatform.v1.FasterDeploymentConfig faster_deployment_config = 23;- Specified by:
getFasterDeploymentConfigin interfaceDeployedModelOrBuilder- Returns:
- The fasterDeploymentConfig.
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setFasterDeploymentConfig
Configuration for faster model deployment.
.google.cloud.aiplatform.v1.FasterDeploymentConfig faster_deployment_config = 23; -
setFasterDeploymentConfig
public DeployedModel.Builder setFasterDeploymentConfig(FasterDeploymentConfig.Builder builderForValue) Configuration for faster model deployment.
.google.cloud.aiplatform.v1.FasterDeploymentConfig faster_deployment_config = 23; -
mergeFasterDeploymentConfig
Configuration for faster model deployment.
.google.cloud.aiplatform.v1.FasterDeploymentConfig faster_deployment_config = 23; -
clearFasterDeploymentConfig
Configuration for faster model deployment.
.google.cloud.aiplatform.v1.FasterDeploymentConfig faster_deployment_config = 23; -
getFasterDeploymentConfigBuilder
Configuration for faster model deployment.
.google.cloud.aiplatform.v1.FasterDeploymentConfig faster_deployment_config = 23; -
getFasterDeploymentConfigOrBuilder
Configuration for faster model deployment.
.google.cloud.aiplatform.v1.FasterDeploymentConfig faster_deployment_config = 23;- Specified by:
getFasterDeploymentConfigOrBuilderin interfaceDeployedModelOrBuilder
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hasStatus
public boolean hasStatus()Output only. Runtime status of the deployed model.
.google.cloud.aiplatform.v1.DeployedModel.Status status = 26 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
hasStatusin interfaceDeployedModelOrBuilder- Returns:
- Whether the status field is set.
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getStatus
Output only. Runtime status of the deployed model.
.google.cloud.aiplatform.v1.DeployedModel.Status status = 26 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
getStatusin interfaceDeployedModelOrBuilder- Returns:
- The status.
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setStatus
Output only. Runtime status of the deployed model.
.google.cloud.aiplatform.v1.DeployedModel.Status status = 26 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
setStatus
Output only. Runtime status of the deployed model.
.google.cloud.aiplatform.v1.DeployedModel.Status status = 26 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
mergeStatus
Output only. Runtime status of the deployed model.
.google.cloud.aiplatform.v1.DeployedModel.Status status = 26 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
clearStatus
Output only. Runtime status of the deployed model.
.google.cloud.aiplatform.v1.DeployedModel.Status status = 26 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
getStatusBuilder
Output only. Runtime status of the deployed model.
.google.cloud.aiplatform.v1.DeployedModel.Status status = 26 [(.google.api.field_behavior) = OUTPUT_ONLY]; -
getStatusOrBuilder
Output only. Runtime status of the deployed model.
.google.cloud.aiplatform.v1.DeployedModel.Status status = 26 [(.google.api.field_behavior) = OUTPUT_ONLY];- Specified by:
getStatusOrBuilderin interfaceDeployedModelOrBuilder
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getSystemLabelsCount
public int getSystemLabelsCount()Description copied from interface:DeployedModelOrBuilderSystem labels to apply to Model Garden deployments. System labels are managed by Google for internal use only.
map<string, string> system_labels = 28;- Specified by:
getSystemLabelsCountin interfaceDeployedModelOrBuilder
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containsSystemLabels
System labels to apply to Model Garden deployments. System labels are managed by Google for internal use only.
map<string, string> system_labels = 28;- Specified by:
containsSystemLabelsin interfaceDeployedModelOrBuilder
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getSystemLabels
Deprecated.UsegetSystemLabelsMap()instead.- Specified by:
getSystemLabelsin interfaceDeployedModelOrBuilder
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getSystemLabelsMap
System labels to apply to Model Garden deployments. System labels are managed by Google for internal use only.
map<string, string> system_labels = 28;- Specified by:
getSystemLabelsMapin interfaceDeployedModelOrBuilder
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getSystemLabelsOrDefault
System labels to apply to Model Garden deployments. System labels are managed by Google for internal use only.
map<string, string> system_labels = 28;- Specified by:
getSystemLabelsOrDefaultin interfaceDeployedModelOrBuilder
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getSystemLabelsOrThrow
System labels to apply to Model Garden deployments. System labels are managed by Google for internal use only.
map<string, string> system_labels = 28;- Specified by:
getSystemLabelsOrThrowin interfaceDeployedModelOrBuilder
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clearSystemLabels
-
removeSystemLabels
System labels to apply to Model Garden deployments. System labels are managed by Google for internal use only.
map<string, string> system_labels = 28; -
getMutableSystemLabels
Deprecated.Use alternate mutation accessors instead. -
putSystemLabels
System labels to apply to Model Garden deployments. System labels are managed by Google for internal use only.
map<string, string> system_labels = 28; -
putAllSystemLabels
System labels to apply to Model Garden deployments. System labels are managed by Google for internal use only.
map<string, string> system_labels = 28; -
getCheckpointId
The checkpoint id of the model.
string checkpoint_id = 29;- Specified by:
getCheckpointIdin interfaceDeployedModelOrBuilder- Returns:
- The checkpointId.
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getCheckpointIdBytes
public com.google.protobuf.ByteString getCheckpointIdBytes()The checkpoint id of the model.
string checkpoint_id = 29;- Specified by:
getCheckpointIdBytesin interfaceDeployedModelOrBuilder- Returns:
- The bytes for checkpointId.
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setCheckpointId
The checkpoint id of the model.
string checkpoint_id = 29;- Parameters:
value- The checkpointId to set.- Returns:
- This builder for chaining.
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clearCheckpointId
The checkpoint id of the model.
string checkpoint_id = 29;- Returns:
- This builder for chaining.
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setCheckpointIdBytes
The checkpoint id of the model.
string checkpoint_id = 29;- Parameters:
value- The bytes for checkpointId to set.- Returns:
- This builder for chaining.
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hasSpeculativeDecodingSpec
public boolean hasSpeculativeDecodingSpec()Optional. Spec for configuring speculative decoding.
.google.cloud.aiplatform.v1.SpeculativeDecodingSpec speculative_decoding_spec = 30 [(.google.api.field_behavior) = OPTIONAL];- Specified by:
hasSpeculativeDecodingSpecin interfaceDeployedModelOrBuilder- Returns:
- Whether the speculativeDecodingSpec field is set.
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getSpeculativeDecodingSpec
Optional. Spec for configuring speculative decoding.
.google.cloud.aiplatform.v1.SpeculativeDecodingSpec speculative_decoding_spec = 30 [(.google.api.field_behavior) = OPTIONAL];- Specified by:
getSpeculativeDecodingSpecin interfaceDeployedModelOrBuilder- Returns:
- The speculativeDecodingSpec.
-
setSpeculativeDecodingSpec
Optional. Spec for configuring speculative decoding.
.google.cloud.aiplatform.v1.SpeculativeDecodingSpec speculative_decoding_spec = 30 [(.google.api.field_behavior) = OPTIONAL]; -
setSpeculativeDecodingSpec
public DeployedModel.Builder setSpeculativeDecodingSpec(SpeculativeDecodingSpec.Builder builderForValue) Optional. Spec for configuring speculative decoding.
.google.cloud.aiplatform.v1.SpeculativeDecodingSpec speculative_decoding_spec = 30 [(.google.api.field_behavior) = OPTIONAL]; -
mergeSpeculativeDecodingSpec
Optional. Spec for configuring speculative decoding.
.google.cloud.aiplatform.v1.SpeculativeDecodingSpec speculative_decoding_spec = 30 [(.google.api.field_behavior) = OPTIONAL]; -
clearSpeculativeDecodingSpec
Optional. Spec for configuring speculative decoding.
.google.cloud.aiplatform.v1.SpeculativeDecodingSpec speculative_decoding_spec = 30 [(.google.api.field_behavior) = OPTIONAL]; -
getSpeculativeDecodingSpecBuilder
Optional. Spec for configuring speculative decoding.
.google.cloud.aiplatform.v1.SpeculativeDecodingSpec speculative_decoding_spec = 30 [(.google.api.field_behavior) = OPTIONAL]; -
getSpeculativeDecodingSpecOrBuilder
Optional. Spec for configuring speculative decoding.
.google.cloud.aiplatform.v1.SpeculativeDecodingSpec speculative_decoding_spec = 30 [(.google.api.field_behavior) = OPTIONAL];- Specified by:
getSpeculativeDecodingSpecOrBuilderin interfaceDeployedModelOrBuilder
-